From 4af524f4eddd4b0cdd9f331ae134c254961fa714 Mon Sep 17 00:00:00 2001 From: Taylor Salo Date: Mon, 8 Jun 2020 20:39:38 -0400 Subject: [PATCH] Add NARPS paper. --- articles.csv | 207 +++++++++--------- assets/images/papers/nature.png | Bin 0 -> 13323 bytes grab_articles.ipynb | 11 +- ...06-08-botvinik-nezer-variability-in-the.md | 40 ++++ team/_posts/2017-05-13-perez-aleymi.md | 2 +- 5 files changed, 150 insertions(+), 110 deletions(-) create mode 100644 assets/images/papers/nature.png create mode 100644 papers/_posts/2020-06-08-botvinik-nezer-variability-in-the.md diff --git a/articles.csv b/articles.csv index 7f8fcb95..a006ea84 100644 --- a/articles.csv +++ b/articles.csv @@ -1,141 +1,142 @@ pmid,pmcid,doi,title,authors,year,month,day,journal,volume,issue,pages,abstract -21305667,PMC4791073,10.1002/hbm.21186,Minimizing within-experiment and within-group effects in Activation Likelihood Estimation meta-analyses,"['Turkeltaub PE', 'Eickhoff SB', 'Laird AR', 'Fox M', 'Wiener M', 'Fox P']",2012,1,17,Hum Brain Mapp,33,1,1-13,"Activation Likelihood Estimation (ALE) is an objective, quantitative technique for coordinate-based meta-analysis (CBMA) of neuroimaging results that has been validated for a variety of uses. Stepwise modifications have improved ALE's theoretical and statistical rigor since its introduction. Here, we evaluate two avenues to further optimize ALE. First, we demonstrate that the maximum contribution of an experiment makes to an ALE map is related to the number of foci it reports and their proximity. We present a modified ALE algorithm that eliminates these within-experiment effects. However, we show that these effects only account for 2-3% of cumulative ALE values, and removing them has little impact on thresholded ALE maps. Next, we present an alternate organizational approach to datasets that prevents subject groups with multiple experiments in a dataset from influencing ALE values more than others. This modification decreases cumulative ALE values by 7-9%, changes the relative magnitude of some clusters, and reduces cluster extents. Overall, differences between results of the standard approach and these new methods were small. This finding validates previous ALE reports against concerns that they were driven by within-experiment or within-group effects. We suggest that the modified ALE algorithm is theoretically advantageous compared with the current algorithm, and that the alternate organization of datasets is the most conservative approach for typical ALE analyses and other CBMA methods. Combining the two modifications minimizes both within-experiment and within-group effects, optimizing the degree to which ALE values represent concordance of findings across independent reports." -21643732,PMC3682219,10.1007/s12021-011-9126-x,The cognitive paradigm ontology: design and application,"['Turner JA', 'Laird AR']",2012,1,17,Neuroinformatics,10,1,57-66,"We present the basic structure of the Cognitive Paradigm Ontology (CogPO) for human behavioral experiments. While the experimental psychology and cognitive neuroscience literature may refer to certain behavioral tasks by name (e.g., the Stroop paradigm or the Sternberg paradigm) or by function (a working memory task, a visual attention task), these paradigms can vary tremendously in the stimuli that are presented to the subject, the response expected from the subject, and the instructions given to the subject. Drawing from the taxonomy developed and used by the BrainMap project ( www.brainmap.org ) for almost two decades to describe key components of published functional imaging results, we have developed an ontology capable of representing certain characteristics of the cognitive paradigms used in the fMRI and PET literature. The Cognitive Paradigm Ontology is being developed to be compliant with the Basic Formal Ontology (BFO), and to harmonize where possible with larger ontologies such as RadLex, NeuroLex, or the Ontology of Biomedical Investigations (OBI). The key components of CogPO include the representation of experimental conditions focused on the stimuli presented, the instructions given, and the responses requested. The use of alternate and even competitive terminologies can often impede scientific discoveries. Categorization of paradigms according to stimulus, response, and instruction has been shown to allow advanced data retrieval techniques by searching for similarities and contrasts across multiple paradigm levels. The goal of CogPO is to develop, evaluate, and distribute a domain ontology of cognitive paradigms for application and use in the functional neuroimaging community." -21667303,PMC4791066,10.1007/s00429-011-0333-x,Neuroanatomic changes and their association with cognitive decline in mild cognitive impairment: a meta-analysis,"['Nickl-Jockschat T', 'Kleiman A', 'Schulz JB', 'Schneider F', 'Laird AR', 'Fox PT', 'Eickhoff SB', 'Reetz K']",2012,1,17,Brain Struct Funct,217,1,115-25,"Mild cognitive impairment (MCI) is an acquired syndrome characterised by cognitive decline not affecting activities of daily living. Using a quantitative meta-analytic approach, we aimed to identify consistent neuroanatomic correlates of MCI and how they are related to cognitive dysfunction. The meta-analysis enrols 22 studies, involving 917 MCI (848 amnestic MCI) patients and 809 healthy controls. Only studies investigating local changes in grey matter and reporting whole-brain results in stereotactic coordinates were included and analysed using the activation likelihood estimation approach. Probabilistic cytoarchitectonic maps were used to compare the localization of the obtained significant effects to histological areas. A correlation between the probability of grey matter changes and cognitive performance of MCI patients was performed. In MCI patients, the meta-analysis revealed three significant clusters of convergent grey matter atrophy, which were mainly situated in the bilateral amygdala and hippocampus, extending to the left medial temporal pole and thalamus, as well as in the bilateral precuneus. A sub-analysis in only amnestic MCI revealed a similar pattern. A voxel-wise analysis revealed a correlation between grey matter reduction and cognitive decline in the right hippocampus and amygdala as well as in the left thalamus. This study provides convergent evidence of a distinct neuroanatomical pattern in MCI. The correlation analysis with cognitive-mnestic decline further highlights the impact of limbic structures and the linkage with data from a functional neuroimaging database provides additional insight into underlying functions. Although different pathologies are underlying MCI, the observed neuroanatomical pattern of structural changes may reflect the common clinical denominator of cognitive impairment." -21692142,PMC4801488,10.1002/hbm.21299,Brain structure anomalies in autism spectrum disorder--a meta-analysis of VBM studies using anatomic likelihood estimation,"['Nickl-Jockschat T', 'Habel U', 'Michel TM', 'Manning J', 'Laird AR', 'Fox PT', 'Schneider F', 'Eickhoff SB']",2012,6,17,Hum Brain Mapp,33,6,1470-89,"Autism spectrum disorders (ASD) are pervasive developmental disorders with characteristic core symptoms such as impairments in social interaction, deviance in communication, repetitive and stereotyped behavior, and impaired motor skills. Anomalies of brain structure have repeatedly been hypothesized to play a major role in the etiopathogenesis of the disorder. Our objective was to perform unbiased meta-analysis on brain structure changes as reported in the current ASD literature. We thus conducted a comprehensive search for morphometric studies by Pubmed query and literature review. We used a revised version of the activation likelihood estimation (ALE) approach for coordinate-based meta-analysis of neuroimaging results. Probabilistic cytoarchitectonic maps were applied to compare the localization of the obtained significant effects to histological areas. Each of the significant ALE clusters was analyzed separately for age effects on gray and white matter density changes. We found six significant clusters of convergence indicating disturbances in the brain structure of ASD patients, including the lateral occipital lobe, the pericentral region, the medial temporal lobe, the basal ganglia, and proximate to the right parietal operculum. Our study provides the first quantitative summary of brain structure changes reported in literature on autism spectrum disorders. In contrast to the rather small sample sizes of the original studies, our meta-analysis encompasses data of 277 ASD patients and 303 healthy controls. This unbiased summary provided evidence for consistent structural abnormalities in spite of heterogeneous diagnostic criteria and voxel-based morphometry (VBM) methodology, but also hinted at a dependency of VBM findings on the age of the patients." -21949904,PMC3178148,10.1155/2012/907409,"Multimodal MRI neuroimaging biomarkers for cognitive normal adults, amnestic mild cognitive impairment, and Alzheimer's disease","['Lin AL', 'Laird AR', 'Fox PT', 'Gao JH']",2012,3,17,Neurol Res Int,2012,,907409,"Multimodal magnetic resonance imaging (MRI) techniques have been developed to noninvasively measure structural, metabolic, hemodynamic and functional changes of the brain. These advantages have made MRI an important tool to investigate neurodegenerative disorders, including diagnosis, disease progression monitoring, and treatment efficacy evaluation. This paper discusses recent findings of the multimodal MRI in the context of surrogate biomarkers for identifying the risk for AD in normal cognitive (NC) adults, brain anatomical and functional alterations in amnestic mild cognitive impairment (aMCI), and Alzheimer's disease (AD) patients. Further developments of these techniques and the establishment of promising neuroimaging biomarkers will enhance our ability to diagnose aMCI and AD in their early stages and improve the assessment of therapeutic efficacy in these diseases in future clinical trials." +21305667,PMC4791073,10.1002/hbm.21186,Minimizing within-experiment and within-group effects in Activation Likelihood Estimation meta-analyses,"['Turkeltaub PE', 'Eickhoff SB', 'Laird AR', 'Fox M', 'Wiener M', 'Fox P']",2012,1,8,Hum Brain Mapp,33,1,1-13,"Activation Likelihood Estimation (ALE) is an objective, quantitative technique for coordinate-based meta-analysis (CBMA) of neuroimaging results that has been validated for a variety of uses. Stepwise modifications have improved ALE's theoretical and statistical rigor since its introduction. Here, we evaluate two avenues to further optimize ALE. First, we demonstrate that the maximum contribution of an experiment makes to an ALE map is related to the number of foci it reports and their proximity. We present a modified ALE algorithm that eliminates these within-experiment effects. However, we show that these effects only account for 2-3% of cumulative ALE values, and removing them has little impact on thresholded ALE maps. Next, we present an alternate organizational approach to datasets that prevents subject groups with multiple experiments in a dataset from influencing ALE values more than others. This modification decreases cumulative ALE values by 7-9%, changes the relative magnitude of some clusters, and reduces cluster extents. Overall, differences between results of the standard approach and these new methods were small. This finding validates previous ALE reports against concerns that they were driven by within-experiment or within-group effects. We suggest that the modified ALE algorithm is theoretically advantageous compared with the current algorithm, and that the alternate organization of datasets is the most conservative approach for typical ALE analyses and other CBMA methods. Combining the two modifications minimizes both within-experiment and within-group effects, optimizing the degree to which ALE values represent concordance of findings across independent reports." +21643732,PMC3682219,10.1007/s12021-011-9126-x,The cognitive paradigm ontology: design and application,"['Turner JA', 'Laird AR']",2012,1,8,Neuroinformatics,10,1,57-66,"We present the basic structure of the Cognitive Paradigm Ontology (CogPO) for human behavioral experiments. While the experimental psychology and cognitive neuroscience literature may refer to certain behavioral tasks by name (e.g., the Stroop paradigm or the Sternberg paradigm) or by function (a working memory task, a visual attention task), these paradigms can vary tremendously in the stimuli that are presented to the subject, the response expected from the subject, and the instructions given to the subject. Drawing from the taxonomy developed and used by the BrainMap project ( www.brainmap.org ) for almost two decades to describe key components of published functional imaging results, we have developed an ontology capable of representing certain characteristics of the cognitive paradigms used in the fMRI and PET literature. The Cognitive Paradigm Ontology is being developed to be compliant with the Basic Formal Ontology (BFO), and to harmonize where possible with larger ontologies such as RadLex, NeuroLex, or the Ontology of Biomedical Investigations (OBI). The key components of CogPO include the representation of experimental conditions focused on the stimuli presented, the instructions given, and the responses requested. The use of alternate and even competitive terminologies can often impede scientific discoveries. Categorization of paradigms according to stimulus, response, and instruction has been shown to allow advanced data retrieval techniques by searching for similarities and contrasts across multiple paradigm levels. The goal of CogPO is to develop, evaluate, and distribute a domain ontology of cognitive paradigms for application and use in the functional neuroimaging community." +21667303,PMC4791066,10.1007/s00429-011-0333-x,Neuroanatomic changes and their association with cognitive decline in mild cognitive impairment: a meta-analysis,"['Nickl-Jockschat T', 'Kleiman A', 'Schulz JB', 'Schneider F', 'Laird AR', 'Fox PT', 'Eickhoff SB', 'Reetz K']",2012,1,8,Brain Struct Funct,217,1,115-25,"Mild cognitive impairment (MCI) is an acquired syndrome characterised by cognitive decline not affecting activities of daily living. Using a quantitative meta-analytic approach, we aimed to identify consistent neuroanatomic correlates of MCI and how they are related to cognitive dysfunction. The meta-analysis enrols 22 studies, involving 917 MCI (848 amnestic MCI) patients and 809 healthy controls. Only studies investigating local changes in grey matter and reporting whole-brain results in stereotactic coordinates were included and analysed using the activation likelihood estimation approach. Probabilistic cytoarchitectonic maps were used to compare the localization of the obtained significant effects to histological areas. A correlation between the probability of grey matter changes and cognitive performance of MCI patients was performed. In MCI patients, the meta-analysis revealed three significant clusters of convergent grey matter atrophy, which were mainly situated in the bilateral amygdala and hippocampus, extending to the left medial temporal pole and thalamus, as well as in the bilateral precuneus. A sub-analysis in only amnestic MCI revealed a similar pattern. A voxel-wise analysis revealed a correlation between grey matter reduction and cognitive decline in the right hippocampus and amygdala as well as in the left thalamus. This study provides convergent evidence of a distinct neuroanatomical pattern in MCI. The correlation analysis with cognitive-mnestic decline further highlights the impact of limbic structures and the linkage with data from a functional neuroimaging database provides additional insight into underlying functions. Although different pathologies are underlying MCI, the observed neuroanatomical pattern of structural changes may reflect the common clinical denominator of cognitive impairment." +21692142,PMC4801488,10.1002/hbm.21299,Brain structure anomalies in autism spectrum disorder--a meta-analysis of VBM studies using anatomic likelihood estimation,"['Nickl-Jockschat T', 'Habel U', 'Michel TM', 'Manning J', 'Laird AR', 'Fox PT', 'Schneider F', 'Eickhoff SB']",2012,6,8,Hum Brain Mapp,33,6,1470-89,"Autism spectrum disorders (ASD) are pervasive developmental disorders with characteristic core symptoms such as impairments in social interaction, deviance in communication, repetitive and stereotyped behavior, and impaired motor skills. Anomalies of brain structure have repeatedly been hypothesized to play a major role in the etiopathogenesis of the disorder. Our objective was to perform unbiased meta-analysis on brain structure changes as reported in the current ASD literature. We thus conducted a comprehensive search for morphometric studies by Pubmed query and literature review. We used a revised version of the activation likelihood estimation (ALE) approach for coordinate-based meta-analysis of neuroimaging results. Probabilistic cytoarchitectonic maps were applied to compare the localization of the obtained significant effects to histological areas. Each of the significant ALE clusters was analyzed separately for age effects on gray and white matter density changes. We found six significant clusters of convergence indicating disturbances in the brain structure of ASD patients, including the lateral occipital lobe, the pericentral region, the medial temporal lobe, the basal ganglia, and proximate to the right parietal operculum. Our study provides the first quantitative summary of brain structure changes reported in literature on autism spectrum disorders. In contrast to the rather small sample sizes of the original studies, our meta-analysis encompasses data of 277 ASD patients and 303 healthy controls. This unbiased summary provided evidence for consistent structural abnormalities in spite of heterogeneous diagnostic criteria and voxel-based morphometry (VBM) methodology, but also hinted at a dependency of VBM findings on the age of the patients." +21949904,PMC3178148,10.1155/2012/907409,"Multimodal MRI neuroimaging biomarkers for cognitive normal adults, amnestic mild cognitive impairment, and Alzheimer's disease","['Lin AL', 'Laird AR', 'Fox PT', 'Gao JH']",2012,6,8,Neurol Res Int,2012,,907409,"Multimodal magnetic resonance imaging (MRI) techniques have been developed to noninvasively measure structural, metabolic, hemodynamic and functional changes of the brain. These advantages have made MRI an important tool to investigate neurodegenerative disorders, including diagnosis, disease progression monitoring, and treatment efficacy evaluation. This paper discusses recent findings of the multimodal MRI in the context of surrogate biomarkers for identifying the risk for AD in normal cognitive (NC) adults, brain anatomical and functional alterations in amnestic mild cognitive impairment (aMCI), and Alzheimer's disease (AD) patients. Further developments of these techniques and the establishment of promising neuroimaging biomarkers will enhance our ability to diagnose aMCI and AD in their early stages and improve the assessment of therapeutic efficacy in these diseases in future clinical trials." 21963913,PMC3254820,10.1016/j.neuroimage.2011.09.017,Activation likelihood estimation meta-analysis revisited,"['Eickhoff SB', 'Bzdok D', 'Laird AR', 'Kurth F', 'Fox PT']",2012,2,1,Neuroimage,59,3,2349-61,"A widely used technique for coordinate-based meta-analysis of neuroimaging data is activation likelihood estimation (ALE), which determines the convergence of foci reported from different experiments. ALE analysis involves modelling these foci as probability distributions whose width is based on empirical estimates of the spatial uncertainty due to the between-subject and between-template variability of neuroimaging data. ALE results are assessed against a null-distribution of random spatial association between experiments, resulting in random-effects inference. In the present revision of this algorithm, we address two remaining drawbacks of the previous algorithm. First, the assessment of spatial association between experiments was based on a highly time-consuming permutation test, which nevertheless entailed the danger of underestimating the right tail of the null-distribution. In this report, we outline how this previous approach may be replaced by a faster and more precise analytical method. Second, the previously applied correction procedure, i.e. controlling the false discovery rate (FDR), is supplemented by new approaches for correcting the family-wise error rate and the cluster-level significance. The different alternatives for drawing inference on meta-analytic results are evaluated on an exemplary dataset on face perception as well as discussed with respect to their methodological limitations and advantages. In summary, we thus replaced the previous permutation algorithm with a faster and more rigorous analytical solution for the null-distribution and comprehensively address the issue of multiple-comparison corrections. The proposed revision of the ALE-algorithm should provide an improved tool for conducting coordinate-based meta-analyses on functional imaging data." -22178808,PMC3288533,10.1016/j.neuroimage.2011.11.050,Modelling neural correlates of working memory: a coordinate-based meta-analysis,"['Rottschy C', 'Langner R', 'Dogan I', 'Reetz K', 'Laird AR', 'Schulz JB', 'Fox PT', 'Eickhoff SB']",2012,3,17,Neuroimage,60,1,830-46,"Working memory subsumes the capability to memorize, retrieve and utilize information for a limited period of time which is essential to many human behaviours. Moreover, impairments of working memory functions may be found in nearly all neurological and psychiatric diseases. To examine what brain regions are commonly and differently active during various working memory tasks, we performed a coordinate-based meta-analysis over 189 fMRI experiments on healthy subjects. The main effect yielded a widespread bilateral fronto-parietal network. Further meta-analyses revealed that several regions were sensitive to specific task components, e.g. Broca's region was selectively active during verbal tasks or ventral and dorsal premotor cortex were preferentially involved in memory for object identity and location, respectively. Moreover, the lateral prefrontal cortex showed a division in a rostral and a caudal part based on differential involvement in task set and load effects. Nevertheless, a consistent but more restricted ""core"" network emerged from conjunctions across analyses of specific task designs and contrasts. This ""core"" network appears to comprise the quintessence of regions, which are necessary during working memory tasks. It may be argued that the core regions form a distributed executive network with potentially generalized functions for focussing on competing representations in the brain. The present study demonstrates that meta-analyses are a powerful tool to integrate the data of functional imaging studies on a (broader) psychological construct, probing the consistency across various paradigms as well as the differential effects of different experimental implementations." -22197743,PMC3288226,10.1016/j.neuroimage.2011.12.010,The functional connectivity of the human caudate: an application of meta-analytic connectivity modeling with behavioral filtering,"['Robinson JL', 'Laird AR', 'Glahn DC', 'Blangero J', 'Sanghera MK', 'Pessoa L', 'Fox PM', 'Uecker A', 'Friehs G', 'Young KA', 'Griffin JL', 'Lovallo WR', 'Fox PT']",2012,3,17,Neuroimage,60,1,117-29,"Meta-analysis based techniques are emerging as powerful, robust tools for developing models of connectivity in functional neuroimaging. Here, we apply meta-analytic connectivity modeling to the human caudate to 1) develop a model of functional connectivity, 2) determine if meta-analytic methods are sufficiently sensitive to detect behavioral domain specificity within region-specific functional connectivity networks, and 3) compare meta-analytic driven segmentation to structural connectivity parcellation using diffusion tensor imaging. Results demonstrate strong coherence between meta-analytic and data-driven methods. Specifically, we found that behavioral filtering resulted in cognition and emotion related structures and networks primarily localized to the head of the caudate nucleus, while perceptual and action specific regions localized to the body of the caudate, consistent with early models of nonhuman primate histological studies and postmortem studies in humans. Diffusion tensor imaging (DTI) revealed support for meta-analytic connectivity modeling's (MACM) utility in identifying both direct and indirect connectivity. Our results provide further validation of meta-analytic connectivity modeling, while also highlighting an additional potential, namely the extraction of behavioral domain specific functional connectivity." -22270812,PMC3445793,10.1007/s00429-012-0380-y,"Parsing the neural correlates of moral cognition: ALE meta-analysis on morality, theory of mind, and empathy","['Bzdok D', 'Schilbach L', 'Vogeley K', 'Schneider K', 'Laird AR', 'Langner R', 'Eickhoff SB']",2012,10,17,Brain Struct Funct,217,4,783-96,"Morally judicious behavior forms the fabric of human sociality. Here, we sought to investigate neural activity associated with different facets of moral thought. Previous research suggests that the cognitive and emotional sources of moral decisions might be closely related to theory of mind, an abstract-cognitive skill, and empathy, a rapid-emotional skill. That is, moral decisions are thought to crucially refer to other persons' representation of intentions and behavioral outcomes as well as (vicariously experienced) emotional states. We thus hypothesized that moral decisions might be implemented in brain areas engaged in 'theory of mind' and empathy. This assumption was tested by conducting a large-scale activation likelihood estimation (ALE) meta-analysis of neuroimaging studies, which assessed 2,607 peak coordinates from 247 experiments in 1,790 participants. The brain areas that were consistently involved in moral decisions showed more convergence with the ALE analysis targeting theory of mind versus empathy. More specifically, the neurotopographical overlap between morality and empathy disfavors a role of affective sharing during moral decisions. Ultimately, our results provide evidence that the neural network underlying moral decisions is probably domain-global and might be dissociable into cognitive and affective sub-systems." -22282036,PMC3660731,10.3758/s13415-011-0083-5,Meta-analytic evidence for a superordinate cognitive control network subserving diverse executive functions,"['Niendam TA', 'Laird AR', 'Ray KL', 'Dean YM', 'Glahn DC', 'Carter CS']",2012,6,17,Cogn Affect Behav Neurosci,12,2,241-68,"Classic cognitive theory conceptualizes executive functions as involving multiple specific domains, including initiation, inhibition, working memory, flexibility, planning, and vigilance. Lesion and neuroimaging experiments over the past two decades have suggested that both common and unique processes contribute to executive functions during higher cognition. It has been suggested that a superordinate fronto-cingulo-parietal network supporting cognitive control may also underlie a range of distinct executive functions. To test this hypothesis in the largest sample to date, we used quantitative meta-analytic methods to analyze 193 functional neuroimaging studies of 2,832 healthy individuals, ages 18-60, in which performance on executive function measures was contrasted with an active control condition. A common pattern of activation was observed in the prefrontal, dorsal anterior cingulate, and parietal cortices across executive function domains, supporting the idea that executive functions are supported by a superordinate cognitive control network. However, domain-specific analyses showed some variation in the recruitment of anterior prefrontal cortex, anterior and midcingulate regions, and unique subcortical regions such as the basal ganglia and cerebellum. These results are consistent with the existence of a superordinate cognitive control network in the brain, involving dorsolateral prefrontal, anterior cingulate, and parietal cortices, that supports a broad range of executive functions." -22319593,PMC3272038,10.1371/journal.pone.0030920,"Introspective minds: using ALE meta-analyses to study commonalities in the neural correlates of emotional processing, social & unconstrained cognition","['Schilbach L', 'Bzdok D', 'Timmermans B', 'Fox PT', 'Laird AR', 'Vogeley K', 'Eickhoff SB']",2012,3,17,PLoS One,7,2,e30920,"Previous research suggests overlap between brain regions that show task-induced deactivations and those activated during the performance of social-cognitive tasks. Here, we present results of quantitative meta-analyses of neuroimaging studies, which confirm a statistical convergence in the neural correlates of social and resting state cognition. Based on the idea that both social and unconstrained cognition might be characterized by introspective processes, which are also thought to be highly relevant for emotional experiences, a third meta-analysis was performed investigating studies on emotional processing. By using conjunction analyses across all three sets of studies, we can demonstrate significant overlap of task-related signal change in dorso-medial prefrontal and medial parietal cortex, brain regions that have, indeed, recently been linked to introspective abilities. Our findings, therefore, provide evidence for the existence of a core neural network, which shows task-related signal change during socio-emotional tasks and during resting states." +22178808,PMC3288533,10.1016/j.neuroimage.2011.11.050,Modelling neural correlates of working memory: a coordinate-based meta-analysis,"['Rottschy C', 'Langner R', 'Dogan I', 'Reetz K', 'Laird AR', 'Schulz JB', 'Fox PT', 'Eickhoff SB']",2012,3,8,Neuroimage,60,1,830-46,"Working memory subsumes the capability to memorize, retrieve and utilize information for a limited period of time which is essential to many human behaviours. Moreover, impairments of working memory functions may be found in nearly all neurological and psychiatric diseases. To examine what brain regions are commonly and differently active during various working memory tasks, we performed a coordinate-based meta-analysis over 189 fMRI experiments on healthy subjects. The main effect yielded a widespread bilateral fronto-parietal network. Further meta-analyses revealed that several regions were sensitive to specific task components, e.g. Broca's region was selectively active during verbal tasks or ventral and dorsal premotor cortex were preferentially involved in memory for object identity and location, respectively. Moreover, the lateral prefrontal cortex showed a division in a rostral and a caudal part based on differential involvement in task set and load effects. Nevertheless, a consistent but more restricted ""core"" network emerged from conjunctions across analyses of specific task designs and contrasts. This ""core"" network appears to comprise the quintessence of regions, which are necessary during working memory tasks. It may be argued that the core regions form a distributed executive network with potentially generalized functions for focussing on competing representations in the brain. The present study demonstrates that meta-analyses are a powerful tool to integrate the data of functional imaging studies on a (broader) psychological construct, probing the consistency across various paradigms as well as the differential effects of different experimental implementations." +22197743,PMC3288226,10.1016/j.neuroimage.2011.12.010,The functional connectivity of the human caudate: an application of meta-analytic connectivity modeling with behavioral filtering,"['Robinson JL', 'Laird AR', 'Glahn DC', 'Blangero J', 'Sanghera MK', 'Pessoa L', 'Fox PM', 'Uecker A', 'Friehs G', 'Young KA', 'Griffin JL', 'Lovallo WR', 'Fox PT']",2012,3,8,Neuroimage,60,1,117-29,"Meta-analysis based techniques are emerging as powerful, robust tools for developing models of connectivity in functional neuroimaging. Here, we apply meta-analytic connectivity modeling to the human caudate to 1) develop a model of functional connectivity, 2) determine if meta-analytic methods are sufficiently sensitive to detect behavioral domain specificity within region-specific functional connectivity networks, and 3) compare meta-analytic driven segmentation to structural connectivity parcellation using diffusion tensor imaging. Results demonstrate strong coherence between meta-analytic and data-driven methods. Specifically, we found that behavioral filtering resulted in cognition and emotion related structures and networks primarily localized to the head of the caudate nucleus, while perceptual and action specific regions localized to the body of the caudate, consistent with early models of nonhuman primate histological studies and postmortem studies in humans. Diffusion tensor imaging (DTI) revealed support for meta-analytic connectivity modeling's (MACM) utility in identifying both direct and indirect connectivity. Our results provide further validation of meta-analytic connectivity modeling, while also highlighting an additional potential, namely the extraction of behavioral domain specific functional connectivity." +22270812,PMC3445793,10.1007/s00429-012-0380-y,"Parsing the neural correlates of moral cognition: ALE meta-analysis on morality, theory of mind, and empathy","['Bzdok D', 'Schilbach L', 'Vogeley K', 'Schneider K', 'Laird AR', 'Langner R', 'Eickhoff SB']",2012,10,8,Brain Struct Funct,217,4,783-96,"Morally judicious behavior forms the fabric of human sociality. Here, we sought to investigate neural activity associated with different facets of moral thought. Previous research suggests that the cognitive and emotional sources of moral decisions might be closely related to theory of mind, an abstract-cognitive skill, and empathy, a rapid-emotional skill. That is, moral decisions are thought to crucially refer to other persons' representation of intentions and behavioral outcomes as well as (vicariously experienced) emotional states. We thus hypothesized that moral decisions might be implemented in brain areas engaged in 'theory of mind' and empathy. This assumption was tested by conducting a large-scale activation likelihood estimation (ALE) meta-analysis of neuroimaging studies, which assessed 2,607 peak coordinates from 247 experiments in 1,790 participants. The brain areas that were consistently involved in moral decisions showed more convergence with the ALE analysis targeting theory of mind versus empathy. More specifically, the neurotopographical overlap between morality and empathy disfavors a role of affective sharing during moral decisions. Ultimately, our results provide evidence that the neural network underlying moral decisions is probably domain-global and might be dissociable into cognitive and affective sub-systems." +22282036,PMC3660731,10.3758/s13415-011-0083-5,Meta-analytic evidence for a superordinate cognitive control network subserving diverse executive functions,"['Niendam TA', 'Laird AR', 'Ray KL', 'Dean YM', 'Glahn DC', 'Carter CS']",2012,6,8,Cogn Affect Behav Neurosci,12,2,241-68,"Classic cognitive theory conceptualizes executive functions as involving multiple specific domains, including initiation, inhibition, working memory, flexibility, planning, and vigilance. Lesion and neuroimaging experiments over the past two decades have suggested that both common and unique processes contribute to executive functions during higher cognition. It has been suggested that a superordinate fronto-cingulo-parietal network supporting cognitive control may also underlie a range of distinct executive functions. To test this hypothesis in the largest sample to date, we used quantitative meta-analytic methods to analyze 193 functional neuroimaging studies of 2,832 healthy individuals, ages 18-60, in which performance on executive function measures was contrasted with an active control condition. A common pattern of activation was observed in the prefrontal, dorsal anterior cingulate, and parietal cortices across executive function domains, supporting the idea that executive functions are supported by a superordinate cognitive control network. However, domain-specific analyses showed some variation in the recruitment of anterior prefrontal cortex, anterior and midcingulate regions, and unique subcortical regions such as the basal ganglia and cerebellum. These results are consistent with the existence of a superordinate cognitive control network in the brain, involving dorsolateral prefrontal, anterior cingulate, and parietal cortices, that supports a broad range of executive functions." +22319593,PMC3272038,10.1371/journal.pone.0030920,"Introspective minds: using ALE meta-analyses to study commonalities in the neural correlates of emotional processing, social & unconstrained cognition","['Schilbach L', 'Bzdok D', 'Timmermans B', 'Fox PT', 'Laird AR', 'Vogeley K', 'Eickhoff SB']",2012,6,8,PLoS One,7,2,e30920,"Previous research suggests overlap between brain regions that show task-induced deactivations and those activated during the performance of social-cognitive tasks. Here, we present results of quantitative meta-analyses of neuroimaging studies, which confirm a statistical convergence in the neural correlates of social and resting state cognition. Based on the idea that both social and unconstrained cognition might be characterized by introspective processes, which are also thought to be highly relevant for emotional experiences, a third meta-analysis was performed investigating studies on emotional processing. By using conjunction analyses across all three sets of studies, we can demonstrate significant overlap of task-related signal change in dorso-medial prefrontal and medial parietal cortex, brain regions that have, indeed, recently been linked to introspective abilities. Our findings, therefore, provide evidence for the existence of a core neural network, which shows task-related signal change during socio-emotional tasks and during resting states." 22326834,PMC3401637,10.1016/j.neuroimage.2012.01.117,Resting state functional connectivity in addiction: Lessons learned and a road ahead,"['Sutherland MT', 'McHugh MJ', 'Pariyadath V', 'Stein EA']",2012,10,1,Neuroimage,62,4,2281-95,"Despite intensive scientific investigation and public health imperatives, drug addiction treatment outcomes have not significantly improved in more than 50 years. Non-invasive brain imaging has, over the past several decades, contributed important new insights into the neuroplastic adaptations that result from chronic drug intake, but additional experimental approaches and neurobiological hypotheses are needed to better capture the totality of the motivational, affective, cognitive, genetic and pharmacological complexities of the disease. Recent advances in assessing network dynamics through resting-state functional connectivity (rsFC) may allow for such systems-level assessments. In this review, we first summarize the nascent addiction-related rsFC literature and suggest that in using this tool, circuit connectivity may inform specific neurobiological substrates underlying psychological dysfunctions associated with reward, affective and cognitive processing often observed in drug addicts. Using nicotine addiction as an exemplar, we subsequently provide a heuristic framework to guide future research by linking recent findings from intrinsic network connectivity studies with those interrogating nicotine's neuropharmacological actions. Emerging evidence supports a critical role for the insula in nicotine addiction. Likewise, the anterior insula, potentially together with the anterior cingulate cortex, appears to pivotally influence the dynamics between large-scale brain networks subserving internal (default-mode network) and external (executive control network) information processing. We suggest that a better understanding of how the insula modulates the interaction between these networks is critical for elucidating both the cognitive impairments often associated with withdrawal and the performance-enhancing effects of nicotine administration. Such an understanding may be usefully applied in the design and development of novel smoking cessation treatments." 22387170,PMC3321133,10.1016/j.neuroimage.2012.02.037,Across-study and within-subject functional connectivity of a right temporo-parietal junction subregion involved in stimulus-context integration,"['Jakobs O', 'Langner R', 'Caspers S', 'Roski C', 'Cieslik EC', 'Zilles K', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2012,5,1,Neuroimage,60,4,2389-98,"Bidirectional integration between sensory stimuli and contextual framing is fundamental to action control. Stimuli may entail context-dependent actions, while temporal or spatial characteristics of a stimulus train may establish a contextual framework for upcoming stimuli. Here we aimed at identifying core areas for stimulus-context integration and delineated their functional connectivity (FC) using meta-analytic connectivity modeling (MACM) and analysis of resting-state networks. In a multi-study conjunction, consistently increased activity under higher demands on stimulus-context integration was predominantly found in the right temporo-parietal junction (TPJ), which represented the largest cluster of overlap and was thus used as the seed for the FC analyses. The conjunction between task-dependent (MACM) and task-free (resting state) FC of the right TPJ revealed a shared network comprising bilaterally inferior parietal and frontal cortices, anterior insula, premotor cortex, putamen and cerebellum, i.e., a 'ventral' action/attention network. Stronger task-dependent (vs. task-free) connectivity was observed with the pre-SMA, dorsal premotor cortex, intraparietal sulcus, basal ganglia and primary sensori motor cortex, while stronger resting-state (vs. task-dependent) connectivity was found with the dorsolateral prefrontal and medial parietal cortex. Our data provide strong evidence that the right TPJ may represent a key region for the integration of sensory stimuli and contextual frames in action control. Task-dependent associations with regions related to stimulus processing and motor responses indicate that the right TPJ may integrate 'collaterals' of sensory processing and apply (ensuing) contextual frames, most likely via modulation of preparatory loops. Given the pattern of resting-state connectivity, internal states and goal representations may provide the substrates for the contextual integration within the TPJ in the absence of a specific task." 22569543,PMC3381058,10.1016/j.neuroimage.2012.04.060,Electrophysiological and functional connectivity of the human supplementary motor area,"['Narayana S', 'Laird AR', 'Tandon N', 'Franklin C', 'Lancaster JL', 'Fox PT']",2012,8,1,Neuroimage,62,1,250-65,"Neuro-imaging methods for detecting functional and structural inter-regional connectivity are in a rapid phase of development. While reports of regional connectivity patterns based on individual methods are becoming common, studies comparing the results of two or more connectivity-mapping methods remain rare. In this study, we applied transcranial magnetic stimulation during PET imaging (TMS/PET), a stimulation-based method, and meta-analytic connectivity modeling (MACM), a task-based method to map the connectivity patterns of the supplementary motor area (SMA). Further, we drew upon the behavioral domain meta-data of the BrainMap(R) database to characterize the behavioral domain specificity of two maps. Both MACM and TMS/PET detected multi-synaptic connectivity patterns, with the MACM-detected connections being more extensive. Both MACM and TMS/PET detected connections belonging to multiple behavioral domains, including action, cognition and perception. Finally, we show that the two connectivity-mapping methods are complementary in that, the MACM informed on the functional nature of SMA connections, while TMS/PET identified brain areas electrophysiologically connected with the SMA. Thus, we demonstrate that integrating multimodal database and imaging techniques can derive comprehensive connectivity maps of brain areas." -22659444,PMC4801477,10.1016/j.neuroimage.2012.05.058,Investigating function and connectivity of morphometric findings--exemplified on cerebellar atrophy in spinocerebellar ataxia 17 (SCA17),"['Reetz K', 'Dogan I', 'Rolfs A', 'Binkofski F', 'Schulz JB', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2012,9,17,Neuroimage,62,3,1354-66,"Spinocerebellar ataxia type 17 (SCA17) is a rare autosomal dominant neurodegenerative disorder characterized by progressive cerebellar ataxia but also a broad spectrum of other neuropsychiatric signs. As anatomical and structural studies have shown severe cerebellar atrophy in SCA17 and a differentiation of the human cerebellum into an anterior sensorimotor and posterior cognitive/emotional partition has been implicated, we aimed at investigating functional connectivity patterns of two cerebellar clusters of atrophy revealed by a morphometric analysis in SCA17 patients. In particular, voxel-based morphometry (VBM) revealed a large cluster of atrophy in SCA17 in the bilateral anterior cerebellum (lobule V) and another one in the left posterior cerebellum (lobules IX, VIIb, VIIIA, VIIIB). These two cerebellar clusters were used as seeds for functional connectivity analyses using task-based meta-analytic connectivity modeling (MACM) and task-free resting state connectivity analysis. Results demonstrated first consistent functional connectivity throughout the cerebellum itself; the anterior cerebellar seed showed stronger connectivity to lobules V, VI and to some extent I-IV, and the posterior cerebellar seed to the posterior lobules VI-IX. Importantly, the cerebellar anterior seed also showed consistently stronger functional connectivity than the posterior one with pre- and motor areas as well as the primary somatosensory cortex. In turn, task-based task-independent functional connectivity analyses revealed that the cerebellar posterior seed was linked with fronto-temporo-parietal areas as well as partly the insula and the thalamus, i.e., brain regions implicated in cognitive and affective processes. Functional characterization of experiments activating either cerebellar seed further corroborated this notion, revealing mainly motor-related functions for the anterior cluster and predominantly cognitive functions were associated for the posterior one. The differential functional connectivity of the cerebellar anterior and posterior cluster highlights the manifold connections and dichotomy of the human cerebellum, providing additional valuable information about probably disrupted cerebellar-cerebral connections and reflecting the brunt of motor but also the broad spectrum of neuropsychiatric deficits in SCA17." -22806915,PMC4801486,10.1002/hbm.22138,"An investigation of the structural, connectional, and functional subspecialization in the human amygdala","['Bzdok D', 'Laird AR', 'Zilles K', 'Fox PT', 'Eickhoff SB']",2013,12,17,Hum Brain Mapp,34,12,3247-66,"Although the amygdala complex is a brain area critical for human behavior, knowledge of its subspecialization is primarily derived from experiments in animals. We here employed methods for large-scale data mining to perform a connectivity-derived parcellation of the human amygdala based on whole-brain coactivation patterns computed for each seed voxel. Voxels within the histologically defined human amygdala were clustered into distinct groups based on their brain-wide coactivation maps. Using this approach, connectivity-based parcellation divided the amygdala into three distinct clusters that are highly consistent with earlier microstructural distinctions. Meta-analytic connectivity modelling then revealed the derived clusters' brain-wide connectivity patterns, while meta-data profiling allowed their functional characterization. These analyses revealed that the amygdala's laterobasal nuclei group was associated with coordinating high-level sensory input, whereas its centromedial nuclei group was linked to mediating attentional, vegetative, and motor responses. The often-neglected superficial nuclei group emerged as particularly sensitive to olfactory and probably social information processing. The results of this model-free approach support the concordance of structural, connectional, and functional organization in the human amygdala and point to the importance of acknowledging the heterogeneity of this region in neuroimaging research." -22918987,PMC3792742,10.1093/cercor/bhs256,"Is there ""one"" DLPFC in cognitive action control? Evidence for heterogeneity from co-activation-based parcellation","['Cieslik EC', 'Zilles K', 'Caspers S', 'Roski C', 'Kellermann TS', 'Jakobs O', 'Langner R', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2013,11,17,Cereb Cortex,23,11,2677-89,"The dorsolateral prefrontal cortex (DLPFC) has consistently been implicated in cognitive control of motor behavior. There is, however, considerable variability in the exact location and extension of these activations across functional magnetic resonance imaging (fMRI) experiments. This poses the question of whether this variability reflects sampling error and spatial uncertainty in fMRI experiments or structural and functional heterogeneity of this region. This study shows that the right DLPFC as observed in 4 different experiments tapping executive action control may be subdivided into 2 distinct subregions-an anterior-ventral and a posterior-dorsal one -based on their whole-brain co-activation patterns across neuroimaging studies. Investigation of task-dependent and task-independent connectivity revealed both clusters to be involved in distinct neural networks. The posterior subregion showed increased connectivity with bilateral intraparietal sulci, whereas the anterior subregion showed increased connectivity with the anterior cingulate cortex. Functional characterization with quantitative forward and reverse inferences revealed the anterior network to be more strongly associated with attention and action inhibition processes, whereas the posterior network was more strongly related to action execution and working memory. The present data provide evidence that cognitive action control in the right DLPFC may rely on differentiable neural networks and cognitive functions." -22922585,PMC4801478,10.1159/000339528,Consistent neurodegeneration and its association with clinical progression in Huntington's disease: a coordinate-based meta-analysis,"['Dogan I', 'Eickhoff SB', 'Schulz JB', 'Shah NJ', 'Laird AR', 'Fox PT', 'Reetz K']",2013,3,17,Neurodegener Dis,12,1,23-35,"BACKGROUND: The neuropathological hallmark of Huntington's disease (HD) is progressive striatal loss starting several years prior to clinical onset. In the past decade, whole-brain magnetic resonance imaging (MRI) studies have provided accumulating evidence for widely distributed cortical and subcortical atrophy in the early course of the disease. OBJECTIVE: In order to synthesize current morphometric MRI findings and to investigate the impact of clinical and genetic features on structural changes, we performed a coordinate-based meta-analysis of voxel-based morphometry (VBM) studies in HD. METHODS: Twenty HD samples derived from 17 studies were integrated in the analysis comparing a total of 685 HD mutation carriers [345 presymptomatic (pre-HD) and 340 symptomatic (symp-HD) subjects] and 507 controls. Convergent findings across studies were delineated using the anatomical likelihood estimation approach. Effects of genetic and clinical parameters on the likelihood of observing VBM findings were calculated by means of correlation analyses. RESULTS: Pre-HD studies featured convergent evidence for neurodegeneration in the basal ganglia, amygdala, thalamus, insula and occipital regions. In symp-HD, cerebral atrophy was more pronounced and spread to cortical regions (i.e., inferior frontal, premotor, sensorimotor, midcingulate, frontoparietal and temporoparietal cortices). Higher cytosine-adenosine-guanosine repeats were associated with striatal degeneration, while parameters of disease progression and motor impairment additionally correlated with cortical atrophy, especially in sensorimotor areas. CONCLUSION: This first quantitative meta-analysis in HD demonstrates the extent of striatal atrophy and further consistent extrastriatal degeneration before clinical conversion. Sensorimotor areas seem to be core regions affected in symp-HD and, along with widespread cortical atrophy, may account for the clinical heterogeneity in HD." -22936519,PMC3514575,10.1002/hbm.22155,A coordinate-based meta-analytic model of trauma processing in posttraumatic stress disorder,"['Ramage AE', 'Laird AR', 'Eickhoff SB', 'Acheson A', 'Peterson AL', 'Williamson DE', 'Telch MJ', 'Fox PT']",2013,12,17,Hum Brain Mapp,34,12,3392-9,"Posttraumatic stress disorder (PTSD) has a well-defined set of symptoms that can be elicited during traumatic imagery tasks. For this reason, trauma imagery tasks are often employed in functional neuroimaging studies. Here, coordinate-based meta-analysis (CBM) was used to pool eight studies applying traumatic imagery tasks to identify sites of task-induced activation in 170 PTSD patients and 104 healthy controls. In this way, right anterior cingulate (ACC), right posterior cingulate (PCC), and left precuneus (Pcun) were identified as regions uniquely active in PTSD patients relative to healthy controls. To further characterize these regions, their normal interactions, and their typical functional roles, meta-analytic connectivity modeling (MACM) with behavioral filtering was applied. MACM indicated that the PCC and Pcun regions were frequently co-active and associated with processing of cognitive information, particularly in explicit memory tasks. Emotional processing was particularly associated with co-activity of the ACC and PCC, as mediated by the thalamus. By narrowing the regions of interest to those commonly active across multiple studies (using CBM) and developing a priori hypotheses about directed probabilistic dependencies amongst these regions, this proposed model-when applied in the context of graphical and causal modeling-should improve model fit and thereby increase statistical power for detecting differences between subject groups and between treatments in neuroimaging studies of PTSD." -22973224,PMC3428588,10.3389/fninf.2012.00023,Automated regional behavioral analysis for human brain images,"['Lancaster JL', 'Laird AR', 'Eickhoff SB', 'Martinez MJ', 'Fox PM', 'Fox PT']",2012,3,17,Front Neuroinform,6,,23,"Behavioral categories of functional imaging experiments along with standardized brain coordinates of associated activations were used to develop a method to automate regional behavioral analysis of human brain images. Behavioral and coordinate data were taken from the BrainMap database (http://www.brainmap.org/), which documents over 20 years of published functional brain imaging studies. A brain region of interest (ROI) for behavioral analysis can be defined in functional images, anatomical images or brain atlases, if images are spatially normalized to MNI or Talairach standards. Results of behavioral analysis are presented for each of BrainMap's 51 behavioral sub-domains spanning five behavioral domains (Action, Cognition, Emotion, Interoception, and Perception). For each behavioral sub-domain the fraction of coordinates falling within the ROI was computed and compared with the fraction expected if coordinates for the behavior were not clustered, i.e., uniformly distributed. When the difference between these fractions is large behavioral association is indicated. A z-score >/= 3.0 was used to designate statistically significant behavioral association. The left-right symmetry of ~100K activation foci was evaluated by hemisphere, lobe, and by behavioral sub-domain. Results highlighted the classic left-side dominance for language while asymmetry for most sub-domains (~75%) was not statistically significant. Use scenarios were presented for anatomical ROIs from the Harvard-Oxford cortical (HOC) brain atlas, functional ROIs from statistical parametric maps in a TMS-PET study, a task-based fMRI study, and ROIs from the ten ""major representative"" functional networks in a previously published resting state fMRI study. Statistically significant behavioral findings for these use scenarios were consistent with published behaviors for associated anatomical and functional regions." -23042731,PMC3862271,10.1093/cercor/bhs308,Meta-analytic connectivity modeling reveals differential functional connectivity of the medial and lateral orbitofrontal cortex,"['Zald DH', 'McHugo M', 'Ray KL', 'Glahn DC', 'Eickhoff SB', 'Laird AR']",2014,1,17,Cereb Cortex,24,1,232-48,"The orbitofrontal cortex (OFC) is implicated in a broad range of behaviors and neuropsychiatric disorders. Anatomical tracing studies in nonhuman primates reveal differences in connectivity across subregions of the OFC, but data on the connectivity of the human OFC remain limited. We applied meta-analytic connectivity modeling in order to examine which brain regions are most frequently coactivated with the medial and lateral portions of the OFC in published functional neuroimaging studies. The analysis revealed a clear divergence in the pattern of connectivity for the medial OFC (mOFC) and lateral OFC (lOFC) regions. The lOFC showed coactivations with a network of prefrontal regions and areas involved in cognitive functions including language and memory. In contrast, the mOFC showed connectivity with default mode, autonomic, and limbic regions. Convergent patterns of coactivations were observed in the amygdala, hippocampus, striatum, and thalamus. A small number of regions showed connectivity specific to the anterior or posterior sectors of the OFC. Task domains involving memory, semantic processing, face processing, and reward were additionally analyzed in order to identify the different patterns of OFC functional connectivity associated with specific cognitive and affective processes. These data provide a framework for understanding the human OFC's position within widespread functional networks." +22659444,PMC4801477,10.1016/j.neuroimage.2012.05.058,Investigating function and connectivity of morphometric findings--exemplified on cerebellar atrophy in spinocerebellar ataxia 17 (SCA17),"['Reetz K', 'Dogan I', 'Rolfs A', 'Binkofski F', 'Schulz JB', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2012,9,8,Neuroimage,62,3,1354-66,"Spinocerebellar ataxia type 17 (SCA17) is a rare autosomal dominant neurodegenerative disorder characterized by progressive cerebellar ataxia but also a broad spectrum of other neuropsychiatric signs. As anatomical and structural studies have shown severe cerebellar atrophy in SCA17 and a differentiation of the human cerebellum into an anterior sensorimotor and posterior cognitive/emotional partition has been implicated, we aimed at investigating functional connectivity patterns of two cerebellar clusters of atrophy revealed by a morphometric analysis in SCA17 patients. In particular, voxel-based morphometry (VBM) revealed a large cluster of atrophy in SCA17 in the bilateral anterior cerebellum (lobule V) and another one in the left posterior cerebellum (lobules IX, VIIb, VIIIA, VIIIB). These two cerebellar clusters were used as seeds for functional connectivity analyses using task-based meta-analytic connectivity modeling (MACM) and task-free resting state connectivity analysis. Results demonstrated first consistent functional connectivity throughout the cerebellum itself; the anterior cerebellar seed showed stronger connectivity to lobules V, VI and to some extent I-IV, and the posterior cerebellar seed to the posterior lobules VI-IX. Importantly, the cerebellar anterior seed also showed consistently stronger functional connectivity than the posterior one with pre- and motor areas as well as the primary somatosensory cortex. In turn, task-based task-independent functional connectivity analyses revealed that the cerebellar posterior seed was linked with fronto-temporo-parietal areas as well as partly the insula and the thalamus, i.e., brain regions implicated in cognitive and affective processes. Functional characterization of experiments activating either cerebellar seed further corroborated this notion, revealing mainly motor-related functions for the anterior cluster and predominantly cognitive functions were associated for the posterior one. The differential functional connectivity of the cerebellar anterior and posterior cluster highlights the manifold connections and dichotomy of the human cerebellum, providing additional valuable information about probably disrupted cerebellar-cerebral connections and reflecting the brunt of motor but also the broad spectrum of neuropsychiatric deficits in SCA17." +22806915,PMC4801486,10.1002/hbm.22138,"An investigation of the structural, connectional, and functional subspecialization in the human amygdala","['Bzdok D', 'Laird AR', 'Zilles K', 'Fox PT', 'Eickhoff SB']",2013,12,8,Hum Brain Mapp,34,12,3247-66,"Although the amygdala complex is a brain area critical for human behavior, knowledge of its subspecialization is primarily derived from experiments in animals. We here employed methods for large-scale data mining to perform a connectivity-derived parcellation of the human amygdala based on whole-brain coactivation patterns computed for each seed voxel. Voxels within the histologically defined human amygdala were clustered into distinct groups based on their brain-wide coactivation maps. Using this approach, connectivity-based parcellation divided the amygdala into three distinct clusters that are highly consistent with earlier microstructural distinctions. Meta-analytic connectivity modelling then revealed the derived clusters' brain-wide connectivity patterns, while meta-data profiling allowed their functional characterization. These analyses revealed that the amygdala's laterobasal nuclei group was associated with coordinating high-level sensory input, whereas its centromedial nuclei group was linked to mediating attentional, vegetative, and motor responses. The often-neglected superficial nuclei group emerged as particularly sensitive to olfactory and probably social information processing. The results of this model-free approach support the concordance of structural, connectional, and functional organization in the human amygdala and point to the importance of acknowledging the heterogeneity of this region in neuroimaging research." +22918987,PMC3792742,10.1093/cercor/bhs256,"Is there ""one"" DLPFC in cognitive action control? Evidence for heterogeneity from co-activation-based parcellation","['Cieslik EC', 'Zilles K', 'Caspers S', 'Roski C', 'Kellermann TS', 'Jakobs O', 'Langner R', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2013,11,8,Cereb Cortex,23,11,2677-89,"The dorsolateral prefrontal cortex (DLPFC) has consistently been implicated in cognitive control of motor behavior. There is, however, considerable variability in the exact location and extension of these activations across functional magnetic resonance imaging (fMRI) experiments. This poses the question of whether this variability reflects sampling error and spatial uncertainty in fMRI experiments or structural and functional heterogeneity of this region. This study shows that the right DLPFC as observed in 4 different experiments tapping executive action control may be subdivided into 2 distinct subregions-an anterior-ventral and a posterior-dorsal one -based on their whole-brain co-activation patterns across neuroimaging studies. Investigation of task-dependent and task-independent connectivity revealed both clusters to be involved in distinct neural networks. The posterior subregion showed increased connectivity with bilateral intraparietal sulci, whereas the anterior subregion showed increased connectivity with the anterior cingulate cortex. Functional characterization with quantitative forward and reverse inferences revealed the anterior network to be more strongly associated with attention and action inhibition processes, whereas the posterior network was more strongly related to action execution and working memory. The present data provide evidence that cognitive action control in the right DLPFC may rely on differentiable neural networks and cognitive functions." +22922585,PMC4801478,10.1159/000339528,Consistent neurodegeneration and its association with clinical progression in Huntington's disease: a coordinate-based meta-analysis,"['Dogan I', 'Eickhoff SB', 'Schulz JB', 'Shah NJ', 'Laird AR', 'Fox PT', 'Reetz K']",2013,6,8,Neurodegener Dis,12,1,23-35,"BACKGROUND: The neuropathological hallmark of Huntington's disease (HD) is progressive striatal loss starting several years prior to clinical onset. In the past decade, whole-brain magnetic resonance imaging (MRI) studies have provided accumulating evidence for widely distributed cortical and subcortical atrophy in the early course of the disease. OBJECTIVE: In order to synthesize current morphometric MRI findings and to investigate the impact of clinical and genetic features on structural changes, we performed a coordinate-based meta-analysis of voxel-based morphometry (VBM) studies in HD. METHODS: Twenty HD samples derived from 17 studies were integrated in the analysis comparing a total of 685 HD mutation carriers [345 presymptomatic (pre-HD) and 340 symptomatic (symp-HD) subjects] and 507 controls. Convergent findings across studies were delineated using the anatomical likelihood estimation approach. Effects of genetic and clinical parameters on the likelihood of observing VBM findings were calculated by means of correlation analyses. RESULTS: Pre-HD studies featured convergent evidence for neurodegeneration in the basal ganglia, amygdala, thalamus, insula and occipital regions. In symp-HD, cerebral atrophy was more pronounced and spread to cortical regions (i.e., inferior frontal, premotor, sensorimotor, midcingulate, frontoparietal and temporoparietal cortices). Higher cytosine-adenosine-guanosine repeats were associated with striatal degeneration, while parameters of disease progression and motor impairment additionally correlated with cortical atrophy, especially in sensorimotor areas. CONCLUSION: This first quantitative meta-analysis in HD demonstrates the extent of striatal atrophy and further consistent extrastriatal degeneration before clinical conversion. Sensorimotor areas seem to be core regions affected in symp-HD and, along with widespread cortical atrophy, may account for the clinical heterogeneity in HD." +22936519,PMC3514575,10.1002/hbm.22155,A coordinate-based meta-analytic model of trauma processing in posttraumatic stress disorder,"['Ramage AE', 'Laird AR', 'Eickhoff SB', 'Acheson A', 'Peterson AL', 'Williamson DE', 'Telch MJ', 'Fox PT']",2013,12,8,Hum Brain Mapp,34,12,3392-9,"Posttraumatic stress disorder (PTSD) has a well-defined set of symptoms that can be elicited during traumatic imagery tasks. For this reason, trauma imagery tasks are often employed in functional neuroimaging studies. Here, coordinate-based meta-analysis (CBM) was used to pool eight studies applying traumatic imagery tasks to identify sites of task-induced activation in 170 PTSD patients and 104 healthy controls. In this way, right anterior cingulate (ACC), right posterior cingulate (PCC), and left precuneus (Pcun) were identified as regions uniquely active in PTSD patients relative to healthy controls. To further characterize these regions, their normal interactions, and their typical functional roles, meta-analytic connectivity modeling (MACM) with behavioral filtering was applied. MACM indicated that the PCC and Pcun regions were frequently co-active and associated with processing of cognitive information, particularly in explicit memory tasks. Emotional processing was particularly associated with co-activity of the ACC and PCC, as mediated by the thalamus. By narrowing the regions of interest to those commonly active across multiple studies (using CBM) and developing a priori hypotheses about directed probabilistic dependencies amongst these regions, this proposed model-when applied in the context of graphical and causal modeling-should improve model fit and thereby increase statistical power for detecting differences between subject groups and between treatments in neuroimaging studies of PTSD." +22973224,PMC3428588,10.3389/fninf.2012.00023,Automated regional behavioral analysis for human brain images,"['Lancaster JL', 'Laird AR', 'Eickhoff SB', 'Martinez MJ', 'Fox PM', 'Fox PT']",2012,6,8,Front Neuroinform,6,,23,"Behavioral categories of functional imaging experiments along with standardized brain coordinates of associated activations were used to develop a method to automate regional behavioral analysis of human brain images. Behavioral and coordinate data were taken from the BrainMap database (http://www.brainmap.org/), which documents over 20 years of published functional brain imaging studies. A brain region of interest (ROI) for behavioral analysis can be defined in functional images, anatomical images or brain atlases, if images are spatially normalized to MNI or Talairach standards. Results of behavioral analysis are presented for each of BrainMap's 51 behavioral sub-domains spanning five behavioral domains (Action, Cognition, Emotion, Interoception, and Perception). For each behavioral sub-domain the fraction of coordinates falling within the ROI was computed and compared with the fraction expected if coordinates for the behavior were not clustered, i.e., uniformly distributed. When the difference between these fractions is large behavioral association is indicated. A z-score >/= 3.0 was used to designate statistically significant behavioral association. The left-right symmetry of ~100K activation foci was evaluated by hemisphere, lobe, and by behavioral sub-domain. Results highlighted the classic left-side dominance for language while asymmetry for most sub-domains (~75%) was not statistically significant. Use scenarios were presented for anatomical ROIs from the Harvard-Oxford cortical (HOC) brain atlas, functional ROIs from statistical parametric maps in a TMS-PET study, a task-based fMRI study, and ROIs from the ten ""major representative"" functional networks in a previously published resting state fMRI study. Statistically significant behavioral findings for these use scenarios were consistent with published behaviors for associated anatomical and functional regions." +23042731,PMC3862271,10.1093/cercor/bhs308,Meta-analytic connectivity modeling reveals differential functional connectivity of the medial and lateral orbitofrontal cortex,"['Zald DH', 'McHugo M', 'Ray KL', 'Glahn DC', 'Eickhoff SB', 'Laird AR']",2014,1,8,Cereb Cortex,24,1,232-48,"The orbitofrontal cortex (OFC) is implicated in a broad range of behaviors and neuropsychiatric disorders. Anatomical tracing studies in nonhuman primates reveal differences in connectivity across subregions of the OFC, but data on the connectivity of the human OFC remain limited. We applied meta-analytic connectivity modeling in order to examine which brain regions are most frequently coactivated with the medial and lateral portions of the OFC in published functional neuroimaging studies. The analysis revealed a clear divergence in the pattern of connectivity for the medial OFC (mOFC) and lateral OFC (lOFC) regions. The lOFC showed coactivations with a network of prefrontal regions and areas involved in cognitive functions including language and memory. In contrast, the mOFC showed connectivity with default mode, autonomic, and limbic regions. Convergent patterns of coactivations were observed in the amygdala, hippocampus, striatum, and thalamus. A small number of regions showed connectivity specific to the anterior or posterior sectors of the OFC. Task domains involving memory, semantic processing, face processing, and reward were additionally analyzed in order to identify the different patterns of OFC functional connectivity associated with specific cognitive and affective processes. These data provide a framework for understanding the human OFC's position within widespread functional networks." 23110878,PMC3636184,10.1016/j.neuroimage.2012.10.043,Individual differences in amygdala reactivity following nicotinic receptor stimulation in abstinent smokers,"['Sutherland MT', 'Carroll AJ', 'Salmeron BJ', 'Ross TJ', 'Hong LE', 'Stein EA']",2013,2,1,Neuroimage,66,,585-93,"Hyperactive amygdala functioning may underlie emotional dysregulation during smoking abstinence and represents one neurobiological target for pharmacological cessation aids. Available pharmacotherapies (e.g., nicotine replacement and varenicline) aid only a subset of individuals with smoking cessation and therefore elucidating the neurobiological impact of these medications is critical to expedite improved interventions. In a fMRI study employing a within-subject, double-blind, placebo-controlled design, we assessed task performance and amygdala functioning during an emotional face matching paradigm following administration of nicotine and varenicline to 24 abstinent smokers and 20 nonsmokers. All participants underwent ~17days of varenicline and placebo pill administration and were scanned, on different days under each condition, wearing a transdermal nicotine or placebo patch. During the amygdala reactivity paradigm, nicotinic acetylcholine receptor (nAChR) stimulation by nicotine and varenicline decreased reaction time (RT) in abstinent smokers but not in nonsmokers. When considering all smokers as a single homogenous group, no drug-induced effects on amygdala reactivity were detected. However, in an exploratory analysis we parsed participants into subgroups according to individual differences in the propensity to demonstrate stable performance augmentation following nAChR stimulation (stable RT-improvers [SI] vs. variable RT-improvers [VI]). Using this exploratory approach, drugs appeared to modulate amygdala reactivity in only one smoker subgroup but not in either nonsmoker subgroup. Specifically, in the SI-smoker cohort abstinence-induced elevated amygdala reactivity was down-regulated by nAChR stimulation. In contrast, varenicline and nicotine did not modulate amygdala functioning in the VI-smoker cohort who displayed moderate levels of amygdala reactivity in the absence of drug administration. These results suggest that pharmacotherapies most robustly dampened amygdala functioning in smokers appearing susceptible to abstinence-induced effects. Such findings provide a step towards fractionating the smoker phenotype by discrete neurobiological characteristics." -23143344,PMC3825581,10.1007/s00429-012-0476-4,"Differentiated parietal connectivity of frontal regions for ""what"" and ""where"" memory","['Rottschy C', 'Caspers S', 'Roski C', 'Reetz K', 'Dogan I', 'Schulz JB', 'Zilles K', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2013,11,17,Brain Struct Funct,218,6,1551-67,"In a previous meta-analysis across almost 200 neuroimaging experiments, working memory for object location showed significantly stronger convergence on the posterior superior frontal gyrus, whereas working memory for identity showed stronger convergence on the posterior inferior frontal gyrus (dorsal to, but overlapping with Brodmann's area BA 44). As similar locations have been discussed as part of a dorsal frontal-superior parietal reach system and an inferior frontal grasp system, the aim of the present study was to test whether the regions of working-memory related ""what"" and ""where"" processing show a similar distinction in parietal connectivity. The regions that were found in the previous meta-analysis were used as seeds for functional connectivity analyses using task-based meta-analytic connectivity modelling and task-independent resting state correlations. While the ventral seed showed significantly stronger connectivity with the bilateral intraparietal sulcus (IPS), the dorsal seed showed stronger connectivity with the bilateral posterior inferior parietal and the medial superior parietal lobule. The observed connections of regions involved in memory for object location and identity thus clearly demonstrate a distinction into separate pathways that resemble the parietal connectivity patterns of the dorsal and ventral premotor cortex in non-human primates and humans. It may hence be speculated that memory for a particular location and reaching towards it as well as object memory and finger positioning for manipulation may rely on shared neural systems. Moreover, the ensuing regions, in turn, featured differential connectivity with the bilateral ventral and dorsal extrastriate cortex, suggesting largely segregated bilateral connectivity pathways from the dorsal visual cortex via the superior and inferior parietal lobules to the dorsal posterior frontal cortex and from the ventral visual cortex via the IPS to the ventral posterior frontal cortex that may underlie action and cognition." +23143344,PMC3825581,10.1007/s00429-012-0476-4,"Differentiated parietal connectivity of frontal regions for ""what"" and ""where"" memory","['Rottschy C', 'Caspers S', 'Roski C', 'Reetz K', 'Dogan I', 'Schulz JB', 'Zilles K', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2013,11,8,Brain Struct Funct,218,6,1551-67,"In a previous meta-analysis across almost 200 neuroimaging experiments, working memory for object location showed significantly stronger convergence on the posterior superior frontal gyrus, whereas working memory for identity showed stronger convergence on the posterior inferior frontal gyrus (dorsal to, but overlapping with Brodmann's area BA 44). As similar locations have been discussed as part of a dorsal frontal-superior parietal reach system and an inferior frontal grasp system, the aim of the present study was to test whether the regions of working-memory related ""what"" and ""where"" processing show a similar distinction in parietal connectivity. The regions that were found in the previous meta-analysis were used as seeds for functional connectivity analyses using task-based meta-analytic connectivity modelling and task-independent resting state correlations. While the ventral seed showed significantly stronger connectivity with the bilateral intraparietal sulcus (IPS), the dorsal seed showed stronger connectivity with the bilateral posterior inferior parietal and the medial superior parietal lobule. The observed connections of regions involved in memory for object location and identity thus clearly demonstrate a distinction into separate pathways that resemble the parietal connectivity patterns of the dorsal and ventral premotor cortex in non-human primates and humans. It may hence be speculated that memory for a particular location and reaching towards it as well as object memory and finger positioning for manipulation may rely on shared neural systems. Moreover, the ensuing regions, in turn, featured differential connectivity with the bilateral ventral and dorsal extrastriate cortex, suggesting largely segregated bilateral connectivity pathways from the dorsal visual cortex via the superior and inferior parietal lobules to the dorsal posterior frontal cortex and from the ventral visual cortex via the IPS to the ventral posterior frontal cortex that may underlie action and cognition." 23370055,PMC4791061,10.1016/j.neuroimage.2013.01.046,Task- and resting-state functional connectivity of brain regions related to affection and susceptible to concurrent cognitive demand,"['Kellermann TS', 'Caspers S', 'Fox PT', 'Zilles K', 'Roski C', 'Laird AR', 'Turetsky BI', 'Eickhoff SB']",2013,5,15,Neuroimage,72,,69-82,"A recent fMRI-study revealed neural responses for affective processing of stimuli for which overt attention irrespective of stimulus valence was required in the orbitofrontal cortex (OFC) and bilateral amygdala (AMY): activation decreased with increasing cognitive demand. To further characterize the network putatively related to this attenuation, we here characterized these regions with respect to their functional properties and connectivity patterns in task-dependent and task-independent states. All experiments of the BrainMap database activating the seed regions OFC and bilateral AMY were identified. Their functional characteristics were quantitatively inferred using the behavioral meta-data of the retrieved experiments. Task-dependent functional connectivity was characterized by meta-analytic connectivity modeling (MACM) of significant co-activations with these seed regions. Task-independent resting-state functional connectivity analysis in a sample of 100 healthy subjects complemented these analyses. All three seed regions co-activated with subgenual cingulum (SGC), precuneus (PCu) and nucleus accumbens (NAcc) in the task-dependent MACM analysis. Task-independent resting-state connectivity revealed significant coupling of the seeds only with the SGC, but not the PCu and the NAcc. The former region (SGC) moreover was shown to feature significant resting-state connectivity with all other regions implicated in the network connected to regions where emotional processing may be modulated by a cognitive distractor. Based on its functional profile and connectivity pattern, we suggest that the SGC might serve as a key hub in the identified network, as such linking autobiographic information [PCu], reward [NAcc], (reinforce) values [OFC] and emotional significance [AMY]. Such a role, in turn, may allow the SGC to influence the OFC and AMY to modulate affective processing." -23452684,PMC5441228,10.1016/j.jaac.2012.12.012,Developmental meta-analysis of the functional neural correlates of autism spectrum disorders,"['Dickstein DP', 'Pescosolido MF', 'Reidy BL', 'Galvan T', 'Kim KL', 'Seymour KE', 'Laird AR', 'Di Martino A', 'Barrett RP']",2013,3,17,J Am Acad Child Adolesc Psychiatry,52,3,279-289.e16,"OBJECTIVE: There is a pressing need to elucidate the brain-behavior interactions underlying autism spectrum disorders (ASD) given the marked rise in ASD diagnosis over the past decade. Functional magnetic resonance imaging (fMRI) has begun to address this need, but few fMRI studies have evaluated age-related changes in ASD. Therefore, we conducted a developmental analysis of activation likelihood estimation (ALE) meta-analysis to compare child versus adult ASD fMRI studies. We hypothesized that children and adolescents with ASD (<18 years old) would rely less on prefrontal cortex structures than adults (>/=18 years old). METHOD: PubMed and PsycInfo literature searches were conducted to identify task-dependent fMRI studies of children or adults with ASD. Then recent GingerALE software improvements were leveraged to perform direct comparisons of child (n = 18) versus adult (n = 24) studies. RESULTS: ALE meta-analyses of social tasks showed that children and adolescents with ASD versus adults had significantly greater hyperactivation in the left post-central gyrus, and greater hypoactivation in the right hippocampus and right superior temporal gyrus. ALE meta-analyses of nonsocial tasks showed that children with ASD versus adults had significantly greater hyperactivation in the right insula and left cingulate gyrus, and hypoactivation in the right middle frontal gyrus. CONCLUSION: Our data suggest that the neural alterations associated with ASD are not static, occurring only in early childhood. Instead, children with ASD have altered neural activity compared to adults during both social and nonsocial tasks, especially in fronto-temporal structures. Longitudinal neuroimaging studies are required to examine these changes prospectively, as potential targets for brain-based treatments for ASD." -23455594,PMC3873099,10.1007/s00213-013-3018-8,Insula's functional connectivity with ventromedial prefrontal cortex mediates the impact of trait alexithymia on state tobacco craving,"['Sutherland MT', 'Carroll AJ', 'Salmeron BJ', 'Ross TJ', 'Stein EA']",2013,7,17,Psychopharmacology (Berl),228,1,143-55,"RATIONALE: Alexithymia is a personality trait characterized by difficulty indentifying and describing subjective emotional experiences. Decreased aptitude in the perception, evaluation, and communication of affectively laden mental states has been associated with reduced emotion regulation, more severe drug craving in addicts, and structural/functional alterations in insula and anterior cingulate cortex (ACC). The insula and ACC represent sites of convergence between the putative neural substrates of alexithymia and those perpetuating cigarette smoking. OBJECTIVES: We examined the interrelations between alexithymia, tobacco craving, and insula/ACC neurocircuitry using resting-state functional connectivity (rsFC). METHODS: Overnight-deprived smokers (n = 24) and nonsmokers (n = 20) completed six neuroimaging assessments on different days both in the absence of, and following, varenicline and/or nicotine administration. In this secondary analysis of data from a larger study, we assessed trait alexithymia and state tobacco craving using self-reports and examined the rsFC of bilateral insular subregions (anterior, middle, posterior) and dorsal ACC. RESULTS: Higher alexithymia in smokers predicted reduced rsFC strength between the right anterior insula (aI) and ventromedial prefrontal cortex (vmPFC). Higher alexithymia also predicted more severe tobacco craving during nicotine withdrawal. Critically, the identified aI-vmPFC circuit fully mediated this alexithymia-craving relation. That is, elevated alexithymia predicted decreased aI-vmPFC rsFC and, in turn, decreased aI-vmPFC rsFC predicted increased craving during withdrawal. A moderated mediation analysis indicated that this aI-vmPFC mediational effect was not observed following drug administration. CONCLUSIONS: These results suggest that a weakened right aI-vmPFC functional circuit confers increased liability for tobacco craving during smoking abstinence. Individual differences in alexithymia and/or aI-vmPFC functional coupling may be relevant factors for smoking cessation success." +23452684,PMC5441228,10.1016/j.jaac.2012.12.012,Developmental meta-analysis of the functional neural correlates of autism spectrum disorders,"['Dickstein DP', 'Pescosolido MF', 'Reidy BL', 'Galvan T', 'Kim KL', 'Seymour KE', 'Laird AR', 'Di Martino A', 'Barrett RP']",2013,3,8,J Am Acad Child Adolesc Psychiatry,52,3,279-289.e16,"OBJECTIVE: There is a pressing need to elucidate the brain-behavior interactions underlying autism spectrum disorders (ASD) given the marked rise in ASD diagnosis over the past decade. Functional magnetic resonance imaging (fMRI) has begun to address this need, but few fMRI studies have evaluated age-related changes in ASD. Therefore, we conducted a developmental analysis of activation likelihood estimation (ALE) meta-analysis to compare child versus adult ASD fMRI studies. We hypothesized that children and adolescents with ASD (<18 years old) would rely less on prefrontal cortex structures than adults (>/=18 years old). METHOD: PubMed and PsycInfo literature searches were conducted to identify task-dependent fMRI studies of children or adults with ASD. Then recent GingerALE software improvements were leveraged to perform direct comparisons of child (n = 18) versus adult (n = 24) studies. RESULTS: ALE meta-analyses of social tasks showed that children and adolescents with ASD versus adults had significantly greater hyperactivation in the left post-central gyrus, and greater hypoactivation in the right hippocampus and right superior temporal gyrus. ALE meta-analyses of nonsocial tasks showed that children with ASD versus adults had significantly greater hyperactivation in the right insula and left cingulate gyrus, and hypoactivation in the right middle frontal gyrus. CONCLUSION: Our data suggest that the neural alterations associated with ASD are not static, occurring only in early childhood. Instead, children with ASD have altered neural activity compared to adults during both social and nonsocial tasks, especially in fronto-temporal structures. Longitudinal neuroimaging studies are required to examine these changes prospectively, as potential targets for brain-based treatments for ASD." +23455594,PMC3873099,10.1007/s00213-013-3018-8,Insula's functional connectivity with ventromedial prefrontal cortex mediates the impact of trait alexithymia on state tobacco craving,"['Sutherland MT', 'Carroll AJ', 'Salmeron BJ', 'Ross TJ', 'Stein EA']",2013,7,8,Psychopharmacology (Berl),228,1,143-55,"RATIONALE: Alexithymia is a personality trait characterized by difficulty indentifying and describing subjective emotional experiences. Decreased aptitude in the perception, evaluation, and communication of affectively laden mental states has been associated with reduced emotion regulation, more severe drug craving in addicts, and structural/functional alterations in insula and anterior cingulate cortex (ACC). The insula and ACC represent sites of convergence between the putative neural substrates of alexithymia and those perpetuating cigarette smoking. OBJECTIVES: We examined the interrelations between alexithymia, tobacco craving, and insula/ACC neurocircuitry using resting-state functional connectivity (rsFC). METHODS: Overnight-deprived smokers (n = 24) and nonsmokers (n = 20) completed six neuroimaging assessments on different days both in the absence of, and following, varenicline and/or nicotine administration. In this secondary analysis of data from a larger study, we assessed trait alexithymia and state tobacco craving using self-reports and examined the rsFC of bilateral insular subregions (anterior, middle, posterior) and dorsal ACC. RESULTS: Higher alexithymia in smokers predicted reduced rsFC strength between the right anterior insula (aI) and ventromedial prefrontal cortex (vmPFC). Higher alexithymia also predicted more severe tobacco craving during nicotine withdrawal. Critically, the identified aI-vmPFC circuit fully mediated this alexithymia-craving relation. That is, elevated alexithymia predicted decreased aI-vmPFC rsFC and, in turn, decreased aI-vmPFC rsFC predicted increased craving during withdrawal. A moderated mediation analysis indicated that this aI-vmPFC mediational effect was not observed following drug administration. CONCLUSIONS: These results suggest that a weakened right aI-vmPFC functional circuit confers increased liability for tobacco craving during smoking abstinence. Individual differences in alexithymia and/or aI-vmPFC functional coupling may be relevant factors for smoking cessation success." 23506999,PMC3775982,10.1016/j.biopsych.2013.01.035,Down-regulation of amygdala and insula functional circuits by varenicline and nicotine in abstinent cigarette smokers,"['Sutherland MT', 'Carroll AJ', 'Salmeron BJ', 'Ross TJ', 'Hong LE', 'Stein EA']",2013,10,1,Biol Psychiatry,74,7,538-46,"BACKGROUND: Although the amygdala and insula are regarded as critical neural substrates perpetuating cigarette smoking, little is known about their circuit-level interactions with interconnected regions during nicotine withdrawal or following pharmacotherapy administration. To elucidate neurocircuitry associated with early smoking abstinence, we examined the impact of varenicline and nicotine, two modestly efficacious pharmacologic cessation aids, on amygdala- and insula-centered circuits using resting-state functional connectivity (rsFC). METHODS: In a functional magnetic resonance imaging study employing a two-drug, placebo-controlled design, 24 overnight-abstinent smokers and 20 nonsmokers underwent approximately 17 days of varenicline and placebo pill administration and were scanned, on different days under each condition, wearing a transdermal nicotine or placebo patch. We examined the impact of varenicline and nicotine (both alone and in combination) on amygdala- and insula-centered rsFC using seed-based assessments. RESULTS: Beginning with a functionally defined amygdala seed, we observed that rsFC strength in an amygdala-insula circuit was down-regulated by varenicline and nicotine in abstinent smokers. Using this identified insula region as a new seed, both drugs similarly decreased rsFC between the insula and constituents of the canonical default-mode network (posterior cingulate cortex, ventromedial/dorsomedial prefrontal cortex, parahippocampus). Drug-induced rsFC modulations were critically linked with nicotine withdrawal, as similar effects were not detected in nonsmokers. CONCLUSIONS: These results suggest that nicotine withdrawal is associated with elevated amygdala-insula and insula-default-mode network interactions. As these potentiated interactions were down-regulated by two pharmacotherapies, this effect may be a characteristic shared by pharmacologic agents promoting smoking cessation. Decreased rsFC in these circuits may contribute to amelioration of subjective withdrawal symptoms." 23631994,PMC3720689,10.1016/j.neuroimage.2013.04.073,Networks of task co-activations,"['Laird AR', 'Eickhoff SB', 'Rottschy C', 'Bzdok D', 'Ray KL', 'Fox PT']",2013,10,15,Neuroimage,80,,505-14,"Recent progress in neuroimaging informatics and meta-analytic techniques has enabled a novel domain of human brain connectomics research that focuses on task-dependent co-activation patterns across behavioral tasks and cognitive domains. Here, we review studies utilizing the BrainMap database to investigate data trends in the activation literature using methods such as meta-analytic connectivity modeling (MACM), connectivity-based parcellation (CPB), and independent component analysis (ICA). We give examples of how these methods are being applied to learn more about the functional connectivity of areas such as the amygdala, the default mode network, and visual area V5. Methods for analyzing the behavioral metadata corresponding to regions of interest and to their intrinsically connected networks are described as a tool for local functional decoding. We finally discuss the relation of observed co-activation connectivity results to resting state connectivity patterns, and provide implications for future work in this domain." -23674246,PMC4981637,10.1002/hbm.22262,The functional neuroanatomy of male psychosexual and physiosexual arousal: a quantitative meta-analysis,"['Poeppl TB', 'Langguth B', 'Laird AR', 'Eickhoff SB']",2014,4,17,Hum Brain Mapp,35,4,1404-21,"Reproductive behavior is mandatory for conservation of species and mediated by a state of sexual arousal (SA), involving both complex mental processes and bodily reactions. An early neurobehavioral model of SA proposes cognitive, emotional, motivational, and autonomic components. In a comprehensive quantitative meta-analysis on previous neuroimaging findings, we provide here evidence for distinct brain networks underlying psychosexual and physiosexual arousal. Psychosexual (i.e., mental sexual) arousal recruits brain areas crucial for cognitive evaluation, top-down modulation of attention and exteroceptive sensory processing, relevance detection and affective evaluation, as well as regions implicated in the representation of urges and in triggering autonomic processes. In contrast, physiosexual (i.e., physiological sexual) arousal is mediated by regions responsible for regulation and monitoring of initiated autonomic processes and emotions and for somatosensory processing. These circuits are interconnected by subcortical structures (putamen and claustrum) that provide exchange of sensorimotor information and crossmodal processing between and within the networks. Brain deactivations may imply attenuation of introspective processes and social cognition, but be necessary to release intrinsic inhibition of SA." -23685185,PMC4827858,10.1016/j.jpain.2013.03.001,Structural brain anomalies and chronic pain: a quantitative meta-analysis of gray matter volume,"['Smallwood RF', 'Laird AR', 'Ramage AE', 'Parkinson AL', 'Lewis J', 'Clauw DJ', 'Williams DA', 'Schmidt-Wilcke T', 'Farrell MJ', 'Eickhoff SB', 'Robin DA']",2013,7,17,J Pain,14,7,663-75,"UNLABELLED: The diversity of chronic pain syndromes and the methods employed to study them make integrating experimental findings challenging. This study performed coordinate-based meta-analyses using voxel-based morphometry imaging results to examine gray matter volume (GMV) differences between chronic pain patients and healthy controls. There were 12 clusters where GMV was decreased in patients compared with controls, including many regions thought to be part of the ""pain matrix"" of regions involved in pain perception, but also including many other regions that are not commonly regarded as pain-processing areas. The right hippocampus and parahippocampal gyrus were the only regions noted to have increased GMV in patients. Functional characterizations were implemented using the BrainMap database to determine which behavioral domains were significantly represented in these regions. The most common behavioral domains associated with these regions were cognitive, affective, and perceptual domains. Because many of these regions are not classically connected with pain and because there was such significance in functionality outside of perception, it is proposed that many of these regions are related to the constellation of comorbidities of chronic pain, such as fatigue and cognitive and emotional impairments. Further research into the mechanisms of GMV changes could provide a perspective on these findings. PERSPECTIVE: Quantitative meta-analyses revealed structural differences between brains of individuals with chronic pain and healthy controls. These differences may be related to comorbidities of chronic pain." +23674246,PMC4981637,10.1002/hbm.22262,The functional neuroanatomy of male psychosexual and physiosexual arousal: a quantitative meta-analysis,"['Poeppl TB', 'Langguth B', 'Laird AR', 'Eickhoff SB']",2014,4,8,Hum Brain Mapp,35,4,1404-21,"Reproductive behavior is mandatory for conservation of species and mediated by a state of sexual arousal (SA), involving both complex mental processes and bodily reactions. An early neurobehavioral model of SA proposes cognitive, emotional, motivational, and autonomic components. In a comprehensive quantitative meta-analysis on previous neuroimaging findings, we provide here evidence for distinct brain networks underlying psychosexual and physiosexual arousal. Psychosexual (i.e., mental sexual) arousal recruits brain areas crucial for cognitive evaluation, top-down modulation of attention and exteroceptive sensory processing, relevance detection and affective evaluation, as well as regions implicated in the representation of urges and in triggering autonomic processes. In contrast, physiosexual (i.e., physiological sexual) arousal is mediated by regions responsible for regulation and monitoring of initiated autonomic processes and emotions and for somatosensory processing. These circuits are interconnected by subcortical structures (putamen and claustrum) that provide exchange of sensorimotor information and crossmodal processing between and within the networks. Brain deactivations may imply attenuation of introspective processes and social cognition, but be necessary to release intrinsic inhibition of SA." +23685185,PMC4827858,10.1016/j.jpain.2013.03.001,Structural brain anomalies and chronic pain: a quantitative meta-analysis of gray matter volume,"['Smallwood RF', 'Laird AR', 'Ramage AE', 'Parkinson AL', 'Lewis J', 'Clauw DJ', 'Williams DA', 'Schmidt-Wilcke T', 'Farrell MJ', 'Eickhoff SB', 'Robin DA']",2013,7,8,J Pain,14,7,663-75,"UNLABELLED: The diversity of chronic pain syndromes and the methods employed to study them make integrating experimental findings challenging. This study performed coordinate-based meta-analyses using voxel-based morphometry imaging results to examine gray matter volume (GMV) differences between chronic pain patients and healthy controls. There were 12 clusters where GMV was decreased in patients compared with controls, including many regions thought to be part of the ""pain matrix"" of regions involved in pain perception, but also including many other regions that are not commonly regarded as pain-processing areas. The right hippocampus and parahippocampal gyrus were the only regions noted to have increased GMV in patients. Functional characterizations were implemented using the BrainMap database to determine which behavioral domains were significantly represented in these regions. The most common behavioral domains associated with these regions were cognitive, affective, and perceptual domains. Because many of these regions are not classically connected with pain and because there was such significance in functionality outside of perception, it is proposed that many of these regions are related to the constellation of comorbidities of chronic pain, such as fatigue and cognitive and emotional impairments. Further research into the mechanisms of GMV changes could provide a perspective on these findings. PERSPECTIVE: Quantitative meta-analyses revealed structural differences between brains of individuals with chronic pain and healthy controls. These differences may be related to comorbidities of chronic pain." 23689016,PMC4791053,10.1016/j.neuroimage.2013.05.046,"Characterization of the temporo-parietal junction by combining data-driven parcellation, complementary connectivity analyses, and functional decoding","['Bzdok D', 'Langner R', 'Schilbach L', 'Jakobs O', 'Roski C', 'Caspers S', 'Laird AR', 'Fox PT', 'Zilles K', 'Eickhoff SB']",2013,11,1,Neuroimage,81,,381-392,"The right temporo-parietal junction (RTPJ) is consistently implicated in two cognitive domains, attention and social cognitions. We conducted multi-modal connectivity-based parcellation to investigate potentially separate functional modules within RTPJ implementing this cognitive dualism. Both task-constrained meta-analytic coactivation mapping and task-free resting-state connectivity analysis independently identified two distinct clusters within RTPJ, subsequently characterized by network mapping and functional forward/reverse inference. Coactivation mapping and resting-state correlations revealed that the anterior cluster increased neural activity concomitantly with a midcingulate-motor-insular network, functionally associated with attention, and decreased neural activity concomitantly with a parietal network, functionally associated with social cognition and memory retrieval. The posterior cluster showed the exact opposite association pattern. Our data thus suggest that RTPJ links two antagonistic brain networks processing external versus internal information." -23702412,PMC5325035,10.1016/j.neuroimage.2013.05.052,"Cytoarchitecture, probability maps and functions of the human frontal pole","['Bludau S', 'Eickhoff SB', 'Mohlberg H', 'Caspers S', 'Laird AR', 'Fox PT', 'Schleicher A', 'Zilles K', 'Amunts K']",2014,6,17,Neuroimage,93 Pt 2,,260-75,"The frontal pole has more expanded than any other part in the human brain as compared to our ancestors. It plays an important role for specifically human behavior and cognitive abilities, e.g. action selection (Kovach et al., 2012). Evidence about divergent functions of its medial and lateral part has been provided, both in the healthy brain and in psychiatric disorders. The anatomical correlates of such functional segregation, however, are still unknown due to a lack of stereotaxic, microstructural maps obtained in a representative sample of brains. Here we show that the human frontopolar cortex consists of two cytoarchitectonically and functionally distinct areas: lateral frontopolar area 1 (Fp1) and medial frontopolar area 2 (Fp2). Based on observer-independent mapping in serial, cell-body stained sections of 10 brains, three-dimensional, probabilistic maps of areas Fp1 and Fp2 were created. They show, for each position of the reference space, the probability with which each area was found in a particular voxel. Applying these maps as seed regions for a meta-analysis revealed that Fp1 and Fp2 differentially contribute to functional networks: Fp1 was involved in cognition, working memory and perception, whereas Fp2 was part of brain networks underlying affective processing and social cognition. The present study thus disclosed cortical correlates of a functional segregation of the human frontopolar cortex. The probabilistic maps provide a sound anatomical basis for interpreting neuroimaging data in the living human brain, and open new perspectives for analyzing structure-function relationships in the prefrontal cortex. The new data will also serve as a starting point for further comparative studies between human and non-human primate brains. This allows finding similarities and differences in the organizational principles of the frontal lobe during evolution as neurobiological basis for our behavior and cognitive abilities." -23755001,PMC3665907,10.3389/fnhum.2013.00232,Segregation of the human medial prefrontal cortex in social cognition,"['Bzdok D', 'Langner R', 'Schilbach L', 'Engemann DA', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2013,3,17,Front Hum Neurosci,7,,232,"While the human medial prefrontal cortex (mPFC) is widely believed to be a key node of neural networks relevant for socio-emotional processing, its functional subspecialization is still poorly understood. We thus revisited the often assumed differentiation of the mPFC in social cognition along its ventral-dorsal axis. Our neuroinformatic analysis was based on a neuroimaging meta-analysis of perspective-taking that yielded two separate clusters in the ventral and dorsal mPFC, respectively. We determined each seed region's brain-wide interaction pattern by two complementary measures of functional connectivity: co-activation across a wide range of neuroimaging studies archived in the BrainMap database and correlated signal fluctuations during unconstrained (""resting"") cognition. Furthermore, we characterized the functions associated with these two regions using the BrainMap database. Across methods, the ventral mPFC was more strongly connected with the nucleus accumbens, hippocampus, posterior cingulate cortex, and retrosplenial cortex, while the dorsal mPFC was more strongly connected with the inferior frontal gyrus, temporo-parietal junction, and middle temporal gyrus. Further, the ventral mPFC was selectively associated with reward related tasks, while the dorsal mPFC was selectively associated with perspective-taking and episodic memory retrieval. The ventral mPFC is therefore predominantly involved in bottom-up-driven, approach/avoidance-modulating, and evaluation-related processing, whereas the dorsal mPFC is predominantly involved in top-down-driven, probabilistic-scene-informed, and metacognition-related processing in social cognition." -23781190,PMC3679482,10.3389/fnhum.2013.00268,Dysregulated left inferior parietal activity in schizophrenia and depression: functional connectivity and characterization,"['Muller VI', 'Cieslik EC', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2013,3,17,Front Hum Neurosci,7,,268,"The inferior parietal cortex (IPC) is a heterogeneous region that is known to be involved in a multitude of diverse different tasks and processes, though its contribution to these often-complex functions is yet poorly understood. In a previous study we demonstrated that patients with depression failed to deactivate the left IPC during processing of congruent audiovisual information. We now found the same dysregulation (same region and condition) in schizophrenia. By using task-independent (resting state) and task-dependent meta-analytic connectivity modeling (MACM) analyses we aimed at characterizing this particular region with regard to its connectivity and function. Across both approaches, results revealed functional connectivity of the left inferior parietal seed region with bilateral IPC, precuneus and posterior cingulate cortex (PrC/PCC), medial orbitofrontal cortex (mOFC), left middle frontal (MFG) as well as inferior frontal (IFG) gyrus. Network-level functional characterization further revealed that on the one hand, all interconnected regions are part of a network involved in memory processes. On the other hand, sub-networks are formed when emotion, language, social cognition and reasoning processes are required. Thus, the IPC-region that is dysregulated in both depression and schizophrenia is functionally connected to a network of regions which, depending on task demands may form sub-networks. These results therefore indicate that dysregulation of left IPC in depression and schizophrenia might not only be connected to deficits in audiovisual integration, but is possibly also associated to impaired memory and deficits in emotion processing in these patient groups." -23791915,PMC4791055,10.1016/j.neuroimage.2013.06.041,Tackling the multifunctional nature of Broca's region meta-analytically: co-activation-based parcellation of area 44,"['Clos M', 'Amunts K', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2013,12,17,Neuroimage,83,,174-88,"Cytoarchitectonic area 44 of Broca's region in the left inferior frontal gyrus is known to be involved in several functional domains including language, action and music processing. We investigated whether this functional heterogeneity is reflected in distinct modules within cytoarchitectonically defined left area 44 using meta-analytic connectivity-based parcellation (CBP). This method relies on identifying the whole-brain co-activation pattern for each area 44 voxel across a wide range of functional neuroimaging experiments and subsequently grouping the voxels into distinct clusters based on the similarity of their co-activation patterns. This CBP analysis revealed that five separate clusters exist within left area 44. A post-hoc functional characterization and functional connectivity analysis of these five clusters was then performed. The two posterior clusters were primarily associated with action processes, in particular with phonology and overt speech (posterior-dorsal cluster) and with rhythmic sequencing (posterior-ventral cluster). The three anterior clusters were primarily associated with language and cognition, in particular with working memory (anterior-dorsal cluster), with detection of meaning (anterior-ventral cluster) and with task switching/cognitive control (inferior frontal junction cluster). These five clusters furthermore showed specific and distinct connectivity patterns. The results demonstrate that left area 44 is heterogeneous, thus supporting anatomical data on the molecular architecture of this region, and provide a basis for more specific interpretations of activations localized in area 44." -23928747,PMC4219928,10.1007/s00429-013-0620-9,Multi-region hemispheric specialization differentiates human from nonhuman primate brain function,"['Wey HY', 'Phillips KA', 'McKay DR', 'Laird AR', 'Kochunov P', 'Davis MD', 'Glahn DC', 'Blangero J', 'Duong TQ', 'Fox PT']",2014,11,17,Brain Struct Funct,219,6,2187-94,"The human behavioral repertoire greatly exceeds that of nonhuman primates. Anatomical specializations of the human brain include an enlarged neocortex and prefrontal cortex (Semendeferi et al. in Am J Phys Anthropol 114:224-241, 2001), but regional enlargements alone cannot account for these vast functional differences. Hemispheric specialization has long believed to be a major contributing factor to such distinctive human characteristics as motor dominance, attentional control and language. Yet structural cerebral asymmetries, documented in both humans and some nonhuman primate species, are relatively minor compared to behavioral lateralization. Identifying the mechanisms that underlie these functional differences remains a goal of considerable interest. Here, we investigate the intrinsic connectivity networks in four primate species (humans, chimpanzees, baboons, and capuchin monkeys) using resting-state fMRI to evaluate the intra- and inter- hemispheric coherences of spontaneous BOLD fluctuation. All three nonhuman primate species displayed lateralized functional networks that were strikingly similar to those observed in humans. However, only humans had multi-region lateralized networks, which provide fronto-parietal connectivity. Our results indicate that this pattern of within-hemisphere connectivity distinguishes humans from nonhuman primates." -24038902,PMC4791049,10.1002/hbm.22364,Functional characterization and differential coactivation patterns of two cytoarchitectonic visual areas on the human posterior fusiform gyrus,"['Caspers J', 'Zilles K', 'Amunts K', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2014,6,17,Hum Brain Mapp,35,6,2754-67,"The ventral stream of the human extrastriate visual cortex shows a considerable functional heterogeneity from early visual processing (posterior) to higher, domain-specific processing (anterior). The fusiform gyrus hosts several of those ""high-level"" functional areas. We recently found a subdivision of the posterior fusiform gyrus on the microstructural level, that is, two distinct cytoarchitectonic areas, FG1 and FG2 (Caspers et al., Brain Structure & Function, 2013). To gain a first insight in the function of these two areas, here we studied their behavioral involvement and coactivation patterns by means of meta-analytic connectivity modeling based on the BrainMap database (www.brainmap.org), using probabilistic maps of these areas as seed regions. The coactivation patterns of the areas support the concept of a common involvement in a core network subserving different cognitive tasks, that is, object recognition, visual language perception, or visual attention. In addition, the analysis supports the previous cytoarchitectonic parcellation, indicating that FG1 appears as a transitional area between early and higher visual cortex and FG2 as a higher-order one. The latter area is furthermore lateralized, as it shows strong relations to the visual language processing system in the left hemisphere, while its right side is stronger associated with face selective regions. These findings indicate that functional lateralization of area FG2 relies on a different pattern of connectivity rather than side-specific cytoarchitectonic features." +23702412,PMC5325035,10.1016/j.neuroimage.2013.05.052,"Cytoarchitecture, probability maps and functions of the human frontal pole","['Bludau S', 'Eickhoff SB', 'Mohlberg H', 'Caspers S', 'Laird AR', 'Fox PT', 'Schleicher A', 'Zilles K', 'Amunts K']",2014,6,8,Neuroimage,93 Pt 2,,260-75,"The frontal pole has more expanded than any other part in the human brain as compared to our ancestors. It plays an important role for specifically human behavior and cognitive abilities, e.g. action selection (Kovach et al., 2012). Evidence about divergent functions of its medial and lateral part has been provided, both in the healthy brain and in psychiatric disorders. The anatomical correlates of such functional segregation, however, are still unknown due to a lack of stereotaxic, microstructural maps obtained in a representative sample of brains. Here we show that the human frontopolar cortex consists of two cytoarchitectonically and functionally distinct areas: lateral frontopolar area 1 (Fp1) and medial frontopolar area 2 (Fp2). Based on observer-independent mapping in serial, cell-body stained sections of 10 brains, three-dimensional, probabilistic maps of areas Fp1 and Fp2 were created. They show, for each position of the reference space, the probability with which each area was found in a particular voxel. Applying these maps as seed regions for a meta-analysis revealed that Fp1 and Fp2 differentially contribute to functional networks: Fp1 was involved in cognition, working memory and perception, whereas Fp2 was part of brain networks underlying affective processing and social cognition. The present study thus disclosed cortical correlates of a functional segregation of the human frontopolar cortex. The probabilistic maps provide a sound anatomical basis for interpreting neuroimaging data in the living human brain, and open new perspectives for analyzing structure-function relationships in the prefrontal cortex. The new data will also serve as a starting point for further comparative studies between human and non-human primate brains. This allows finding similarities and differences in the organizational principles of the frontal lobe during evolution as neurobiological basis for our behavior and cognitive abilities." +23755001,PMC3665907,10.3389/fnhum.2013.00232,Segregation of the human medial prefrontal cortex in social cognition,"['Bzdok D', 'Langner R', 'Schilbach L', 'Engemann DA', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2013,6,8,Front Hum Neurosci,7,,232,"While the human medial prefrontal cortex (mPFC) is widely believed to be a key node of neural networks relevant for socio-emotional processing, its functional subspecialization is still poorly understood. We thus revisited the often assumed differentiation of the mPFC in social cognition along its ventral-dorsal axis. Our neuroinformatic analysis was based on a neuroimaging meta-analysis of perspective-taking that yielded two separate clusters in the ventral and dorsal mPFC, respectively. We determined each seed region's brain-wide interaction pattern by two complementary measures of functional connectivity: co-activation across a wide range of neuroimaging studies archived in the BrainMap database and correlated signal fluctuations during unconstrained (""resting"") cognition. Furthermore, we characterized the functions associated with these two regions using the BrainMap database. Across methods, the ventral mPFC was more strongly connected with the nucleus accumbens, hippocampus, posterior cingulate cortex, and retrosplenial cortex, while the dorsal mPFC was more strongly connected with the inferior frontal gyrus, temporo-parietal junction, and middle temporal gyrus. Further, the ventral mPFC was selectively associated with reward related tasks, while the dorsal mPFC was selectively associated with perspective-taking and episodic memory retrieval. The ventral mPFC is therefore predominantly involved in bottom-up-driven, approach/avoidance-modulating, and evaluation-related processing, whereas the dorsal mPFC is predominantly involved in top-down-driven, probabilistic-scene-informed, and metacognition-related processing in social cognition." +23781190,PMC3679482,10.3389/fnhum.2013.00268,Dysregulated left inferior parietal activity in schizophrenia and depression: functional connectivity and characterization,"['Muller VI', 'Cieslik EC', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2013,6,8,Front Hum Neurosci,7,,268,"The inferior parietal cortex (IPC) is a heterogeneous region that is known to be involved in a multitude of diverse different tasks and processes, though its contribution to these often-complex functions is yet poorly understood. In a previous study we demonstrated that patients with depression failed to deactivate the left IPC during processing of congruent audiovisual information. We now found the same dysregulation (same region and condition) in schizophrenia. By using task-independent (resting state) and task-dependent meta-analytic connectivity modeling (MACM) analyses we aimed at characterizing this particular region with regard to its connectivity and function. Across both approaches, results revealed functional connectivity of the left inferior parietal seed region with bilateral IPC, precuneus and posterior cingulate cortex (PrC/PCC), medial orbitofrontal cortex (mOFC), left middle frontal (MFG) as well as inferior frontal (IFG) gyrus. Network-level functional characterization further revealed that on the one hand, all interconnected regions are part of a network involved in memory processes. On the other hand, sub-networks are formed when emotion, language, social cognition and reasoning processes are required. Thus, the IPC-region that is dysregulated in both depression and schizophrenia is functionally connected to a network of regions which, depending on task demands may form sub-networks. These results therefore indicate that dysregulation of left IPC in depression and schizophrenia might not only be connected to deficits in audiovisual integration, but is possibly also associated to impaired memory and deficits in emotion processing in these patient groups." +23791915,PMC4791055,10.1016/j.neuroimage.2013.06.041,Tackling the multifunctional nature of Broca's region meta-analytically: co-activation-based parcellation of area 44,"['Clos M', 'Amunts K', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2013,12,8,Neuroimage,83,,174-88,"Cytoarchitectonic area 44 of Broca's region in the left inferior frontal gyrus is known to be involved in several functional domains including language, action and music processing. We investigated whether this functional heterogeneity is reflected in distinct modules within cytoarchitectonically defined left area 44 using meta-analytic connectivity-based parcellation (CBP). This method relies on identifying the whole-brain co-activation pattern for each area 44 voxel across a wide range of functional neuroimaging experiments and subsequently grouping the voxels into distinct clusters based on the similarity of their co-activation patterns. This CBP analysis revealed that five separate clusters exist within left area 44. A post-hoc functional characterization and functional connectivity analysis of these five clusters was then performed. The two posterior clusters were primarily associated with action processes, in particular with phonology and overt speech (posterior-dorsal cluster) and with rhythmic sequencing (posterior-ventral cluster). The three anterior clusters were primarily associated with language and cognition, in particular with working memory (anterior-dorsal cluster), with detection of meaning (anterior-ventral cluster) and with task switching/cognitive control (inferior frontal junction cluster). These five clusters furthermore showed specific and distinct connectivity patterns. The results demonstrate that left area 44 is heterogeneous, thus supporting anatomical data on the molecular architecture of this region, and provide a basis for more specific interpretations of activations localized in area 44." +23928747,PMC4219928,10.1007/s00429-013-0620-9,Multi-region hemispheric specialization differentiates human from nonhuman primate brain function,"['Wey HY', 'Phillips KA', 'McKay DR', 'Laird AR', 'Kochunov P', 'Davis MD', 'Glahn DC', 'Blangero J', 'Duong TQ', 'Fox PT']",2014,11,8,Brain Struct Funct,219,6,2187-94,"The human behavioral repertoire greatly exceeds that of nonhuman primates. Anatomical specializations of the human brain include an enlarged neocortex and prefrontal cortex (Semendeferi et al. in Am J Phys Anthropol 114:224-241, 2001), but regional enlargements alone cannot account for these vast functional differences. Hemispheric specialization has long believed to be a major contributing factor to such distinctive human characteristics as motor dominance, attentional control and language. Yet structural cerebral asymmetries, documented in both humans and some nonhuman primate species, are relatively minor compared to behavioral lateralization. Identifying the mechanisms that underlie these functional differences remains a goal of considerable interest. Here, we investigate the intrinsic connectivity networks in four primate species (humans, chimpanzees, baboons, and capuchin monkeys) using resting-state fMRI to evaluate the intra- and inter- hemispheric coherences of spontaneous BOLD fluctuation. All three nonhuman primate species displayed lateralized functional networks that were strikingly similar to those observed in humans. However, only humans had multi-region lateralized networks, which provide fronto-parietal connectivity. Our results indicate that this pattern of within-hemisphere connectivity distinguishes humans from nonhuman primates." +24038902,PMC4791049,10.1002/hbm.22364,Functional characterization and differential coactivation patterns of two cytoarchitectonic visual areas on the human posterior fusiform gyrus,"['Caspers J', 'Zilles K', 'Amunts K', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2014,6,8,Hum Brain Mapp,35,6,2754-67,"The ventral stream of the human extrastriate visual cortex shows a considerable functional heterogeneity from early visual processing (posterior) to higher, domain-specific processing (anterior). The fusiform gyrus hosts several of those ""high-level"" functional areas. We recently found a subdivision of the posterior fusiform gyrus on the microstructural level, that is, two distinct cytoarchitectonic areas, FG1 and FG2 (Caspers et al., Brain Structure & Function, 2013). To gain a first insight in the function of these two areas, here we studied their behavioral involvement and coactivation patterns by means of meta-analytic connectivity modeling based on the BrainMap database (www.brainmap.org), using probabilistic maps of these areas as seed regions. The coactivation patterns of the areas support the concept of a common involvement in a core network subserving different cognitive tasks, that is, object recognition, visual language perception, or visual attention. In addition, the analysis supports the previous cytoarchitectonic parcellation, indicating that FG1 appears as a transitional area between early and higher visual cortex and FG2 as a higher-order one. The latter area is furthermore lateralized, as it shows strong relations to the visual language processing system in the left hemisphere, while its right side is stronger associated with face selective regions. These findings indicate that functional lateralization of area FG2 relies on a different pattern of connectivity rather than side-specific cytoarchitectonic features." 24068828,PMC3782630,10.1523/JNEUROSCI.1616-13.2013,Sulcal depth-position profile is a genetically mediated neuroscientific trait: description and characterization in the central sulcus,"['McKay DR', 'Kochunov P', 'Cykowski MD', 'Kent JW Jr', 'Laird AR', 'Lancaster JL', 'Blangero J', 'Glahn DC', 'Fox PT']",2013,9,25,J Neurosci,33,39,15618-25,"Genetic and environmental influences on brain morphology were assessed in an extended-pedigree design by extracting depth-position profiles (DPP) of the central sulcus (CS). T1-weighted magnetic resonance images were used to measure CS length and depth in 467 human subjects from 35 extended families. Three primary forms of DPPs were observed. The most prevalent form, present in 70% of subjects, was bimodal, with peaks near hand and mouth regions. Trimodal and unimodal configurations accounted for 15 and 8%, respectively. Genetic control accounted for 56 and 66% of between-subject variance in average CS depth and length, respectively, and was not significantly influenced by environmental factors. Genetic control over CS depth ranged from 1 to 50% across the DPP. Areas of peak heritability occurred at locations corresponding to hand and mouth areas. Left and right analogous CS depth measurements were strongly pleiotropic. Shared genetic influence lessened as the distance between depth measurements was increased. We argue that DPPs are powerful phenotypes that should inform genetic influence of more complex brain regions and contribute to gene discovery efforts." -24115159,PMC5293144,10.1002/hbm.22363,The role of anterior midcingulate cortex in cognitive motor control: evidence from functional connectivity analyses,"['Hoffstaedter F', 'Grefkes C', 'Caspers S', 'Roski C', 'Palomero-Gallagher N', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2014,6,17,Hum Brain Mapp,35,6,2741-53,"The rostral cingulate cortex has been associated with a multitude of cognitive control functions. Recent neuroimaging data suggest that the anterior midcingulate cortex (aMCC) has a key role for cognitive aspects of movement generation, i.e., intentional motor control. We here tested the functional connectivity of this area using two complementary approaches: (1) resting-state connectivity of the aMCC based on fMRI scans obtained in 100 subjects, and (2) functional connectivity in the context of explicit task conditions using meta-analytic connectivity modeling (MACM) over 656 imaging experiment. Both approaches revealed a convergent functional network architecture of the aMCC with prefrontal, premotor and parietal cortices as well as anterior insula, area 44/45, cerebellum and dorsal striatum. To specifically test the role of the aMCC's task-based functional connectivity in cognitive motor control, separate MACM analyses were conducted over ""cognitive"" and ""action"" related experimental paradigms. Both analyses confirmed the same task-based connectivity pattern of the aMCC. While the ""cognition"" domain showed higher convergence of activity in supramodal association areas in prefrontal cortex and anterior insula, ""action"" related experiments yielded higher convergence in somatosensory and premotor areas. Secondly, to probe the functional specificity of the aMCC's convergent functional connectivity, it was compared with a neural network of intentional movement initiation. This exemplary comparison confirmed the involvement of the state independent FC network of the aMCC in the intentional generation of movements. In summary, the different experiments of the present study suggest that the aMCC constitute a key region in the network realizing intentional motor control." -24142505,PMC5293143,10.1002/hbm.22392,Bridging the gap between functional and anatomical features of cortico-cerebellar circuits using meta-analytic connectivity modeling,"['Balsters JH', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2014,7,17,Hum Brain Mapp,35,7,3152-69,"Theories positing that the cerebellum contributes to cognitive as well as motor control are driven by two sources of information: (1) studies highlighting connections between the cerebellum and both prefrontal and motor territories, (2) functional neuroimaging studies demonstrating cerebellar activations evoked during the performance of both cognitive and motor tasks. However, almost no studies to date have combined these two sources of information and investigated cortico-cerebellar connectivity during task performance. Through the use of a novel neuroimaging tool (Meta-Analytic Connectivity Modelling) we demonstrate for the first time that cortico-cerebellar connectivity patterns seen in anatomical studies and resting fMRI are also present during task performance. Consistent with human and nonhuman primate anatomical studies cerebellar lobules Crus I and II were significantly coactivated with prefrontal and parietal cortices during task performance, whilst lobules HV, HVI, HVIIb, and HVIII were significantly coactivated with the pre- and postcentral gyrus. An analysis of the behavioral domains showed that these circuits were driven by distinct tasks. Prefrontal-parietal-cerebellar circuits were more active during cognitive and emotion tasks whilst motor-cerebellar circuits were more active during action execution tasks. These results highlight the separation of prefrontal and motor cortico-cerebellar loops during task performance, and further demonstrate that activity within these circuits relates to distinct functions." -24174404,PMC4007379,10.1002/oby.20659,Neural bases of food perception: coordinate-based meta-analyses of neuroimaging studies in multiple modalities,"['Huerta CI', 'Sarkar PR', 'Duong TQ', 'Laird AR', 'Fox PT']",2014,6,17,Obesity (Silver Spring),22,6,1439-46,"OBJECTIVE: The purpose of this study was to compare the results of the three food-cue paradigms most commonly used for functional neuroimaging studies to determine: i) commonalities and differences in the neural response patterns by paradigm and ii) the relative robustness and reliability of responses to each paradigm. METHODS: Functional magnetic resonance imaging studies using standardized stereotactic coordinates to report brain responses to food cues were identified using online databases. Studies were grouped by food-cue modality as: i) tastes (8 studies); ii) odors (8 studies); and, iii) images (11 studies). Activation likelihood estimation was used to identify statistically reliable regional responses within each stimulation paradigm. RESULTS: Brain response distributions were distinctly different for the three stimulation modalities, corresponding to known differences in location of the respective primary and associative cortices. Visual stimulation induced the most robust and extensive responses. The left anterior insula was the only brain region reliably responding to all three stimulus categories. CONCLUSIONS: These findings suggest visual food-cue paradigm as promising candidate for imaging studies addressing the neural substrate of therapeutic interventions." -24179755,PMC3777772,10.1016/j.nicl.2012.11.004,Thalamic medial dorsal nucleus atrophy in medial temporal lobe epilepsy: A VBM meta-analysis,"['Barron DS', 'Fox PM', 'Laird AR', 'Robinson JL', 'Fox PT']",2012,3,17,Neuroimage Clin,2,,25-32,"PURPOSE: Medial temporal lobe epilepsy (MTLE) is associated with MTLE network pathology within and beyond the hippocampus. The purpose of this meta-analysis was to identify consistent MTLE structural change to guide subsequent targeted analyses of these areas. METHODS: We performed an anatomic likelihood estimation (ALE) meta-analysis of 22 whole-brain voxel-based morphometry experiments from 11 published studies. We grouped these experiments in three ways. We then constructed a meta-analytic connectivity model (MACM) for regions of consistent MTLE structural change as reported by the ALE analysis. KEY FINDINGS: ALE reported spatially consistent structural change across VBM studies only in the epileptogenic hippocampus and the bilateral thalamus; within the thalamus, the medial dorsal nucleus of the thalamus (MDN thalamus) represented the greatest convergence (P < 0.05 corrected for multiple comparisons). The subsequent MACM for the hippocampus and ipsilateral MDN thalamus demonstrated that the hippocampus and ipsilateral MDN thalamus functionally co-activate and are nodes within the same network, suggesting that MDN thalamic damage could result from MTLE network excitotoxicity. SIGNIFICANCE: Notwithstanding our large sample of studies, these findings are more restrictive than previous reports and demonstrate the utility of our inclusion filters and of recently modified meta-analytic methods in approximating clinical relevance. Thalamic pathology is commonly observed in animal and human studies, suggesting it could be a clinically useful indicator. Thalamus-specific research as a clinical marker awaits further investigation." -24194718,PMC3810651,10.3389/fnagi.2013.00067,Adult age-dependent differences in resting-state connectivity within and between visual-attention and sensorimotor networks,"['Roski C', 'Caspers S', 'Langner R', 'Laird AR', 'Fox PT', 'Zilles K', 'Amunts K', 'Eickhoff SB']",2013,3,17,Front Aging Neurosci,5,,67,"Healthy aging is accompanied by structural and functional changes in the brain, among which a loss of neural specificity (i.e., dedifferentiation) is one of the most consistent findings. Little is known, however, about changes in interregional integration underlying a dedifferentiation across different functional systems. In a large sample (n = 399) of healthy adults aged from 18 to 85 years, we analyzed age-dependent differences in resting-state (RS) (task-independent) functional connectivity (FC) of a set of brain regions derived from a previous fMRI study. In that study, these regions had shown an age-related loss of activation specificity in visual-attention (superior parietal area 7A and dorsal premotor cortex) or sensorimotor (area OP4 of the parietal operculum) tasks. In addition to these dedifferentiated regions, the FC analysis of the present study included ""task-general"" regions associated with both attention and sensorimotor systems (rostral supplementary motor area and bilateral anterior insula) as defined via meta-analytical co-activation mapping. Within this network, we observed both selective increases and decreases in RS-FC with age. In line with regional activation changes reported previously, we found diminished anti-correlated FC for inter-system connections (i.e., between sensorimotor-related and visual attention-related regions). Our analysis also revealed reduced FC between system-specific and task-general regions, which might reflect age-related deficits in top-down control possibly leading to dedifferentiation of task-specific brain activity. Together, our results underpin the notion that RS-FC changes concur with regional activity changes in the healthy aging brain, presumably contributing jointly to age-related behavioral changes." +24115159,PMC5293144,10.1002/hbm.22363,The role of anterior midcingulate cortex in cognitive motor control: evidence from functional connectivity analyses,"['Hoffstaedter F', 'Grefkes C', 'Caspers S', 'Roski C', 'Palomero-Gallagher N', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2014,6,8,Hum Brain Mapp,35,6,2741-53,"The rostral cingulate cortex has been associated with a multitude of cognitive control functions. Recent neuroimaging data suggest that the anterior midcingulate cortex (aMCC) has a key role for cognitive aspects of movement generation, i.e., intentional motor control. We here tested the functional connectivity of this area using two complementary approaches: (1) resting-state connectivity of the aMCC based on fMRI scans obtained in 100 subjects, and (2) functional connectivity in the context of explicit task conditions using meta-analytic connectivity modeling (MACM) over 656 imaging experiment. Both approaches revealed a convergent functional network architecture of the aMCC with prefrontal, premotor and parietal cortices as well as anterior insula, area 44/45, cerebellum and dorsal striatum. To specifically test the role of the aMCC's task-based functional connectivity in cognitive motor control, separate MACM analyses were conducted over ""cognitive"" and ""action"" related experimental paradigms. Both analyses confirmed the same task-based connectivity pattern of the aMCC. While the ""cognition"" domain showed higher convergence of activity in supramodal association areas in prefrontal cortex and anterior insula, ""action"" related experiments yielded higher convergence in somatosensory and premotor areas. Secondly, to probe the functional specificity of the aMCC's convergent functional connectivity, it was compared with a neural network of intentional movement initiation. This exemplary comparison confirmed the involvement of the state independent FC network of the aMCC in the intentional generation of movements. In summary, the different experiments of the present study suggest that the aMCC constitute a key region in the network realizing intentional motor control." +24142505,PMC5293143,10.1002/hbm.22392,Bridging the gap between functional and anatomical features of cortico-cerebellar circuits using meta-analytic connectivity modeling,"['Balsters JH', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2014,7,8,Hum Brain Mapp,35,7,3152-69,"Theories positing that the cerebellum contributes to cognitive as well as motor control are driven by two sources of information: (1) studies highlighting connections between the cerebellum and both prefrontal and motor territories, (2) functional neuroimaging studies demonstrating cerebellar activations evoked during the performance of both cognitive and motor tasks. However, almost no studies to date have combined these two sources of information and investigated cortico-cerebellar connectivity during task performance. Through the use of a novel neuroimaging tool (Meta-Analytic Connectivity Modelling) we demonstrate for the first time that cortico-cerebellar connectivity patterns seen in anatomical studies and resting fMRI are also present during task performance. Consistent with human and nonhuman primate anatomical studies cerebellar lobules Crus I and II were significantly coactivated with prefrontal and parietal cortices during task performance, whilst lobules HV, HVI, HVIIb, and HVIII were significantly coactivated with the pre- and postcentral gyrus. An analysis of the behavioral domains showed that these circuits were driven by distinct tasks. Prefrontal-parietal-cerebellar circuits were more active during cognitive and emotion tasks whilst motor-cerebellar circuits were more active during action execution tasks. These results highlight the separation of prefrontal and motor cortico-cerebellar loops during task performance, and further demonstrate that activity within these circuits relates to distinct functions." +24174404,PMC4007379,10.1002/oby.20659,Neural bases of food perception: coordinate-based meta-analyses of neuroimaging studies in multiple modalities,"['Huerta CI', 'Sarkar PR', 'Duong TQ', 'Laird AR', 'Fox PT']",2014,6,8,Obesity (Silver Spring),22,6,1439-46,"OBJECTIVE: The purpose of this study was to compare the results of the three food-cue paradigms most commonly used for functional neuroimaging studies to determine: i) commonalities and differences in the neural response patterns by paradigm and ii) the relative robustness and reliability of responses to each paradigm. METHODS: Functional magnetic resonance imaging studies using standardized stereotactic coordinates to report brain responses to food cues were identified using online databases. Studies were grouped by food-cue modality as: i) tastes (8 studies); ii) odors (8 studies); and, iii) images (11 studies). Activation likelihood estimation was used to identify statistically reliable regional responses within each stimulation paradigm. RESULTS: Brain response distributions were distinctly different for the three stimulation modalities, corresponding to known differences in location of the respective primary and associative cortices. Visual stimulation induced the most robust and extensive responses. The left anterior insula was the only brain region reliably responding to all three stimulus categories. CONCLUSIONS: These findings suggest visual food-cue paradigm as promising candidate for imaging studies addressing the neural substrate of therapeutic interventions." +24179755,PMC3777772,10.1016/j.nicl.2012.11.004,Thalamic medial dorsal nucleus atrophy in medial temporal lobe epilepsy: A VBM meta-analysis,"['Barron DS', 'Fox PM', 'Laird AR', 'Robinson JL', 'Fox PT']",2012,6,8,Neuroimage Clin,2,,25-32,"PURPOSE: Medial temporal lobe epilepsy (MTLE) is associated with MTLE network pathology within and beyond the hippocampus. The purpose of this meta-analysis was to identify consistent MTLE structural change to guide subsequent targeted analyses of these areas. METHODS: We performed an anatomic likelihood estimation (ALE) meta-analysis of 22 whole-brain voxel-based morphometry experiments from 11 published studies. We grouped these experiments in three ways. We then constructed a meta-analytic connectivity model (MACM) for regions of consistent MTLE structural change as reported by the ALE analysis. KEY FINDINGS: ALE reported spatially consistent structural change across VBM studies only in the epileptogenic hippocampus and the bilateral thalamus; within the thalamus, the medial dorsal nucleus of the thalamus (MDN thalamus) represented the greatest convergence (P < 0.05 corrected for multiple comparisons). The subsequent MACM for the hippocampus and ipsilateral MDN thalamus demonstrated that the hippocampus and ipsilateral MDN thalamus functionally co-activate and are nodes within the same network, suggesting that MDN thalamic damage could result from MTLE network excitotoxicity. SIGNIFICANCE: Notwithstanding our large sample of studies, these findings are more restrictive than previous reports and demonstrate the utility of our inclusion filters and of recently modified meta-analytic methods in approximating clinical relevance. Thalamic pathology is commonly observed in animal and human studies, suggesting it could be a clinically useful indicator. Thalamus-specific research as a clinical marker awaits further investigation." +24194718,PMC3810651,10.3389/fnagi.2013.00067,Adult age-dependent differences in resting-state connectivity within and between visual-attention and sensorimotor networks,"['Roski C', 'Caspers S', 'Langner R', 'Laird AR', 'Fox PT', 'Zilles K', 'Amunts K', 'Eickhoff SB']",2013,6,8,Front Aging Neurosci,5,,67,"Healthy aging is accompanied by structural and functional changes in the brain, among which a loss of neural specificity (i.e., dedifferentiation) is one of the most consistent findings. Little is known, however, about changes in interregional integration underlying a dedifferentiation across different functional systems. In a large sample (n = 399) of healthy adults aged from 18 to 85 years, we analyzed age-dependent differences in resting-state (RS) (task-independent) functional connectivity (FC) of a set of brain regions derived from a previous fMRI study. In that study, these regions had shown an age-related loss of activation specificity in visual-attention (superior parietal area 7A and dorsal premotor cortex) or sensorimotor (area OP4 of the parietal operculum) tasks. In addition to these dedifferentiated regions, the FC analysis of the present study included ""task-general"" regions associated with both attention and sensorimotor systems (rostral supplementary motor area and bilateral anterior insula) as defined via meta-analytical co-activation mapping. Within this network, we observed both selective increases and decreases in RS-FC with age. In line with regional activation changes reported previously, we found diminished anti-correlated FC for inter-system connections (i.e., between sensorimotor-related and visual attention-related regions). Our analysis also revealed reduced FC between system-specific and task-general regions, which might reflect age-related deficits in top-down control possibly leading to dedifferentiation of task-specific brain activity. Together, our results underpin the notion that RS-FC changes concur with regional activity changes in the healthy aging brain, presumably contributing jointly to age-related behavioral changes." 24220041,PMC4801480,10.1016/j.neuroimage.2013.11.001,Neural network of cognitive emotion regulation--an ALE meta-analysis and MACM analysis,"['Kohn N', 'Eickhoff SB', 'Scheller M', 'Laird AR', 'Fox PT', 'Habel U']",2014,2,15,Neuroimage,87,,345-55,"Cognitive regulation of emotions is a fundamental prerequisite for intact social functioning which impacts on both well being and psychopathology. The neural underpinnings of this process have been studied intensively in recent years, without, however, a general consensus. We here quantitatively summarize the published literature on cognitive emotion regulation using activation likelihood estimation in fMRI and PET (23 studies/479 subjects). In addition, we assessed the particular functional contribution of identified regions and their interactions using quantitative functional inference and meta-analytic connectivity modeling, respectively. In doing so, we developed a model for the core brain network involved in emotion regulation of emotional reactivity. According to this, the superior temporal gyrus, angular gyrus and (pre) supplementary motor area should be involved in execution of regulation initiated by frontal areas. The dorsolateral prefrontal cortex may be related to regulation of cognitive processes such as attention, while the ventrolateral prefrontal cortex may not necessarily reflect the regulatory process per se, but signals salience and therefore the need to regulate. We also identified a cluster in the anterior middle cingulate cortex as a region, which is anatomically and functionally in an ideal position to influence behavior and subcortical structures related to affect generation. Hence this area may play a central, integrative role in emotion regulation. By focusing on regions commonly active across multiple studies, this proposed model should provide important a priori information for the assessment of dysregulated emotion regulation in psychiatric disorders." -24339802,PMC3857551,10.3389/fnins.2013.00237,ICA model order selection of task co-activation networks,"['Ray KL', 'McKay DR', 'Fox PM', 'Riedel MC', 'Uecker AM', 'Beckmann CF', 'Smith SM', 'Fox PT', 'Laird AR']",2013,3,17,Front Neurosci,7,,237,"Independent component analysis (ICA) has become a widely used method for extracting functional networks in the brain during rest and task. Historically, preferred ICA dimensionality has widely varied within the neuroimaging community, but typically varies between 20 and 100 components. This can be problematic when comparing results across multiple studies because of the impact ICA dimensionality has on the topology of its resultant components. Recent studies have demonstrated that ICA can be applied to peak activation coordinates archived in a large neuroimaging database (i.e., BrainMap Database) to yield whole-brain task-based co-activation networks. A strength of applying ICA to BrainMap data is that the vast amount of metadata in BrainMap can be used to quantitatively assess tasks and cognitive processes contributing to each component. In this study, we investigated the effect of model order on the distribution of functional properties across networks as a method for identifying the most informative decompositions of BrainMap-based ICA components. Our findings suggest dimensionality of 20 for low model order ICA to examine large-scale brain networks, and dimensionality of 70 to provide insight into how large-scale networks fractionate into sub-networks. We also provide a functional and organizational assessment of visual, motor, emotion, and interoceptive task co-activation networks as they fractionate from low to high model-orders." -24354662,PMC4057361,10.1111/adb.12118,Greater externalizing personality traits predict less error-related insula and anterior cingulate cortex activity in acutely abstinent cigarette smokers,"['Carroll AJ', 'Sutherland MT', 'Salmeron BJ', 'Ross TJ', 'Stein EA']",2015,3,17,Addict Biol,20,2,377-89,"Attenuated activity in performance-monitoring brain regions following erroneous actions may contribute to the repetition of maladaptive behaviors such as continued drug use. Externalizing is a broad personality construct characterized by deficient impulse control, vulnerability to addiction and reduced neurobiological indices of error processing. The insula and dorsal anterior cingulate cortex (dACC) are regions critically linked with error processing as well as the perpetuation of cigarette smoking. As such, we examined the interrelations between externalizing tendencies, erroneous task performance, and error-related insula and dACC activity in overnight-deprived smokers (n = 24) and non-smokers (n = 20). Participants completed a self-report measure assessing externalizing tendencies (Externalizing Spectrum Inventory) and a speeded Flanker task during functional magnetic resonance imaging scanning. We observed that higher externalizing tendencies correlated with the occurrence of more performance errors among smokers but not non-smokers. Suggesting a neurobiological contribution to such suboptimal performance among smokers, higher externalizing also predicted less recruitment of the right insula and dACC following error commission. Critically, this error-related activity fully mediated the relationship between externalizing traits and error rates. That is, higher externalizing scores predicted less error-related right insula and dACC activity and, in turn, less error-related activity predicted more errors. Relating such regional activity with a clinically relevant construct, less error-related right insula and dACC responses correlated with higher tobacco craving during abstinence. Given that inadequate error-related neuronal responses may contribute to continued drug use despite negative consequences, these results suggest that externalizing tendencies and/or compromised error processing among subsets of smokers may be relevant factors for smoking cessation success." -24399179,PMC4087104,10.1007/s00429-013-0698-0,Definition and characterization of an extended social-affective default network,"['Amft M', 'Bzdok D', 'Laird AR', 'Fox PT', 'Schilbach L', 'Eickhoff SB']",2015,3,17,Brain Struct Funct,220,2,1031-49,"Recent evidence suggests considerable overlap between the default mode network (DMN) and regions involved in social, affective and introspective processes. We considered these overlapping regions as the social-affective part of the DMN. In this study, we established a robust mapping of the underlying brain network formed by these regions and those strongly connected to them (the extended social-affective default network). We first seeded meta-analytic connectivity modeling and resting-state analyses in the meta-analytically defined DMN regions that showed statistical overlap with regions associated with social and affective processing. Consensus connectivity of each seed was subsequently delineated by a conjunction across both connectivity analyses. We then functionally characterized the ensuing regions and performed several cluster analyses. Among the identified regions, the amygdala/hippocampus formed a cluster associated with emotional processes and memory functions. The ventral striatum, anterior cingulum, subgenual cingulum and ventromedial prefrontal cortex formed a heterogeneous subgroup associated with motivation, reward and cognitive modulation of affect. Posterior cingulum/precuneus and dorsomedial prefrontal cortex were associated with mentalizing, self-reference and autobiographic information. The cluster formed by the temporo-parietal junction and anterior middle temporal sulcus/gyrus was associated with language and social cognition. Taken together, the current work highlights a robustly interconnected network that may be central to introspective, socio-affective, that is, self- and other-related mental processes." -24409112,PMC3864256,10.3389/fnins.2013.00240,Automated annotation of functional imaging experiments via multi-label classification,"['Turner MD', 'Chakrabarti C', 'Jones TB', 'Xu JF', 'Fox PT', 'Luger GF', 'Laird AR', 'Turner JA']",2013,3,17,Front Neurosci,7,,240,"Identifying the experimental methods in human neuroimaging papers is important for grouping meaningfully similar experiments for meta-analyses. Currently, this can only be done by human readers. We present the performance of common machine learning (text mining) methods applied to the problem of automatically classifying or labeling this literature. Labeling terms are from the Cognitive Paradigm Ontology (CogPO), the text corpora are abstracts of published functional neuroimaging papers, and the methods use the performance of a human expert as training data. We aim to replicate the expert's annotation of multiple labels per abstract identifying the experimental stimuli, cognitive paradigms, response types, and other relevant dimensions of the experiments. We use several standard machine learning methods: naive Bayes (NB), k-nearest neighbor, and support vector machines (specifically SMO or sequential minimal optimization). Exact match performance ranged from only 15% in the worst cases to 78% in the best cases. NB methods combined with binary relevance transformations performed strongly and were robust to overfitting. This collection of results demonstrates what can be achieved with off-the-shelf software components and little to no pre-processing of raw text." -24681401,PMC4526025,10.1016/j.bandl.2014.02.001,The neural changes in connectivity of the voice network during voice pitch perturbation,"['Flagmeier SG', 'Ray KL', 'Parkinson AL', 'Li K', 'Vargas R', 'Price LR', 'Laird AR', 'Larson CR', 'Robin DA']",2014,5,17,Brain Lang,132,,7-13,"Voice control is critical to communication. To date, studies have used behavioral, electrophysiological and functional data to investigate the neural correlates of voice control using perturbation tasks, but have yet to examine the interactions of these neural regions. The goal of this study was to use structural equation modeling of functional neuroimaging data to examine network properties of voice with and without perturbation. Results showed that the presence of a pitch shift, which was processed as an error in vocalization, altered connections between right STG and left STG. Other regions that revealed differences in connectivity during error detection and correction included bilateral inferior frontal gyrus, and the primary and pre motor cortices. Results indicated that STG plays a critical role in voice control, specifically, during error detection and correction. Additionally, pitch perturbation elicits changes in the voice network that suggest the right hemisphere is critical to pitch modulation." -24763126,PMC4108513,10.1016/j.cortex.2014.02.022,Conceptualizing neuropsychiatric diseases with multimodal data-driven meta-analyses - the case of behavioral variant frontotemporal dementia,"['Schroeter ML', 'Laird AR', 'Chwiesko C', 'Deuschl C', 'Schneider E', 'Bzdok D', 'Eickhoff SB', 'Neumann J']",2014,8,17,Cortex,57,,22-37,"INTRODUCTION: Uniform coordinate systems in neuroimaging research have enabled comprehensive systematic and quantitative meta-analyses. Such approaches are particularly relevant for neuropsychiatric diseases, the understanding of their symptoms, prediction and treatment. Behavioral variant frontotemporal dementia (bvFTD), a common neurodegenerative syndrome, is characterized by deep alterations in behavior and personality. Investigating this 'nexopathy' elucidates the healthy social and emotional brain. METHODS: Here, we combine three multimodal meta-analyses approaches - anatomical and activation likelihood estimates and behavioral domain profiles - to identify neural correlates of bvFTD in 417 patients and 406 control subjects and to extract mental functions associated with this disease by meta-analyzing functional activation studies in the comprehensive probabilistic functional brain atlas of the BrainMap database. RESULTS: The analyses identify the frontomedian cortex, basal ganglia, anterior insulae and thalamus as most relevant hubs, with a regional dissociation between atrophy and hypometabolism. Neural networks affected by bvFTD were associated with emotion and reward processing, empathy and executive functions (mainly inhibition), suggesting these functions as core domains affected by the disease and finally leading to its clinical symptoms. In contrast, changes in theory of mind or mentalizing abilities seem to be secondary phenomena of executive dysfunctions. CONCLUSIONS: The study creates a novel conceptual framework to understand neuropsychiatric diseases by powerful data-driven meta-analytic approaches that shall be extended to the whole neuropsychiatric spectrum in the future." +24339802,PMC3857551,10.3389/fnins.2013.00237,ICA model order selection of task co-activation networks,"['Ray KL', 'McKay DR', 'Fox PM', 'Riedel MC', 'Uecker AM', 'Beckmann CF', 'Smith SM', 'Fox PT', 'Laird AR']",2013,6,8,Front Neurosci,7,,237,"Independent component analysis (ICA) has become a widely used method for extracting functional networks in the brain during rest and task. Historically, preferred ICA dimensionality has widely varied within the neuroimaging community, but typically varies between 20 and 100 components. This can be problematic when comparing results across multiple studies because of the impact ICA dimensionality has on the topology of its resultant components. Recent studies have demonstrated that ICA can be applied to peak activation coordinates archived in a large neuroimaging database (i.e., BrainMap Database) to yield whole-brain task-based co-activation networks. A strength of applying ICA to BrainMap data is that the vast amount of metadata in BrainMap can be used to quantitatively assess tasks and cognitive processes contributing to each component. In this study, we investigated the effect of model order on the distribution of functional properties across networks as a method for identifying the most informative decompositions of BrainMap-based ICA components. Our findings suggest dimensionality of 20 for low model order ICA to examine large-scale brain networks, and dimensionality of 70 to provide insight into how large-scale networks fractionate into sub-networks. We also provide a functional and organizational assessment of visual, motor, emotion, and interoceptive task co-activation networks as they fractionate from low to high model-orders." +24354662,PMC4057361,10.1111/adb.12118,Greater externalizing personality traits predict less error-related insula and anterior cingulate cortex activity in acutely abstinent cigarette smokers,"['Carroll AJ', 'Sutherland MT', 'Salmeron BJ', 'Ross TJ', 'Stein EA']",2015,3,8,Addict Biol,20,2,377-89,"Attenuated activity in performance-monitoring brain regions following erroneous actions may contribute to the repetition of maladaptive behaviors such as continued drug use. Externalizing is a broad personality construct characterized by deficient impulse control, vulnerability to addiction and reduced neurobiological indices of error processing. The insula and dorsal anterior cingulate cortex (dACC) are regions critically linked with error processing as well as the perpetuation of cigarette smoking. As such, we examined the interrelations between externalizing tendencies, erroneous task performance, and error-related insula and dACC activity in overnight-deprived smokers (n = 24) and non-smokers (n = 20). Participants completed a self-report measure assessing externalizing tendencies (Externalizing Spectrum Inventory) and a speeded Flanker task during functional magnetic resonance imaging scanning. We observed that higher externalizing tendencies correlated with the occurrence of more performance errors among smokers but not non-smokers. Suggesting a neurobiological contribution to such suboptimal performance among smokers, higher externalizing also predicted less recruitment of the right insula and dACC following error commission. Critically, this error-related activity fully mediated the relationship between externalizing traits and error rates. That is, higher externalizing scores predicted less error-related right insula and dACC activity and, in turn, less error-related activity predicted more errors. Relating such regional activity with a clinically relevant construct, less error-related right insula and dACC responses correlated with higher tobacco craving during abstinence. Given that inadequate error-related neuronal responses may contribute to continued drug use despite negative consequences, these results suggest that externalizing tendencies and/or compromised error processing among subsets of smokers may be relevant factors for smoking cessation success." +24399179,PMC4087104,10.1007/s00429-013-0698-0,Definition and characterization of an extended social-affective default network,"['Amft M', 'Bzdok D', 'Laird AR', 'Fox PT', 'Schilbach L', 'Eickhoff SB']",2015,3,8,Brain Struct Funct,220,2,1031-49,"Recent evidence suggests considerable overlap between the default mode network (DMN) and regions involved in social, affective and introspective processes. We considered these overlapping regions as the social-affective part of the DMN. In this study, we established a robust mapping of the underlying brain network formed by these regions and those strongly connected to them (the extended social-affective default network). We first seeded meta-analytic connectivity modeling and resting-state analyses in the meta-analytically defined DMN regions that showed statistical overlap with regions associated with social and affective processing. Consensus connectivity of each seed was subsequently delineated by a conjunction across both connectivity analyses. We then functionally characterized the ensuing regions and performed several cluster analyses. Among the identified regions, the amygdala/hippocampus formed a cluster associated with emotional processes and memory functions. The ventral striatum, anterior cingulum, subgenual cingulum and ventromedial prefrontal cortex formed a heterogeneous subgroup associated with motivation, reward and cognitive modulation of affect. Posterior cingulum/precuneus and dorsomedial prefrontal cortex were associated with mentalizing, self-reference and autobiographic information. The cluster formed by the temporo-parietal junction and anterior middle temporal sulcus/gyrus was associated with language and social cognition. Taken together, the current work highlights a robustly interconnected network that may be central to introspective, socio-affective, that is, self- and other-related mental processes." +24409112,PMC3864256,10.3389/fnins.2013.00240,Automated annotation of functional imaging experiments via multi-label classification,"['Turner MD', 'Chakrabarti C', 'Jones TB', 'Xu JF', 'Fox PT', 'Luger GF', 'Laird AR', 'Turner JA']",2013,6,8,Front Neurosci,7,,240,"Identifying the experimental methods in human neuroimaging papers is important for grouping meaningfully similar experiments for meta-analyses. Currently, this can only be done by human readers. We present the performance of common machine learning (text mining) methods applied to the problem of automatically classifying or labeling this literature. Labeling terms are from the Cognitive Paradigm Ontology (CogPO), the text corpora are abstracts of published functional neuroimaging papers, and the methods use the performance of a human expert as training data. We aim to replicate the expert's annotation of multiple labels per abstract identifying the experimental stimuli, cognitive paradigms, response types, and other relevant dimensions of the experiments. We use several standard machine learning methods: naive Bayes (NB), k-nearest neighbor, and support vector machines (specifically SMO or sequential minimal optimization). Exact match performance ranged from only 15% in the worst cases to 78% in the best cases. NB methods combined with binary relevance transformations performed strongly and were robust to overfitting. This collection of results demonstrates what can be achieved with off-the-shelf software components and little to no pre-processing of raw text." +24681401,PMC4526025,10.1016/j.bandl.2014.02.001,The neural changes in connectivity of the voice network during voice pitch perturbation,"['Flagmeier SG', 'Ray KL', 'Parkinson AL', 'Li K', 'Vargas R', 'Price LR', 'Laird AR', 'Larson CR', 'Robin DA']",2014,5,8,Brain Lang,132,,7-13,"Voice control is critical to communication. To date, studies have used behavioral, electrophysiological and functional data to investigate the neural correlates of voice control using perturbation tasks, but have yet to examine the interactions of these neural regions. The goal of this study was to use structural equation modeling of functional neuroimaging data to examine network properties of voice with and without perturbation. Results showed that the presence of a pitch shift, which was processed as an error in vocalization, altered connections between right STG and left STG. Other regions that revealed differences in connectivity during error detection and correction included bilateral inferior frontal gyrus, and the primary and pre motor cortices. Results indicated that STG plays a critical role in voice control, specifically, during error detection and correction. Additionally, pitch perturbation elicits changes in the voice network that suggest the right hemisphere is critical to pitch modulation." +24763126,PMC4108513,10.1016/j.cortex.2014.02.022,Conceptualizing neuropsychiatric diseases with multimodal data-driven meta-analyses - the case of behavioral variant frontotemporal dementia,"['Schroeter ML', 'Laird AR', 'Chwiesko C', 'Deuschl C', 'Schneider E', 'Bzdok D', 'Eickhoff SB', 'Neumann J']",2014,8,8,Cortex,57,,22-37,"INTRODUCTION: Uniform coordinate systems in neuroimaging research have enabled comprehensive systematic and quantitative meta-analyses. Such approaches are particularly relevant for neuropsychiatric diseases, the understanding of their symptoms, prediction and treatment. Behavioral variant frontotemporal dementia (bvFTD), a common neurodegenerative syndrome, is characterized by deep alterations in behavior and personality. Investigating this 'nexopathy' elucidates the healthy social and emotional brain. METHODS: Here, we combine three multimodal meta-analyses approaches - anatomical and activation likelihood estimates and behavioral domain profiles - to identify neural correlates of bvFTD in 417 patients and 406 control subjects and to extract mental functions associated with this disease by meta-analyzing functional activation studies in the comprehensive probabilistic functional brain atlas of the BrainMap database. RESULTS: The analyses identify the frontomedian cortex, basal ganglia, anterior insulae and thalamus as most relevant hubs, with a regional dissociation between atrophy and hypometabolism. Neural networks affected by bvFTD were associated with emotion and reward processing, empathy and executive functions (mainly inhibition), suggesting these functions as core domains affected by the disease and finally leading to its clinical symptoms. In contrast, changes in theory of mind or mentalizing abilities seem to be secondary phenomena of executive dysfunctions. CONCLUSIONS: The study creates a novel conceptual framework to understand neuropsychiatric diseases by powerful data-driven meta-analytic approaches that shall be extended to the whole neuropsychiatric spectrum in the future." 24844743,PMC4251452,10.1016/j.neuroimage.2014.05.030,Comparison of structural covariance with functional connectivity approaches exemplified by an investigation of the left anterior insula,"['Clos M', 'Rottschy C', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2014,10,1,Neuroimage,99,,269-80,"The anterior insula is a multifunctional region involved in various cognitive, perceptual and socio-emotional processes. In particular, a portion of the left anterior insula is closely associated with working memory processes in healthy participants and shows gray matter reduction in schizophrenia. To unravel the functional networks related to this left anterior insula region, we here combined resting state connectivity, meta-analytic-connectivity modeling (MACM) and structural covariance (SC) in addition to functional characterization based on BrainMap meta-data. Apart from allowing new insight into the seed region, this approach moreover provided an opportunity to systematically compare these different connectivity approaches. The results showed that the left anterior insula has a broad response profile and is part of multiple functional networks including language, memory and socio-emotional networks. As all these domains are linked with several symptoms of schizophrenia, dysfunction of the left anterior insula might be a crucial component contributing to this disorder. Moreover, although converging connectivity across all three connectivity approaches for the left anterior insula were found, also striking differences were observed. RS and MACM as functional connectivity approaches specifically revealed functional networks linked with internal cognition and active perceptual/language processes, respectively. SC, in turn, showed a clear preference for highlighting regions involved in social cognition. These differential connectivity results thus indicate that the use of multiple forms of connectivity is advantageous when investigating functional networks as conceptual differences between these approaches might lead to systematic variation in the revealed functional networks." -24869925,PMC4782795,10.1007/s00429-014-0791-z,Neural networks related to dysfunctional face processing in autism spectrum disorder,"['Nickl-Jockschat T', 'Rottschy C', 'Thommes J', 'Schneider F', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2015,7,17,Brain Struct Funct,220,4,2355-71,"One of the most consistent neuropsychological findings in autism spectrum disorders (ASD) is a reduced interest in and impaired processing of human faces. We conducted an activation likelihood estimation meta-analysis on 14 functional imaging studies on neural correlates of face processing enrolling a total of 164 ASD patients. Subsequently, normative whole-brain functional connectivity maps for the identified regions of significant convergence were computed for the task-independent (resting-state) and task-dependent (co-activations) state in healthy subjects. Quantitative functional decoding was performed by reference to the BrainMap database. Finally, we examined the overlap of the delineated network with the results of a previous meta-analysis on structural abnormalities in ASD as well as with brain regions involved in human action observation/imitation. We found a single cluster in the left fusiform gyrus showing significantly reduced activation during face processing in ASD across all studies. Both task-dependent and task-independent analyses indicated significant functional connectivity of this region with the temporo-occipital and lateral occipital cortex, the inferior frontal and parietal cortices, the thalamus and the amygdala. Quantitative reverse inference then indicated an association of these regions mainly with face processing, affective processing, and language-related tasks. Moreover, we found that the cortex in the region of right area V5 displaying structural changes in ASD patients showed consistent connectivity with the region showing aberrant responses in the context of face processing. Finally, this network was also implicated in the human action observation/imitation network. In summary, our findings thus suggest a functionally and structurally disturbed network of occipital regions related primarily to face (but potentially also language) processing, which interact with inferior frontal as well as limbic regions and may be the core of aberrant face processing and reduced interest in faces in ASD." +24869925,PMC4782795,10.1007/s00429-014-0791-z,Neural networks related to dysfunctional face processing in autism spectrum disorder,"['Nickl-Jockschat T', 'Rottschy C', 'Thommes J', 'Schneider F', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2015,7,8,Brain Struct Funct,220,4,2355-71,"One of the most consistent neuropsychological findings in autism spectrum disorders (ASD) is a reduced interest in and impaired processing of human faces. We conducted an activation likelihood estimation meta-analysis on 14 functional imaging studies on neural correlates of face processing enrolling a total of 164 ASD patients. Subsequently, normative whole-brain functional connectivity maps for the identified regions of significant convergence were computed for the task-independent (resting-state) and task-dependent (co-activations) state in healthy subjects. Quantitative functional decoding was performed by reference to the BrainMap database. Finally, we examined the overlap of the delineated network with the results of a previous meta-analysis on structural abnormalities in ASD as well as with brain regions involved in human action observation/imitation. We found a single cluster in the left fusiform gyrus showing significantly reduced activation during face processing in ASD across all studies. Both task-dependent and task-independent analyses indicated significant functional connectivity of this region with the temporo-occipital and lateral occipital cortex, the inferior frontal and parietal cortices, the thalamus and the amygdala. Quantitative reverse inference then indicated an association of these regions mainly with face processing, affective processing, and language-related tasks. Moreover, we found that the cortex in the region of right area V5 displaying structural changes in ASD patients showed consistent connectivity with the region showing aberrant responses in the context of face processing. Finally, this network was also implicated in the human action observation/imitation network. In summary, our findings thus suggest a functionally and structurally disturbed network of occipital regions related primarily to face (but potentially also language) processing, which interact with inferior frontal as well as limbic regions and may be the core of aberrant face processing and reduced interest in faces in ASD." 24945668,PMC4112007,10.1016/j.neuroimage.2014.06.007,Meta-analytic connectivity modeling revisited: controlling for activation base rates,"['Langner R', 'Rottschy C', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2014,10,1,Neuroimage,99,,559-70,"Co-activation of distinct brain regions is a measure of functional interaction, or connectivity, between those regions. The co-activation pattern of a given region can be investigated using seed-based activation likelihood estimation meta-analysis of functional neuroimaging data stored in databases such as BrainMap. This method reveals inter-regional functional connectivity by determining brain regions that are consistently co-activated with a given region of interest (the ""seed"") across a broad range of experiments. In current implementations of this meta-analytic connectivity modeling (MACM), significant spatial convergence (i.e. consistent co-activation) is distinguished from noise by comparing it against an unbiased null-distribution of random spatial associations between experiments according to which all gray-matter voxels have the same chance of convergence. As the a priori probability of finding activation in different voxels markedly differs across the brain, computing such a quasi-rectangular null-distribution renders the detection of significant convergence more likely in those voxels that are frequently activated. Here, we propose and test a modified MACM approach that takes this activation frequency bias into account. In this new specific co-activation likelihood estimation (SCALE) algorithm, a null-distribution is generated that reflects the base rate of reporting activation in any given voxel and thus equalizes the a priori chance of finding across-study convergence in each voxel of the brain. Using four exemplary seed regions (right visual area V4, left anterior insula, right intraparietal sulcus, and subgenual cingulum), our tests corroborated the enhanced specificity of the modified algorithm, indicating that SCALE may be especially useful for delineating distinct core networks of co-activation." -25032500,PMC4782802,10.1146/annurev-neuro-062012-170320,Meta-analysis in human neuroimaging: computational modeling of large-scale databases,"['Fox PT', 'Lancaster JL', 'Laird AR', 'Eickhoff SB']",2014,3,17,Annu Rev Neurosci,37,,409-34,"Spatial normalization--applying standardized coordinates as anatomical addresses within a reference space--was introduced to human neuroimaging research nearly 30 years ago. Over these three decades, an impressive series of methodological advances have adopted, extended, and popularized this standard. Collectively, this work has generated a methodologically coherent literature of unprecedented rigor, size, and scope. Large-scale online databases have compiled these observations and their associated meta-data, stimulating the development of meta-analytic methods to exploit this expanding corpus. Coordinate-based meta-analytic methods have emerged and evolved in rigor and utility. Early methods computed cross-study consensus, in a manner roughly comparable to traditional (nonimaging) meta-analysis. Recent advances now compute coactivation-based connectivity, connectivity-based functional parcellation, and complex network models powered from data sets representing tens of thousands of subjects. Meta-analyses of human neuroimaging data in large-scale databases now stand at the forefront of computational neurobiology." -25042764,PMC4157091,10.1016/j.biopsycho.2014.06.008,Gender differences in working memory networks: a BrainMap meta-analysis,"['Hill AC', 'Laird AR', 'Robinson JL']",2014,10,17,Biol Psychol,102,,18-29,"Gender differences in psychological processes have been of great interest in a variety of fields. While the majority of research in this area has focused on specific differences in relation to test performance, this study sought to determine the underlying neurofunctional differences observed during working memory, a pivotal cognitive process shown to be predictive of academic achievement and intelligence. Using the BrainMap database, we performed a meta-analysis and applied activation likelihood estimation to our search set. Our results demonstrate consistent working memory networks across genders, but also provide evidence for gender-specific networks whereby females consistently activate more limbic (e.g., amygdala and hippocampus) and prefrontal structures (e.g., right inferior frontal gyrus), and males activate a distributed network inclusive of more parietal regions. These data provide a framework for future investigations using functional or effective connectivity methods to elucidate the underpinnings of gender differences in neural network recruitment during working memory tasks." -25093071,PMC4108869,10.1186/2041-1480-5-S1-S2,Statistical algorithms for ontology-based annotation of scientific literature,"['Chakrabarti C', 'Jones TB', 'Luger GF', 'Xu JF', 'Turner MD', 'Laird AR', 'Turner JA']",2014,3,17,J Biomed Semantics,5,Suppl 1 Proceedings of the Bio-Ontologies Spec Interest G,S2,"BACKGROUND: Ontologies encode relationships within a domain in robust data structures that can be used to annotate data objects, including scientific papers, in ways that ease tasks such as search and meta-analysis. However, the annotation process requires significant time and effort when performed by humans. Text mining algorithms can facilitate this process, but they render an analysis mainly based upon keyword, synonym and semantic matching. They do not leverage information embedded in an ontology's structure. METHODS: We present a probabilistic framework that facilitates the automatic annotation of literature by indirectly modeling the restrictions among the different classes in the ontology. Our research focuses on annotating human functional neuroimaging literature within the Cognitive Paradigm Ontology (CogPO). We use an approach that combines the stochastic simplicity of naive Bayes with the formal transparency of decision trees. Our data structure is easily modifiable to reflect changing domain knowledge. RESULTS: We compare our results across naive Bayes, Bayesian Decision Trees, and Constrained Decision Tree classifiers that keep a human expert in the loop, in terms of the quality measure of the F1-mirco score. CONCLUSIONS: Unlike traditional text mining algorithms, our framework can model the knowledge encoded by the dependencies in an ontology, albeit indirectly. We successfully exploit the fact that CogPO has explicitly stated restrictions, and implicit dependencies in the form of patterns in the expert curated annotations." -25100166,PMC4545589,10.1001/jamapsychiatry.2014.660,Developmental meta-analyses of the functional neural correlates of bipolar disorder,"['Wegbreit E', 'Cushman GK', 'Puzia ME', 'Weissman AB', 'Kim KL', 'Laird AR', 'Dickstein DP']",2014,8,17,JAMA Psychiatry,71,8,926-35,"IMPORTANCE: Bipolar disorder (BD) is a debilitating mental illness associated with high costs to diagnosed individuals and society. Within the past 2 decades, increasing numbers of children and adolescents have been diagnosed as having BD. While functional magnetic resonance imaging (fMRI) studies have begun to investigate the neural mechanisms underlying BD, few have directly compared differences in youths with BD and adults with BD (hereafter BD-youths and BD-adults, respectively). OBJECTIVE: To test the hypothesis that BD-youths (<18 years old) would show greater convergence of amygdala hyperactivation and prefrontal cortical hypoactivation vs BD-adults. DATA SOURCES: PubMed and PsycINFO databases were searched on July 17, 2013, for original, task-related coordinate-based fMRI articles. STUDY SELECTION: In total, 21 pediatric studies, 73 adult studies, and 2 studies containing distinct pediatric and adult groups within the same study met inclusion criteria for our ALE analyses. DATA EXTRACTION AND SYNTHESIS: Coordinates of significant between-group differences were extracted from each published study. Recent improvements in GingerALE software were used to perform direct comparisons of pediatric and adult fMRI findings. We conducted activation likelihood estimation (ALE) meta-analyses directly comparing the voxelwise convergence of fMRI findings in BD-youths vs BD-adults, both relative to healthy control (HC) participants. RESULTS: Analyses of emotional face recognition fMRI studies showed significantly greater convergence of amygdala hyperactivation among BD-youths than BD-adults. More broadly, analyses of fMRI studies using emotional stimuli showed significantly greater convergence of hyperactivation among BD-youths than BD-adults in the inferior frontal gyrus and precuneus. In contrast, analyses of fMRI studies using nonemotional cognitive tasks and analyses aggregating emotional and nonemotional tasks showed significantly greater convergence of hypoactivation among BD-youths than BD-adults in the anterior cingulate cortex. CONCLUSIONS AND RELEVANCE: Our data suggest that amygdala, prefrontal, and visual system hyperactivation is important in the emotional dysfunction present in BD-youths, as well as that anterior cingulate cortex hypoactivation is relevant to the cognitive deficits in BD-youths. Future studies are required to determine if the developmental fMRI differences between BD-youths and BD-adults identified by our ALE meta-analyses are useful as brain-based diagnostic or treatment markers of BD, including either longitudinal neuroimaging studies of BD-youths as they become adults or cross-sectional imaging studies directly comparing BD-youths with BD-adults." -25331597,PMC4677979,10.1093/cercor/bhu250,Functional Segregation of the Human Dorsomedial Prefrontal Cortex,"['Eickhoff SB', 'Laird AR', 'Fox PT', 'Bzdok D', 'Hensel L']",2016,1,17,Cereb Cortex,26,1,304-21,"The human dorsomedial prefrontal cortex (dmPFC) has been implicated in various complex cognitive processes, including social cognition. To unravel its functional organization, we assessed the dmPFC's regional heterogeneity, connectivity patterns, and functional profiles. First, the heterogeneity of a dmPFC seed, engaged during social processing, was investigated by assessing local differences in whole-brain coactivation profiles. Second, functional connectivity of the ensuing dmPFC clusters was compared by task-constrained meta-analytic coactivation mapping and task-unconstrained resting-state correlations. Third, dmPFC clusters were functionally profiled by forward/reverse inference. The dmPFC seed was thus segregated into 4 clusters (rostroventral, rostrodorsal, caudal-right, and caudal-left). Both rostral clusters were connected to the amygdala and hippocampus and associated with memory and social cognitive tasks in functional decoding. The rostroventral cluster exhibited strongest connectivity to the default mode network. Unlike the rostral segregation, the caudal dmPFC was divided by hemispheres. The caudal-right cluster was strongly connected to a frontoparietal network (dorsal attention network), whereas the caudal-left cluster was strongly connected to the anterior midcingulate cortex and bilateral anterior insula (salience network). In conclusion, we demonstrate that a dmPFC seed reflecting social processing can be divided into 4 separate functional modules that contribute to distinct facets of advanced human cognition." +25032500,PMC4782802,10.1146/annurev-neuro-062012-170320,Meta-analysis in human neuroimaging: computational modeling of large-scale databases,"['Fox PT', 'Lancaster JL', 'Laird AR', 'Eickhoff SB']",2014,6,8,Annu Rev Neurosci,37,,409-34,"Spatial normalization--applying standardized coordinates as anatomical addresses within a reference space--was introduced to human neuroimaging research nearly 30 years ago. Over these three decades, an impressive series of methodological advances have adopted, extended, and popularized this standard. Collectively, this work has generated a methodologically coherent literature of unprecedented rigor, size, and scope. Large-scale online databases have compiled these observations and their associated meta-data, stimulating the development of meta-analytic methods to exploit this expanding corpus. Coordinate-based meta-analytic methods have emerged and evolved in rigor and utility. Early methods computed cross-study consensus, in a manner roughly comparable to traditional (nonimaging) meta-analysis. Recent advances now compute coactivation-based connectivity, connectivity-based functional parcellation, and complex network models powered from data sets representing tens of thousands of subjects. Meta-analyses of human neuroimaging data in large-scale databases now stand at the forefront of computational neurobiology." +25042764,PMC4157091,10.1016/j.biopsycho.2014.06.008,Gender differences in working memory networks: a BrainMap meta-analysis,"['Hill AC', 'Laird AR', 'Robinson JL']",2014,10,8,Biol Psychol,102,,18-29,"Gender differences in psychological processes have been of great interest in a variety of fields. While the majority of research in this area has focused on specific differences in relation to test performance, this study sought to determine the underlying neurofunctional differences observed during working memory, a pivotal cognitive process shown to be predictive of academic achievement and intelligence. Using the BrainMap database, we performed a meta-analysis and applied activation likelihood estimation to our search set. Our results demonstrate consistent working memory networks across genders, but also provide evidence for gender-specific networks whereby females consistently activate more limbic (e.g., amygdala and hippocampus) and prefrontal structures (e.g., right inferior frontal gyrus), and males activate a distributed network inclusive of more parietal regions. These data provide a framework for future investigations using functional or effective connectivity methods to elucidate the underpinnings of gender differences in neural network recruitment during working memory tasks." +25093071,PMC4108869,10.1186/2041-1480-5-S1-S2,Statistical algorithms for ontology-based annotation of scientific literature,"['Chakrabarti C', 'Jones TB', 'Luger GF', 'Xu JF', 'Turner MD', 'Laird AR', 'Turner JA']",2014,6,8,J Biomed Semantics,5,Suppl 1 Proceedings of the Bio-Ontologies Spec Interest G,S2,"BACKGROUND: Ontologies encode relationships within a domain in robust data structures that can be used to annotate data objects, including scientific papers, in ways that ease tasks such as search and meta-analysis. However, the annotation process requires significant time and effort when performed by humans. Text mining algorithms can facilitate this process, but they render an analysis mainly based upon keyword, synonym and semantic matching. They do not leverage information embedded in an ontology's structure. METHODS: We present a probabilistic framework that facilitates the automatic annotation of literature by indirectly modeling the restrictions among the different classes in the ontology. Our research focuses on annotating human functional neuroimaging literature within the Cognitive Paradigm Ontology (CogPO). We use an approach that combines the stochastic simplicity of naive Bayes with the formal transparency of decision trees. Our data structure is easily modifiable to reflect changing domain knowledge. RESULTS: We compare our results across naive Bayes, Bayesian Decision Trees, and Constrained Decision Tree classifiers that keep a human expert in the loop, in terms of the quality measure of the F1-mirco score. CONCLUSIONS: Unlike traditional text mining algorithms, our framework can model the knowledge encoded by the dependencies in an ontology, albeit indirectly. We successfully exploit the fact that CogPO has explicitly stated restrictions, and implicit dependencies in the form of patterns in the expert curated annotations." +25100166,PMC4545589,10.1001/jamapsychiatry.2014.660,Developmental meta-analyses of the functional neural correlates of bipolar disorder,"['Wegbreit E', 'Cushman GK', 'Puzia ME', 'Weissman AB', 'Kim KL', 'Laird AR', 'Dickstein DP']",2014,8,8,JAMA Psychiatry,71,8,926-35,"IMPORTANCE: Bipolar disorder (BD) is a debilitating mental illness associated with high costs to diagnosed individuals and society. Within the past 2 decades, increasing numbers of children and adolescents have been diagnosed as having BD. While functional magnetic resonance imaging (fMRI) studies have begun to investigate the neural mechanisms underlying BD, few have directly compared differences in youths with BD and adults with BD (hereafter BD-youths and BD-adults, respectively). OBJECTIVE: To test the hypothesis that BD-youths (<18 years old) would show greater convergence of amygdala hyperactivation and prefrontal cortical hypoactivation vs BD-adults. DATA SOURCES: PubMed and PsycINFO databases were searched on July 17, 2013, for original, task-related coordinate-based fMRI articles. STUDY SELECTION: In total, 21 pediatric studies, 73 adult studies, and 2 studies containing distinct pediatric and adult groups within the same study met inclusion criteria for our ALE analyses. DATA EXTRACTION AND SYNTHESIS: Coordinates of significant between-group differences were extracted from each published study. Recent improvements in GingerALE software were used to perform direct comparisons of pediatric and adult fMRI findings. We conducted activation likelihood estimation (ALE) meta-analyses directly comparing the voxelwise convergence of fMRI findings in BD-youths vs BD-adults, both relative to healthy control (HC) participants. RESULTS: Analyses of emotional face recognition fMRI studies showed significantly greater convergence of amygdala hyperactivation among BD-youths than BD-adults. More broadly, analyses of fMRI studies using emotional stimuli showed significantly greater convergence of hyperactivation among BD-youths than BD-adults in the inferior frontal gyrus and precuneus. In contrast, analyses of fMRI studies using nonemotional cognitive tasks and analyses aggregating emotional and nonemotional tasks showed significantly greater convergence of hypoactivation among BD-youths than BD-adults in the anterior cingulate cortex. CONCLUSIONS AND RELEVANCE: Our data suggest that amygdala, prefrontal, and visual system hyperactivation is important in the emotional dysfunction present in BD-youths, as well as that anterior cingulate cortex hypoactivation is relevant to the cognitive deficits in BD-youths. Future studies are required to determine if the developmental fMRI differences between BD-youths and BD-adults identified by our ALE meta-analyses are useful as brain-based diagnostic or treatment markers of BD, including either longitudinal neuroimaging studies of BD-youths as they become adults or cross-sectional imaging studies directly comparing BD-youths with BD-adults." +25331597,PMC4677979,10.1093/cercor/bhu250,Functional Segregation of the Human Dorsomedial Prefrontal Cortex,"['Eickhoff SB', 'Laird AR', 'Fox PT', 'Bzdok D', 'Hensel L']",2016,1,8,Cereb Cortex,26,1,304-21,"The human dorsomedial prefrontal cortex (dmPFC) has been implicated in various complex cognitive processes, including social cognition. To unravel its functional organization, we assessed the dmPFC's regional heterogeneity, connectivity patterns, and functional profiles. First, the heterogeneity of a dmPFC seed, engaged during social processing, was investigated by assessing local differences in whole-brain coactivation profiles. Second, functional connectivity of the ensuing dmPFC clusters was compared by task-constrained meta-analytic coactivation mapping and task-unconstrained resting-state correlations. Third, dmPFC clusters were functionally profiled by forward/reverse inference. The dmPFC seed was thus segregated into 4 clusters (rostroventral, rostrodorsal, caudal-right, and caudal-left). Both rostral clusters were connected to the amygdala and hippocampus and associated with memory and social cognitive tasks in functional decoding. The rostroventral cluster exhibited strongest connectivity to the default mode network. Unlike the rostral segregation, the caudal dmPFC was divided by hemispheres. The caudal-right cluster was strongly connected to a frontoparietal network (dorsal attention network), whereas the caudal-left cluster was strongly connected to the anterior midcingulate cortex and bilateral anterior insula (salience network). In conclusion, we demonstrate that a dmPFC seed reflecting social processing can be divided into 4 separate functional modules that contribute to distinct facets of advanced human cognition." 25462801,PMC4780672,10.1016/j.neuroimage.2014.11.009,Subspecialization in the human posterior medial cortex,"['Bzdok D', 'Heeger A', 'Langner R', 'Laird AR', 'Fox PT', 'Palomero-Gallagher N', 'Vogt BA', 'Zilles K', 'Eickhoff SB']",2015,2,1,Neuroimage,106,,55-71,"The posterior medial cortex (PMC) is particularly poorly understood. Its neural activity changes have been related to highly disparate mental processes. We therefore investigated PMC properties with a data-driven exploratory approach. First, we subdivided the PMC by whole-brain coactivation profiles. Second, functional connectivity of the ensuing PMC regions was compared by task-constrained meta-analytic coactivation mapping (MACM) and task-unconstrained resting-state correlations (RSFC). Third, PMC regions were functionally described by forward/reverse functional inference. A precuneal cluster was mostly connected to the intraparietal sulcus, frontal eye fields, and right temporo-parietal junction; associated with attention and motor tasks. A ventral posterior cingulate cortex (PCC) cluster was mostly connected to the ventromedial prefrontal cortex and middle left inferior parietal cortex (IPC); associated with facial appraisal and language tasks. A dorsal PCC cluster was mostly connected to the dorsomedial prefrontal cortex, anterior/posterior IPC, posterior midcingulate cortex, and left dorsolateral prefrontal cortex; associated with delay discounting. A cluster in the retrosplenial cortex was mostly connected to the anterior thalamus and hippocampus. Furthermore, all PMC clusters were congruently coupled with the default mode network according to task-unconstrained but not task-constrained connectivity. We thus identified distinct regions in the PMC and characterized their neural networks and functional implications." 25662104,PMC4494985,10.1016/j.biopsych.2014.12.021,Neurobiological impact of nicotinic acetylcholine receptor agonists: an activation likelihood estimation meta-analysis of pharmacologic neuroimaging studies,"['Sutherland MT', 'Ray KL', 'Riedel MC', 'Yanes JA', 'Stein EA', 'Laird AR']",2015,11,15,Biol Psychiatry,78,10,711-20,"BACKGROUND: Nicotinic acetylcholine receptor (nAChR) agonists augment cognition among cigarette smokers and nonsmokers, yet the systems-level neurobiological mechanisms underlying such improvements are not fully understood. Aggregating neuroimaging results regarding nAChR agonists provides a means to identify common functional brain changes that may be related to procognitive drug effects. METHODS: We conducted a meta-analysis of pharmacologic neuroimaging studies within the activation likelihood estimation framework. We identified published studies contrasting a nAChR drug condition versus a baseline and coded each contrast by activity change direction (decrease or increase), participant characteristics (smokers or nonsmokers), and drug manipulation employed (pharmacologic administration or cigarette smoking). RESULTS: When considering all studies, nAChR agonist administration was associated with activity decreases in multiple regions, including the ventromedial prefrontal cortex (vmPFC), posterior cingulate cortex (PCC), parahippocampus, insula, and the parietal and precentral cortices. Conversely, activity increases were observed in lateral frontoparietal cortices, the anterior cingulate cortex, thalamus, and cuneus. Exploratory analyses indicated that both smokers and nonsmokers showed activity decreases in the vmPFC and PCC, and increases in lateral frontoparietal regions. Among smokers, both pharmacologic administration and cigarette smoking were associated with activity decreases in the vmPFC, PCC, and insula and increases in the lateral PFC, dorsal anterior cingulate cortex, thalamus, and cuneus. CONCLUSIONS: These results provide support for the systems-level perspective that nAChR agonists suppress activity in default-mode network regions and enhance activity in executive control network regions in addition to reducing activation of some task-related regions. We speculate these are potential mechanisms by which nAChR agonists enhance cognition." 25662104,PMC4494985,10.1016/j.biopsych.2014.12.021,Neurobiological impact of nicotinic acetylcholine receptor agonists: an activation likelihood estimation meta-analysis of pharmacologic neuroimaging studies,"['Sutherland MT', 'Ray KL', 'Riedel MC', 'Yanes JA', 'Stein EA', 'Laird AR']",2015,11,15,Biol Psychiatry,78,10,711-20,"BACKGROUND: Nicotinic acetylcholine receptor (nAChR) agonists augment cognition among cigarette smokers and nonsmokers, yet the systems-level neurobiological mechanisms underlying such improvements are not fully understood. Aggregating neuroimaging results regarding nAChR agonists provides a means to identify common functional brain changes that may be related to procognitive drug effects. METHODS: We conducted a meta-analysis of pharmacologic neuroimaging studies within the activation likelihood estimation framework. We identified published studies contrasting a nAChR drug condition versus a baseline and coded each contrast by activity change direction (decrease or increase), participant characteristics (smokers or nonsmokers), and drug manipulation employed (pharmacologic administration or cigarette smoking). RESULTS: When considering all studies, nAChR agonist administration was associated with activity decreases in multiple regions, including the ventromedial prefrontal cortex (vmPFC), posterior cingulate cortex (PCC), parahippocampus, insula, and the parietal and precentral cortices. Conversely, activity increases were observed in lateral frontoparietal cortices, the anterior cingulate cortex, thalamus, and cuneus. Exploratory analyses indicated that both smokers and nonsmokers showed activity decreases in the vmPFC and PCC, and increases in lateral frontoparietal regions. Among smokers, both pharmacologic administration and cigarette smoking were associated with activity decreases in the vmPFC, PCC, and insula and increases in the lateral PFC, dorsal anterior cingulate cortex, thalamus, and cuneus. CONCLUSIONS: These results provide support for the systems-level perspective that nAChR agonists suppress activity in default-mode network regions and enhance activity in executive control network regions in addition to reducing activation of some task-related regions. We speculate these are potential mechanisms by which nAChR agonists enhance cognition." -25692068,PMC4321681,10.1155/2015/783106,Functional activation and effective connectivity differences in adolescent marijuana users performing a simulated gambling task,"['Acheson A', 'Ray KL', 'Hines CS', 'Li K', 'Dawes MA', 'Mathias CW', 'Dougherty DM', 'Laird AR']",2015,3,17,J Addict,2015,,783106,"Background. Adolescent marijuana use is associated with structural and functional differences in forebrain regions while performing memory and attention tasks. In the present study, we investigated neural processing in adolescent marijuana users experiencing rewards and losses. Fourteen adolescents with frequent marijuana use (>5 uses per week) and 14 nonuser controls performed a computer task where they were required to guess the outcome of a simulated coin flip while undergoing magnetic resonance imaging. Results. Across all participants, ""Wins"" and ""Losses"" were associated with activations including cingulate, middle frontal, superior frontal, and inferior frontal gyri and declive activations. Relative to controls, users had greater activity in the middle and inferior frontal gyri, caudate, and claustrum during ""Wins"" and greater activity in the anterior and posterior cingulate, middle frontal gyrus, insula, claustrum, and declive during ""Losses."" Effective connectivity analyses revealed similar overall network interactions among these regions for users and controls during both ""Wins"" and ""Losses."" However, users and controls had significantly different causal interactions for 10 out of 28 individual paths during the ""Losses"" condition. Conclusions. Collectively, these results indicate adolescent marijuana users have enhanced neural responses to simulated monetary rewards and losses and relatively subtle differences in effective connectivity." -25733379,PMC4777354,10.1002/hbm.22777,Connectivity and functional profiling of abnormal brain structures in pedophilia,"['Poeppl TB', 'Eickhoff SB', 'Fox PT', 'Laird AR', 'Rupprecht R', 'Langguth B', 'Bzdok D']",2015,6,17,Hum Brain Mapp,36,6,2374-86,"Despite its 0.5-1% lifetime prevalence in men and its general societal relevance, neuroimaging investigations in pedophilia are scarce. Preliminary findings indicate abnormal brain structure and function. However, no study has yet linked structural alterations in pedophiles to both connectional and functional properties of the aberrant hotspots. The relationship between morphological alterations and brain function in pedophilia as well as their contribution to its psychopathology thus remain unclear. First, we assessed bimodal connectivity of structurally altered candidate regions using meta-analytic connectivity modeling (MACM) and resting-state correlations employing openly accessible data. We compared the ensuing connectivity maps to the activation likelihood estimation (ALE) maps of a recent quantitative meta-analysis of brain activity during processing of sexual stimuli. Second, we functionally characterized the structurally altered regions employing meta-data of a large-scale neuroimaging database. Candidate regions were functionally connected to key areas for processing of sexual stimuli. Moreover, we found that the functional role of structurally altered brain regions in pedophilia relates to nonsexual emotional as well as neurocognitive and executive functions, previously reported to be impaired in pedophiles. Our results suggest that structural brain alterations affect neural networks for sexual processing by way of disrupted functional connectivity, which may entail abnormal sexual arousal patterns. The findings moreover indicate that structural alterations account for common affective and neurocognitive impairments in pedophilia. The present multimodal integration of brain structure and function analyses links sexual and nonsexual psychopathology in pedophilia." -25742873,PMC4839527,10.1038/npp.2015.54,Reward Anticipation Is Differentially Modulated by Varenicline and Nicotine in Smokers,"['Fedota JR', 'Sutherland MT', 'Salmeron BJ', 'Ross TJ', 'Hong LE', 'Stein EA']",2015,7,17,Neuropsychopharmacology,40,8,2038-46,"Recidivism rates for cigarette smokers following treatment often exceed 80%. Varenicline is the most efficacious pharmacotherapy currently available with cessation rates of 25-35% following a year of treatment. Although the in vivo binding properties are well known, varenicline's neurobiological mechanisms of action are still poorly understood. Varenicline acts as a nicotinic receptor partial agonist or antagonist depending on the presence or absence of nicotine and has been implicated in the reduction of reward signaling more broadly. The current study probed anticipatory reward processing using a revised monetary incentive delay task during fMRI in cohorts of smokers and non-smokers who completed a two-drug, placebo-controlled, double-blind crossover study. All participants underwent ~17 days of order-balanced varenicline and placebo pill administration and were scanned under each condition wearing a transdermal nicotine or placebo patch. Consistent with nicotine's ability to enhance the rewarding properties of nondrug stimuli, acute nicotine administration enhanced activation in response to reward-predicting monetary cues in both smokers and non-smokers. In contrast, varenicline reduced gain magnitude processing, but did so only in smokers. These results suggest that varenicline's downregulation of anticipatory reward processing in smokers, in addition to its previously demonstrated reduction in the negative affect associated with withdrawal, independently and additively alter distinct brain circuits. These effects likely contribute to varenicline's efficacy as a pharmacotherapy for smoking cessation." -25749860,PMC5558201,10.1007/s00429-015-1022-y,"Modeling the effective connectivity of the visual network in healthy and photosensitive, epileptic baboons","['Akos Szabo C', 'Salinas FS', 'Li K', 'Franklin C', 'Leland MM', 'Fox PT', 'Laird AR', 'Narayana S']",2016,5,17,Brain Struct Funct,221,4,2023-33,"The baboon provides a model of photosensitive, generalized epilepsy. This study compares cerebral blood flow responses during intermittent light stimulation (ILS) between photosensitive (PS) and healthy control (CTL) baboons using H 2 (15) O-PET. We examined effective connectivity associated with visual stimulation in both groups using structural equation modeling (SEM). Eight PS and six CTL baboons, matched for age, gender and weight, were classified on the basis of scalp EEG findings performed during the neuroimaging studies. Five H 2 (15) O-PET studies were acquired alternating between resting and activation (ILS at 25 Hz) scans. PET images were acquired in 3D mode and co-registered with MRI. SEM demonstrated differences in neural connectivity between PS and CTL groups during ILS that were not previously identified using traditional activation analyses. First-level pathways consisted of similar posterior-to-anterior projections in both groups. While second-level pathways were mainly lateralized to the left hemisphere in the CTL group, they consisted of bilateral anterior-to-posterior projections in the PS baboons. Third- and fourth-level pathways were only evident in PS baboons. This is the first functional neuroimaging study used to model the photoparoxysmal response (PPR) using a primate model of photosensitive, generalized epilepsy. Evidence of increased interhemispheric connectivity and bidirectional feedback loops in the PS baboons represents electrophysiological synchronization associated with the generation of epileptic discharges. PS baboons demonstrated decreased model stability compared to controls, which may be attributed to greater variability in the driving response or PPRs, or to the influence of regions not included in the model." -25844318,PMC4375786,10.1016/j.nicl.2015.02.018,Functional connectivity modeling of consistent cortico-striatal degeneration in Huntington's disease,"['Dogan I', 'Eickhoff CR', 'Fox PT', 'Laird AR', 'Schulz JB', 'Eickhoff SB', 'Reetz K']",2015,3,17,Neuroimage Clin,7,,640-52,"Huntington's disease (HD) is a progressive neurodegenerative disorder characterized by a complex neuropsychiatric phenotype. In a recent meta-analysis we identified core regions of consistent neurodegeneration in premanifest HD in the striatum and middle occipital gyrus (MOG). For early manifest HD convergent evidence of atrophy was most prominent in the striatum, motor cortex (M1) and inferior frontal junction (IFJ). The aim of the present study was to functionally characterize this topography of brain atrophy and to investigate differential connectivity patterns formed by consistent cortico-striatal atrophy regions in HD. Using areas of striatal and cortical atrophy at different disease stages as seeds, we performed task-free resting-state and task-based meta-analytic connectivity modeling (MACM). MACM utilizes the large data source of the BrainMap database and identifies significant areas of above-chance co-activation with the seed-region via the activation-likelihood-estimation approach. In order to delineate functional networks formed by cortical as well as striatal atrophy regions we computed the conjunction between the co-activation profiles of striatal and cortical seeds in the premanifest and manifest stages of HD, respectively. Functional characterization of the seeds was obtained using the behavioral meta-data of BrainMap. Cortico-striatal atrophy seeds of the premanifest stage of HD showed common co-activation with a rather cognitive network including the striatum, anterior insula, lateral prefrontal, premotor, supplementary motor and parietal regions. A similar but more pronounced co-activation pattern, additionally including the medial prefrontal cortex and thalamic nuclei was found with striatal and IFJ seeds at the manifest HD stage. The striatum and M1 were functionally connected mainly to premotor and sensorimotor areas, posterior insula, putamen and thalamus. Behavioral characterization of the seeds confirmed that experiments activating the MOG or IFJ in conjunction with the striatum were associated with cognitive functions, while the network formed by M1 and the striatum was driven by motor-related tasks. Thus, based on morphological changes in HD, we identified functionally distinct cortico-striatal networks resembling a cognitive and motor loop, which may be prone to early disruptions in different stages of the disease and underlie HD-related cognitive and motor symptom profiles. Our findings provide an important link between morphometrically defined seed-regions and corresponding functional circuits highlighting the functional and ensuing clinical relevance of structural damage in HD." -25982222,PMC4791192,10.1007/s00429-015-1060-5,Multimodal connectivity mapping of the human left anterior and posterior lateral prefrontal cortex,"['Reid AT', 'Bzdok D', 'Langner R', 'Fox PT', 'Laird AR', 'Amunts K', 'Eickhoff SB', 'Eickhoff CR']",2016,6,17,Brain Struct Funct,221,5,2589-605,"Working memory is essential for many of our distinctly human abilities, including reasoning, problem solving, and planning. Research spanning many decades has helped to refine our understanding of this high-level function as comprising several hierarchically organized components, some which maintain information in the conscious mind, and others which manipulate and reorganize this information in useful ways. In the neocortex, these processes are likely implemented by a distributed frontoparietal network, with more posterior regions serving to maintain volatile information, and more anterior regions subserving the manipulation of this information. Recent meta-analytic findings have identified the anterior lateral prefrontal cortex, in particular, as being generally engaged by working memory tasks, while the posterior lateral prefrontal cortex was more strongly associated with the cognitive load required by these tasks. These findings suggest specific roles for these regions in the cognitive control processes underlying working memory. To further characterize these regions, we applied three distinct seed-based methods for determining cortical connectivity. Specifically, we employed meta-analytic connectivity mapping across task-based fMRI experiments, resting-state BOLD correlations, and VBM-based structural covariance. We found a frontoparietal pattern of convergence which strongly resembled the working memory networks identified in previous research. A contrast between anterior and posterior parts of the lateral prefrontal cortex revealed distinct connectivity patterns consistent with the idea of a hierarchical organization of frontoparietal networks. Moreover, we found a distributed network that was anticorrelated with the anterior seed region, which included most of the default mode network and a subcomponent related to social and emotional processing. These findings fit well with the internal attention model of working memory, in which representation of information is processed according to an anteroposterior gradient of abstract-to-concrete representations." +25692068,PMC4321681,10.1155/2015/783106,Functional activation and effective connectivity differences in adolescent marijuana users performing a simulated gambling task,"['Acheson A', 'Ray KL', 'Hines CS', 'Li K', 'Dawes MA', 'Mathias CW', 'Dougherty DM', 'Laird AR']",2015,6,8,J Addict,2015,,783106,"Background. Adolescent marijuana use is associated with structural and functional differences in forebrain regions while performing memory and attention tasks. In the present study, we investigated neural processing in adolescent marijuana users experiencing rewards and losses. Fourteen adolescents with frequent marijuana use (>5 uses per week) and 14 nonuser controls performed a computer task where they were required to guess the outcome of a simulated coin flip while undergoing magnetic resonance imaging. Results. Across all participants, ""Wins"" and ""Losses"" were associated with activations including cingulate, middle frontal, superior frontal, and inferior frontal gyri and declive activations. Relative to controls, users had greater activity in the middle and inferior frontal gyri, caudate, and claustrum during ""Wins"" and greater activity in the anterior and posterior cingulate, middle frontal gyrus, insula, claustrum, and declive during ""Losses."" Effective connectivity analyses revealed similar overall network interactions among these regions for users and controls during both ""Wins"" and ""Losses."" However, users and controls had significantly different causal interactions for 10 out of 28 individual paths during the ""Losses"" condition. Conclusions. Collectively, these results indicate adolescent marijuana users have enhanced neural responses to simulated monetary rewards and losses and relatively subtle differences in effective connectivity." +25733379,PMC4777354,10.1002/hbm.22777,Connectivity and functional profiling of abnormal brain structures in pedophilia,"['Poeppl TB', 'Eickhoff SB', 'Fox PT', 'Laird AR', 'Rupprecht R', 'Langguth B', 'Bzdok D']",2015,6,8,Hum Brain Mapp,36,6,2374-86,"Despite its 0.5-1% lifetime prevalence in men and its general societal relevance, neuroimaging investigations in pedophilia are scarce. Preliminary findings indicate abnormal brain structure and function. However, no study has yet linked structural alterations in pedophiles to both connectional and functional properties of the aberrant hotspots. The relationship between morphological alterations and brain function in pedophilia as well as their contribution to its psychopathology thus remain unclear. First, we assessed bimodal connectivity of structurally altered candidate regions using meta-analytic connectivity modeling (MACM) and resting-state correlations employing openly accessible data. We compared the ensuing connectivity maps to the activation likelihood estimation (ALE) maps of a recent quantitative meta-analysis of brain activity during processing of sexual stimuli. Second, we functionally characterized the structurally altered regions employing meta-data of a large-scale neuroimaging database. Candidate regions were functionally connected to key areas for processing of sexual stimuli. Moreover, we found that the functional role of structurally altered brain regions in pedophilia relates to nonsexual emotional as well as neurocognitive and executive functions, previously reported to be impaired in pedophiles. Our results suggest that structural brain alterations affect neural networks for sexual processing by way of disrupted functional connectivity, which may entail abnormal sexual arousal patterns. The findings moreover indicate that structural alterations account for common affective and neurocognitive impairments in pedophilia. The present multimodal integration of brain structure and function analyses links sexual and nonsexual psychopathology in pedophilia." +25742873,PMC4839527,10.1038/npp.2015.54,Reward Anticipation Is Differentially Modulated by Varenicline and Nicotine in Smokers,"['Fedota JR', 'Sutherland MT', 'Salmeron BJ', 'Ross TJ', 'Hong LE', 'Stein EA']",2015,7,8,Neuropsychopharmacology,40,8,2038-46,"Recidivism rates for cigarette smokers following treatment often exceed 80%. Varenicline is the most efficacious pharmacotherapy currently available with cessation rates of 25-35% following a year of treatment. Although the in vivo binding properties are well known, varenicline's neurobiological mechanisms of action are still poorly understood. Varenicline acts as a nicotinic receptor partial agonist or antagonist depending on the presence or absence of nicotine and has been implicated in the reduction of reward signaling more broadly. The current study probed anticipatory reward processing using a revised monetary incentive delay task during fMRI in cohorts of smokers and non-smokers who completed a two-drug, placebo-controlled, double-blind crossover study. All participants underwent ~17 days of order-balanced varenicline and placebo pill administration and were scanned under each condition wearing a transdermal nicotine or placebo patch. Consistent with nicotine's ability to enhance the rewarding properties of nondrug stimuli, acute nicotine administration enhanced activation in response to reward-predicting monetary cues in both smokers and non-smokers. In contrast, varenicline reduced gain magnitude processing, but did so only in smokers. These results suggest that varenicline's downregulation of anticipatory reward processing in smokers, in addition to its previously demonstrated reduction in the negative affect associated with withdrawal, independently and additively alter distinct brain circuits. These effects likely contribute to varenicline's efficacy as a pharmacotherapy for smoking cessation." +25749860,PMC5558201,10.1007/s00429-015-1022-y,"Modeling the effective connectivity of the visual network in healthy and photosensitive, epileptic baboons","['Akos Szabo C', 'Salinas FS', 'Li K', 'Franklin C', 'Leland MM', 'Fox PT', 'Laird AR', 'Narayana S']",2016,5,8,Brain Struct Funct,221,4,2023-33,"The baboon provides a model of photosensitive, generalized epilepsy. This study compares cerebral blood flow responses during intermittent light stimulation (ILS) between photosensitive (PS) and healthy control (CTL) baboons using H 2 (15) O-PET. We examined effective connectivity associated with visual stimulation in both groups using structural equation modeling (SEM). Eight PS and six CTL baboons, matched for age, gender and weight, were classified on the basis of scalp EEG findings performed during the neuroimaging studies. Five H 2 (15) O-PET studies were acquired alternating between resting and activation (ILS at 25 Hz) scans. PET images were acquired in 3D mode and co-registered with MRI. SEM demonstrated differences in neural connectivity between PS and CTL groups during ILS that were not previously identified using traditional activation analyses. First-level pathways consisted of similar posterior-to-anterior projections in both groups. While second-level pathways were mainly lateralized to the left hemisphere in the CTL group, they consisted of bilateral anterior-to-posterior projections in the PS baboons. Third- and fourth-level pathways were only evident in PS baboons. This is the first functional neuroimaging study used to model the photoparoxysmal response (PPR) using a primate model of photosensitive, generalized epilepsy. Evidence of increased interhemispheric connectivity and bidirectional feedback loops in the PS baboons represents electrophysiological synchronization associated with the generation of epileptic discharges. PS baboons demonstrated decreased model stability compared to controls, which may be attributed to greater variability in the driving response or PPRs, or to the influence of regions not included in the model." +25844318,PMC4375786,10.1016/j.nicl.2015.02.018,Functional connectivity modeling of consistent cortico-striatal degeneration in Huntington's disease,"['Dogan I', 'Eickhoff CR', 'Fox PT', 'Laird AR', 'Schulz JB', 'Eickhoff SB', 'Reetz K']",2015,6,8,Neuroimage Clin,7,,640-52,"Huntington's disease (HD) is a progressive neurodegenerative disorder characterized by a complex neuropsychiatric phenotype. In a recent meta-analysis we identified core regions of consistent neurodegeneration in premanifest HD in the striatum and middle occipital gyrus (MOG). For early manifest HD convergent evidence of atrophy was most prominent in the striatum, motor cortex (M1) and inferior frontal junction (IFJ). The aim of the present study was to functionally characterize this topography of brain atrophy and to investigate differential connectivity patterns formed by consistent cortico-striatal atrophy regions in HD. Using areas of striatal and cortical atrophy at different disease stages as seeds, we performed task-free resting-state and task-based meta-analytic connectivity modeling (MACM). MACM utilizes the large data source of the BrainMap database and identifies significant areas of above-chance co-activation with the seed-region via the activation-likelihood-estimation approach. In order to delineate functional networks formed by cortical as well as striatal atrophy regions we computed the conjunction between the co-activation profiles of striatal and cortical seeds in the premanifest and manifest stages of HD, respectively. Functional characterization of the seeds was obtained using the behavioral meta-data of BrainMap. Cortico-striatal atrophy seeds of the premanifest stage of HD showed common co-activation with a rather cognitive network including the striatum, anterior insula, lateral prefrontal, premotor, supplementary motor and parietal regions. A similar but more pronounced co-activation pattern, additionally including the medial prefrontal cortex and thalamic nuclei was found with striatal and IFJ seeds at the manifest HD stage. The striatum and M1 were functionally connected mainly to premotor and sensorimotor areas, posterior insula, putamen and thalamus. Behavioral characterization of the seeds confirmed that experiments activating the MOG or IFJ in conjunction with the striatum were associated with cognitive functions, while the network formed by M1 and the striatum was driven by motor-related tasks. Thus, based on morphological changes in HD, we identified functionally distinct cortico-striatal networks resembling a cognitive and motor loop, which may be prone to early disruptions in different stages of the disease and underlie HD-related cognitive and motor symptom profiles. Our findings provide an important link between morphometrically defined seed-regions and corresponding functional circuits highlighting the functional and ensuing clinical relevance of structural damage in HD." +25982222,PMC4791192,10.1007/s00429-015-1060-5,Multimodal connectivity mapping of the human left anterior and posterior lateral prefrontal cortex,"['Reid AT', 'Bzdok D', 'Langner R', 'Fox PT', 'Laird AR', 'Amunts K', 'Eickhoff SB', 'Eickhoff CR']",2016,6,8,Brain Struct Funct,221,5,2589-605,"Working memory is essential for many of our distinctly human abilities, including reasoning, problem solving, and planning. Research spanning many decades has helped to refine our understanding of this high-level function as comprising several hierarchically organized components, some which maintain information in the conscious mind, and others which manipulate and reorganize this information in useful ways. In the neocortex, these processes are likely implemented by a distributed frontoparietal network, with more posterior regions serving to maintain volatile information, and more anterior regions subserving the manipulation of this information. Recent meta-analytic findings have identified the anterior lateral prefrontal cortex, in particular, as being generally engaged by working memory tasks, while the posterior lateral prefrontal cortex was more strongly associated with the cognitive load required by these tasks. These findings suggest specific roles for these regions in the cognitive control processes underlying working memory. To further characterize these regions, we applied three distinct seed-based methods for determining cortical connectivity. Specifically, we employed meta-analytic connectivity mapping across task-based fMRI experiments, resting-state BOLD correlations, and VBM-based structural covariance. We found a frontoparietal pattern of convergence which strongly resembled the working memory networks identified in previous research. A contrast between anterior and posterior parts of the lateral prefrontal cortex revealed distinct connectivity patterns consistent with the idea of a hierarchical organization of frontoparietal networks. Moreover, we found a distributed network that was anticorrelated with the anterior seed region, which included most of the default mode network and a subcomponent related to social and emotional processing. These findings fit well with the internal attention model of working memory, in which representation of information is processed according to an anteroposterior gradient of abstract-to-concrete representations." 25998956,PMC4512917,10.1016/j.neuroimage.2015.05.008,Meta-analytic connectivity and behavioral parcellation of the human cerebellum,"['Riedel MC', 'Ray KL', 'Dick AS', 'Sutherland MT', 'Hernandez Z', 'Fox PM', 'Eickhoff SB', 'Fox PT', 'Laird AR']",2015,8,15,Neuroimage,117,,327-42,"The cerebellum historically has been thought to mediate motor and sensory signals between the body and cerebral cortex, yet cerebellar lesions are also associated with altered cognitive behavioral performance. Neuroimaging evidence indicates that the cerebellum contributes to a wide range of cognitive, perceptual, and motor functions. Here, we used the BrainMap database to investigate whole-brainco-activation patterns between cerebellar structures and regions of the cerebral cortex, as well as associations with behavioral tasks. Hierarchical clustering was performed to meta-analytically identify cerebellar structures with similar cortical co-activation, and independently, with similar correlations to specific behavioral tasks. Strong correspondences were observed in these separate but parallel analyses of meta-analytic connectivity and behavioral metadata. We recovered differential zones of cerebellar co-activation that are reflected across the literature. Furthermore, the behaviors and tasks associated with the different cerebellar zones provide insight into the specialized function of the cerebellum, relating to high-order cognition, emotion, perception, interoception, and action. Taken together, these task-basedmeta-analytic results implicate distinct zones of the cerebellum as critically involved in the monitoring and mediation of psychological responses to internal and external stimuli." 25998956,PMC4512917,10.1016/j.neuroimage.2015.05.008,Meta-analytic connectivity and behavioral parcellation of the human cerebellum,"['Riedel MC', 'Ray KL', 'Dick AS', 'Sutherland MT', 'Hernandez Z', 'Fox PM', 'Eickhoff SB', 'Fox PT', 'Laird AR']",2015,8,15,Neuroimage,117,,327-42,"The cerebellum historically has been thought to mediate motor and sensory signals between the body and cerebral cortex, yet cerebellar lesions are also associated with altered cognitive behavioral performance. Neuroimaging evidence indicates that the cerebellum contributes to a wide range of cognitive, perceptual, and motor functions. Here, we used the BrainMap database to investigate whole-brainco-activation patterns between cerebellar structures and regions of the cerebral cortex, as well as associations with behavioral tasks. Hierarchical clustering was performed to meta-analytically identify cerebellar structures with similar cortical co-activation, and independently, with similar correlations to specific behavioral tasks. Strong correspondences were observed in these separate but parallel analyses of meta-analytic connectivity and behavioral metadata. We recovered differential zones of cerebellar co-activation that are reflected across the literature. Furthermore, the behaviors and tasks associated with the different cerebellar zones provide insight into the specialized function of the cerebellum, relating to high-order cognition, emotion, perception, interoception, and action. Taken together, these task-basedmeta-analytic results implicate distinct zones of the cerebellum as critically involved in the monitoring and mediation of psychological responses to internal and external stimuli." 26093327,PMC4564321,10.1016/j.neuroimage.2015.06.044,Neural architecture underlying classification of face perception paradigms,"['Laird AR', 'Riedel MC', 'Sutherland MT', 'Eickhoff SB', 'Ray KL', 'Uecker AM', 'Fox PM', 'Turner JA', 'Fox PT']",2015,10,1,Neuroimage,119,,70-80,"We present a novel strategy for deriving a classification system of functional neuroimaging paradigms that relies on hierarchical clustering of experiments archived in the BrainMap database. The goal of our proof-of-concept application was to examine the underlying neural architecture of the face perception literature from a meta-analytic perspective, as these studies include a wide range of tasks. Task-based results exhibiting similar activation patterns were grouped as similar, while tasks activating different brain networks were classified as functionally distinct. We identified four sub-classes of face tasks: (1) Visuospatial Attention and Visuomotor Coordination to Faces, (2) Perception and Recognition of Faces, (3) Social Processing and Episodic Recall of Faces, and (4) Face Naming and Lexical Retrieval. Interpretation of these sub-classes supports an extension of a well-known model of face perception to include a core system for visual analysis and extended systems for personal information, emotion, and salience processing. Overall, these results demonstrate that a large-scale data mining approach can inform the evolution of theoretical cognitive models by probing the range of behavioral manipulations across experimental tasks." 26093327,PMC4564321,10.1016/j.neuroimage.2015.06.044,Neural architecture underlying classification of face perception paradigms,"['Laird AR', 'Riedel MC', 'Sutherland MT', 'Eickhoff SB', 'Ray KL', 'Uecker AM', 'Fox PM', 'Turner JA', 'Fox PT']",2015,10,1,Neuroimage,119,,70-80,"We present a novel strategy for deriving a classification system of functional neuroimaging paradigms that relies on hierarchical clustering of experiments archived in the BrainMap database. The goal of our proof-of-concept application was to examine the underlying neural architecture of the face perception literature from a meta-analytic perspective, as these studies include a wide range of tasks. Task-based results exhibiting similar activation patterns were grouped as similar, while tasks activating different brain networks were classified as functionally distinct. We identified four sub-classes of face tasks: (1) Visuospatial Attention and Visuomotor Coordination to Faces, (2) Perception and Recognition of Faces, (3) Social Processing and Episodic Recall of Faces, and (4) Face Naming and Lexical Retrieval. Interpretation of these sub-classes supports an extension of a well-known model of face perception to include a core system for visual analysis and extended systems for personal information, emotion, and salience processing. Overall, these results demonstrate that a large-scale data mining approach can inform the evolution of theoretical cognitive models by probing the range of behavioral manipulations across experimental tasks." 26231246,,10.1016/j.neuroimage.2015.07.060,ANIMA: A data-sharing initiative for neuroimaging meta-analyses,"['Reid AT', 'Bzdok D', 'Genon S', 'Langner R', 'Muller VI', 'Eickhoff CR', 'Hoffstaedter F', 'Cieslik EC', 'Fox PT', 'Laird AR', 'Amunts K', 'Caspers S', 'Eickhoff SB']",2016,1,1,Neuroimage,124,Pt B,1245-1253,"Meta-analytic techniques allow cognitive neuroscientists to pool large amounts of data across many individual task-based functional neuroimaging experiments. These methods have been aided by the introduction of online databases such as Brainmap.org or Neurosynth.org, which collate peak activation coordinates obtained from thousands of published studies. Findings from meta-analytic studies typically include brain regions which are consistently activated across studies for specific contrasts, investigating cognitive or clinical hypotheses. These regions can be subsequently used as the basis for seed-based connectivity analysis, or formally compared to neuroimaging data in order to help interpret new findings. To facilitate such approaches, we have developed a new online repository of meta-analytic neuroimaging results, named the Archive of Neuroimaging Meta-analyses (ANIMA). The ANIMA platform consists of an intuitive online interface for querying, downloading, and contributing data from published meta-analytic studies. Additionally, to aid the process of organizing, visualizing, and working with these data, we present an open-source desktop application called Volume Viewer. Volume Viewer allows users to easily arrange imaging data into composite stacks, and save these sessions as individual files, which can also be uploaded to the ANIMA database. The application also allows users to perform basic functions, such as computing conjunctions between images, or extracting regions-of-interest or peak coordinates for further analysis. The introduction of this new resource will enhance the ability of researchers to both share their findings and incorporate existing meta-analytic results into their own research." -26254112,PMC4626376,10.1016/j.neuroimage.2015.07.072,Co-activation based parcellation of the human frontal pole,"['Ray KL', 'Zald DH', 'Bludau S', 'Riedel MC', 'Bzdok D', 'Yanes J', 'Falcone KE', 'Amunts K', 'Fox PT', 'Eickhoff SB', 'Laird AR']",2015,12,17,Neuroimage,123,,200-11,"Historically, the human frontal pole (FP) has been considered as a single architectonic area. Brodmann's area 10 is located in the frontal lobe with known contributions in the execution of various higher order cognitive processes. However, recent cytoarchitectural studies of the FP in humans have shown that this portion of cortex contains two distinct cytoarchitectonic regions. Since architectonic differences are accompanied by differential connectivity and functions, the frontal pole qualifies as a candidate region for exploratory parcellation into functionally discrete sub-regions. We investigated whether this functional heterogeneity is reflected in distinct segregations within cytoarchitectonically defined FP-areas using meta-analytic co-activation based parcellation (CBP). The CBP method examined the co-activation patterns of all voxels within the FP as reported in functional neuroimaging studies archived in the BrainMap database. Voxels within the FP were subsequently clustered into sub-regions based on the similarity of their respective meta-analytically derived co-activation maps. Performing this CBP analysis on the FP via k-means clustering produced a distinct 3-cluster parcellation for each hemisphere corresponding to previously identified cytoarchitectural differences. Post-hoc functional characterization of clusters via BrainMap metadata revealed that lateral regions of the FP mapped to memory and emotion domains, while the dorso- and ventromedial clusters were associated broadly with emotion and social cognition processes. Furthermore, the dorsomedial regions contain an emphasis on theory of mind and affective related paradigms whereas ventromedial regions couple with reward tasks. Results from this study support previous segregations of the FP and provide meta-analytic contributions to the ongoing discussion of elucidating functional architecture within human FP." -26750447,,10.1111/desc.12400,"Functional connectivity of brain regions for self- and other-evaluation in children, adolescents and adults with autism","['Burrows CA', 'Laird AR', 'Uddin LQ']",2016,7,17,Dev Sci,19,4,564-80,"Developing strong ties between oneself and others lays the foundation for developing social competence. Neuroimaging studies have consistently identified specific cortical midline regions activated during evaluative judgments about the self and others. Individuals with autism spectrum disorder (ASD) process self-relevant information differently from their peers, both behaviorally and at the neural level. We compared resting-state functional connectivity (rsFC) of regions involved in self-referential (e.g. medial prefrontal cortex; mPFC) and other-referential (e.g. posterior cingulate cortex; PCC) processing between neurotypical individuals and individuals with ASD in three age cohorts using regions of interest (ROIs) identified through an activation likelihood estimation meta-analysis. Typically developing children demonstrated greater connectivity within the midline self- and other-referential networks compared with age-matched children with ASD. No group differences in rsFC of mPFC or PCC emerged between typically developing adolescents and adolescents with ASD. Neurotypical adults exhibited stronger rsFC of the PCC with orbitofrontal cortex compared with adults with ASD. Developmental differences in functional connectivity between areas underlying self- and other-referential thought may explain altered developmental trajectories in the understanding of self and others in individuals with ASD." -27039344,PMC5103027,10.1016/j.neubiorev.2016.03.026,Structural and functional neural adaptations in obstructive sleep apnea: An activation likelihood estimation meta-analysis,"['Tahmasian M', 'Rosenzweig I', 'Eickhoff SB', 'Sepehry AA', 'Laird AR', 'Fox PT', 'Morrell MJ', 'Khazaie H', 'Eickhoff CR']",2016,6,17,Neurosci Biobehav Rev,65,,142-56,"Obstructive sleep apnea (OSA) is a common multisystem chronic disorder. Functional and structural neuroimaging has been widely applied in patients with OSA, but these studies have often yielded diverse results. The present quantitative meta-analysis aims to identify consistent patterns of abnormal activation and grey matter loss in OSA across studies. We used PubMed to retrieve task/resting-state functional magnetic resonance imaging and voxel-based morphometry studies. Stereotactic data were extracted from fifteen studies, and subsequently tested for convergence using activation likelihood estimation. We found convergent evidence for structural atrophy and functional disturbances in the right basolateral amygdala/hippocampus and the right central insula. Functional characterization of these regions using the BrainMap database suggested associated dysfunction of emotional, sensory, and limbic processes. Assessment of task-based co-activation patterns furthermore indicated that the two regions obtained from the meta-analysis are part of a joint network comprising the anterior insula, posterior-medial frontal cortex and thalamus. Taken together, our findings highlight the role of right amygdala, hippocampus and insula in the abnormal emotional and sensory processing in OSA." -27090056,,10.1002/hbm.23217,Imbalance in subregional connectivity of the right temporoparietal junction in major depression,"['Poeppl TB', 'Muller VI', 'Hoffstaedter F', 'Bzdok D', 'Laird AR', 'Fox PT', 'Langguth B', 'Rupprecht R', 'Sorg C', 'Riedl V', 'Goya-Maldonado R', 'Gruber O', 'Eickhoff SB']",2016,8,17,Hum Brain Mapp,37,8,2931-42,"Major depressive disorder (MDD) involves impairment in cognitive and interpersonal functioning. The right temporoparietal junction (RTPJ) is a key brain region subserving cognitive-attentional and social processes. Yet, findings on the involvement of the RTPJ in the pathophysiology of MDD have so far been controversial. Recent connectivity-based parcellation data revealed a topofunctional dualism within the RTPJ, linking its anterior and posterior part (aRTPJ/pRTPJ) to antagonistic brain networks for attentional and social processing, respectively. Comparing functional resting-state connectivity of the aRTPJ and pRTPJ in 72 MDD patients and 76 well-matched healthy controls, we found a seed (aRTPJ/pRTPJ) x diagnosis (MDD/controls) interaction in functional connectivity for eight regions. Employing meta-data from a large-scale neuroimaging database, functional characterization of these regions exhibiting differentially altered connectivity with the aRTPJ/pRTPJ revealed associations with cognitive (dorsolateral prefrontal cortex, parahippocampus) and behavioral (posterior medial frontal cortex) control, visuospatial processing (dorsal visual cortex), reward (subgenual anterior cingulate cortex, medial orbitofrontal cortex, posterior cingulate cortex), as well as memory retrieval and social cognition (precuneus). These findings suggest that an imbalance in connectivity of subregions, rather than disturbed connectivity of the RTPJ as a whole, characterizes the connectional disruption of the RTPJ in MDD. This imbalance may account for key symptoms of MDD in cognitive, emotional, and social domains. Hum Brain Mapp 37:2931-2942, 2016. (c) 2016 Wiley Periodicals, Inc." +26254112,PMC4626376,10.1016/j.neuroimage.2015.07.072,Co-activation based parcellation of the human frontal pole,"['Ray KL', 'Zald DH', 'Bludau S', 'Riedel MC', 'Bzdok D', 'Yanes J', 'Falcone KE', 'Amunts K', 'Fox PT', 'Eickhoff SB', 'Laird AR']",2015,12,8,Neuroimage,123,,200-11,"Historically, the human frontal pole (FP) has been considered as a single architectonic area. Brodmann's area 10 is located in the frontal lobe with known contributions in the execution of various higher order cognitive processes. However, recent cytoarchitectural studies of the FP in humans have shown that this portion of cortex contains two distinct cytoarchitectonic regions. Since architectonic differences are accompanied by differential connectivity and functions, the frontal pole qualifies as a candidate region for exploratory parcellation into functionally discrete sub-regions. We investigated whether this functional heterogeneity is reflected in distinct segregations within cytoarchitectonically defined FP-areas using meta-analytic co-activation based parcellation (CBP). The CBP method examined the co-activation patterns of all voxels within the FP as reported in functional neuroimaging studies archived in the BrainMap database. Voxels within the FP were subsequently clustered into sub-regions based on the similarity of their respective meta-analytically derived co-activation maps. Performing this CBP analysis on the FP via k-means clustering produced a distinct 3-cluster parcellation for each hemisphere corresponding to previously identified cytoarchitectural differences. Post-hoc functional characterization of clusters via BrainMap metadata revealed that lateral regions of the FP mapped to memory and emotion domains, while the dorso- and ventromedial clusters were associated broadly with emotion and social cognition processes. Furthermore, the dorsomedial regions contain an emphasis on theory of mind and affective related paradigms whereas ventromedial regions couple with reward tasks. Results from this study support previous segregations of the FP and provide meta-analytic contributions to the ongoing discussion of elucidating functional architecture within human FP." +26750447,,10.1111/desc.12400,"Functional connectivity of brain regions for self- and other-evaluation in children, adolescents and adults with autism","['Burrows CA', 'Laird AR', 'Uddin LQ']",2016,7,8,Dev Sci,19,4,564-80,"Developing strong ties between oneself and others lays the foundation for developing social competence. Neuroimaging studies have consistently identified specific cortical midline regions activated during evaluative judgments about the self and others. Individuals with autism spectrum disorder (ASD) process self-relevant information differently from their peers, both behaviorally and at the neural level. We compared resting-state functional connectivity (rsFC) of regions involved in self-referential (e.g. medial prefrontal cortex; mPFC) and other-referential (e.g. posterior cingulate cortex; PCC) processing between neurotypical individuals and individuals with ASD in three age cohorts using regions of interest (ROIs) identified through an activation likelihood estimation meta-analysis. Typically developing children demonstrated greater connectivity within the midline self- and other-referential networks compared with age-matched children with ASD. No group differences in rsFC of mPFC or PCC emerged between typically developing adolescents and adolescents with ASD. Neurotypical adults exhibited stronger rsFC of the PCC with orbitofrontal cortex compared with adults with ASD. Developmental differences in functional connectivity between areas underlying self- and other-referential thought may explain altered developmental trajectories in the understanding of self and others in individuals with ASD." +27039344,PMC5103027,10.1016/j.neubiorev.2016.03.026,Structural and functional neural adaptations in obstructive sleep apnea: An activation likelihood estimation meta-analysis,"['Tahmasian M', 'Rosenzweig I', 'Eickhoff SB', 'Sepehry AA', 'Laird AR', 'Fox PT', 'Morrell MJ', 'Khazaie H', 'Eickhoff CR']",2016,6,8,Neurosci Biobehav Rev,65,,142-56,"Obstructive sleep apnea (OSA) is a common multisystem chronic disorder. Functional and structural neuroimaging has been widely applied in patients with OSA, but these studies have often yielded diverse results. The present quantitative meta-analysis aims to identify consistent patterns of abnormal activation and grey matter loss in OSA across studies. We used PubMed to retrieve task/resting-state functional magnetic resonance imaging and voxel-based morphometry studies. Stereotactic data were extracted from fifteen studies, and subsequently tested for convergence using activation likelihood estimation. We found convergent evidence for structural atrophy and functional disturbances in the right basolateral amygdala/hippocampus and the right central insula. Functional characterization of these regions using the BrainMap database suggested associated dysfunction of emotional, sensory, and limbic processes. Assessment of task-based co-activation patterns furthermore indicated that the two regions obtained from the meta-analysis are part of a joint network comprising the anterior insula, posterior-medial frontal cortex and thalamus. Taken together, our findings highlight the role of right amygdala, hippocampus and insula in the abnormal emotional and sensory processing in OSA." +27090056,,10.1002/hbm.23217,Imbalance in subregional connectivity of the right temporoparietal junction in major depression,"['Poeppl TB', 'Muller VI', 'Hoffstaedter F', 'Bzdok D', 'Laird AR', 'Fox PT', 'Langguth B', 'Rupprecht R', 'Sorg C', 'Riedl V', 'Goya-Maldonado R', 'Gruber O', 'Eickhoff SB']",2016,8,8,Hum Brain Mapp,37,8,2931-42,"Major depressive disorder (MDD) involves impairment in cognitive and interpersonal functioning. The right temporoparietal junction (RTPJ) is a key brain region subserving cognitive-attentional and social processes. Yet, findings on the involvement of the RTPJ in the pathophysiology of MDD have so far been controversial. Recent connectivity-based parcellation data revealed a topofunctional dualism within the RTPJ, linking its anterior and posterior part (aRTPJ/pRTPJ) to antagonistic brain networks for attentional and social processing, respectively. Comparing functional resting-state connectivity of the aRTPJ and pRTPJ in 72 MDD patients and 76 well-matched healthy controls, we found a seed (aRTPJ/pRTPJ) x diagnosis (MDD/controls) interaction in functional connectivity for eight regions. Employing meta-data from a large-scale neuroimaging database, functional characterization of these regions exhibiting differentially altered connectivity with the aRTPJ/pRTPJ revealed associations with cognitive (dorsolateral prefrontal cortex, parahippocampus) and behavioral (posterior medial frontal cortex) control, visuospatial processing (dorsal visual cortex), reward (subgenual anterior cingulate cortex, medial orbitofrontal cortex, posterior cingulate cortex), as well as memory retrieval and social cognition (precuneus). These findings suggest that an imbalance in connectivity of subregions, rather than disturbed connectivity of the RTPJ as a whole, characterizes the connectional disruption of the RTPJ in MDD. This imbalance may account for key symptoms of MDD in cognitive, emotional, and social domains. Hum Brain Mapp 37:2931-2942, 2016. (c) 2016 Wiley Periodicals, Inc." 27179606,PMC4981641,10.1016/j.neuroimage.2016.04.072,"Behavior, sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation","['Eickhoff SB', 'Nichols TE', 'Laird AR', 'Hoffstaedter F', 'Amunts K', 'Fox PT', 'Bzdok D', 'Eickhoff CR']",2016,8,15,Neuroimage,137,,70-85,"Given the increasing number of neuroimaging publications, the automated knowledge extraction on brain-behavior associations by quantitative meta-analyses has become a highly important and rapidly growing field of research. Among several methods to perform coordinate-based neuroimaging meta-analyses, Activation Likelihood Estimation (ALE) has been widely adopted. In this paper, we addressed two pressing questions related to ALE meta-analysis: i) Which thresholding method is most appropriate to perform statistical inference? ii) Which sample size, i.e., number of experiments, is needed to perform robust meta-analyses? We provided quantitative answers to these questions by simulating more than 120,000 meta-analysis datasets using empirical parameters (i.e., number of subjects, number of reported foci, distribution of activation foci) derived from the BrainMap database. This allowed to characterize the behavior of ALE analyses, to derive first power estimates for neuroimaging meta-analyses, and to thus formulate recommendations for future ALE studies. We could show as a first consequence that cluster-level family-wise error (FWE) correction represents the most appropriate method for statistical inference, while voxel-level FWE correction is valid but more conservative. In contrast, uncorrected inference and false-discovery rate correction should be avoided. As a second consequence, researchers should aim to include at least 20 experiments into an ALE meta-analysis to achieve sufficient power for moderate effects. We would like to note, though, that these calculations and recommendations are specific to ALE and may not be extrapolated to other approaches for (neuroimaging) meta-analysis." -27211526,PMC5003685,10.1016/j.neubiorev.2016.05.012,Different involvement of subregions within dorsal premotor and medial frontal cortex for pro- and antisaccades,"['Cieslik EC', 'Seidler I', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2016,9,17,Neurosci Biobehav Rev,68,,256-269,"The antisaccade task has been widely used to investigate cognitive action control. While the general network for saccadic eye movements is well defined, the exact location of eye fields within the frontal cortex strongly varies between studies. It is unknown whether this inconsistency reflects spatial uncertainty or is the result of different involvement of subregions for specific aspects of eye movement control. The aim of the present study was to examine functional differentiations within the frontal cortex by integrating results from neuroimaging studies analyzing pro- and antisaccade behavior using meta-analyses. The results provide evidence for a differential functional specialization of neighboring oculomotor frontal regions, with lateral frontal eye fields (FEF) and supplementary eye field (SEF) more often involved in prosaccades while medial FEF and anterior midcingulate cortex (aMCC) revealed consistent stronger involvement for antisaccades. This dissociation was furthermore mirrored by functional connectivity analyses showing that the lateral FEF and SEF are embedded in a motor output network, while medial FEF and aMCC are integrated in a multiple demand network." -27230218,PMC4961028,10.1093/cercor/bhw157,The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture,"['Fan L', 'Li H', 'Zhuo J', 'Zhang Y', 'Wang J', 'Chen L', 'Yang Z', 'Chu C', 'Xie S', 'Laird AR', 'Fox PT', 'Eickhoff SB', 'Yu C', 'Jiang T']",2016,8,17,Cereb Cortex,26,8,3508-26,"The human brain atlases that allow correlating brain anatomy with psychological and cognitive functions are in transition from ex vivo histology-based printed atlases to digital brain maps providing multimodal in vivo information. Many current human brain atlases cover only specific structures, lack fine-grained parcellations, and fail to provide functionally important connectivity information. Using noninvasive multimodal neuroimaging techniques, we designed a connectivity-based parcellation framework that identifies the subdivisions of the entire human brain, revealing the in vivo connectivity architecture. The resulting human Brainnetome Atlas, with 210 cortical and 36 subcortical subregions, provides a fine-grained, cross-validated atlas and contains information on both anatomical and functional connections. Additionally, we further mapped the delineated structures to mental processes by reference to the BrainMap database. It thus provides an objective and stable starting point from which to explore the complex relationships between structure, connectivity, and function, and eventually improves understanding of how the human brain works. The human Brainnetome Atlas will be made freely available for download at http://atlas.brainnetome.org, so that whole brain parcellations, connections, and functional data will be readily available for researchers to use in their investigations into healthy and pathological states." -27241201,PMC5441272,10.1016/j.neubiorev.2016.02.024,Left inferior parietal lobe engagement in social cognition and language,"['Bzdok D', 'Hartwigsen G', 'Reid A', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2016,9,17,Neurosci Biobehav Rev,68,,319-334,"Social cognition and language are two core features of the human species. Despite distributed recruitment of brain regions in each mental capacity, the left parietal lobe (LPL) represents a zone of topographical convergence. The present study quantitatively summarizes hundreds of neuroimaging studies on social cognition and language. Using connectivity-based parcellation on a meta-analytically defined volume of interest (VOI), regional coactivation patterns within this VOI allowed identifying distinct subregions. Across parcellation solutions, two clusters emerged consistently in rostro-ventral and caudo-ventral aspects of the parietal VOI. Both clusters were functionally significantly associated with social-cognitive and language processing. In particular, the rostro-ventral cluster was associated with lower-level processing facets, while the caudo-ventral cluster was associated with higher-level processing facets in both mental capacities. Contrarily, in the (less stable) dorsal parietal VOI, all clusters reflected computation of general-purpose processes, such as working memory and matching tasks, that are frequently co-recruited by social or language processes. Our results hence favour a rostro-caudal distinction of lower- versus higher-level processes underlying social cognition and language in the left inferior parietal lobe." +27211526,PMC5003685,10.1016/j.neubiorev.2016.05.012,Different involvement of subregions within dorsal premotor and medial frontal cortex for pro- and antisaccades,"['Cieslik EC', 'Seidler I', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2016,9,8,Neurosci Biobehav Rev,68,,256-269,"The antisaccade task has been widely used to investigate cognitive action control. While the general network for saccadic eye movements is well defined, the exact location of eye fields within the frontal cortex strongly varies between studies. It is unknown whether this inconsistency reflects spatial uncertainty or is the result of different involvement of subregions for specific aspects of eye movement control. The aim of the present study was to examine functional differentiations within the frontal cortex by integrating results from neuroimaging studies analyzing pro- and antisaccade behavior using meta-analyses. The results provide evidence for a differential functional specialization of neighboring oculomotor frontal regions, with lateral frontal eye fields (FEF) and supplementary eye field (SEF) more often involved in prosaccades while medial FEF and anterior midcingulate cortex (aMCC) revealed consistent stronger involvement for antisaccades. This dissociation was furthermore mirrored by functional connectivity analyses showing that the lateral FEF and SEF are embedded in a motor output network, while medial FEF and aMCC are integrated in a multiple demand network." +27230218,PMC4961028,10.1093/cercor/bhw157,The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture,"['Fan L', 'Li H', 'Zhuo J', 'Zhang Y', 'Wang J', 'Chen L', 'Yang Z', 'Chu C', 'Xie S', 'Laird AR', 'Fox PT', 'Eickhoff SB', 'Yu C', 'Jiang T']",2016,8,8,Cereb Cortex,26,8,3508-26,"The human brain atlases that allow correlating brain anatomy with psychological and cognitive functions are in transition from ex vivo histology-based printed atlases to digital brain maps providing multimodal in vivo information. Many current human brain atlases cover only specific structures, lack fine-grained parcellations, and fail to provide functionally important connectivity information. Using noninvasive multimodal neuroimaging techniques, we designed a connectivity-based parcellation framework that identifies the subdivisions of the entire human brain, revealing the in vivo connectivity architecture. The resulting human Brainnetome Atlas, with 210 cortical and 36 subcortical subregions, provides a fine-grained, cross-validated atlas and contains information on both anatomical and functional connections. Additionally, we further mapped the delineated structures to mental processes by reference to the BrainMap database. It thus provides an objective and stable starting point from which to explore the complex relationships between structure, connectivity, and function, and eventually improves understanding of how the human brain works. The human Brainnetome Atlas will be made freely available for download at http://atlas.brainnetome.org, so that whole brain parcellations, connections, and functional data will be readily available for researchers to use in their investigations into healthy and pathological states." +27241201,PMC5441272,10.1016/j.neubiorev.2016.02.024,Left inferior parietal lobe engagement in social cognition and language,"['Bzdok D', 'Hartwigsen G', 'Reid A', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2016,9,8,Neurosci Biobehav Rev,68,,319-334,"Social cognition and language are two core features of the human species. Despite distributed recruitment of brain regions in each mental capacity, the left parietal lobe (LPL) represents a zone of topographical convergence. The present study quantitatively summarizes hundreds of neuroimaging studies on social cognition and language. Using connectivity-based parcellation on a meta-analytically defined volume of interest (VOI), regional coactivation patterns within this VOI allowed identifying distinct subregions. Across parcellation solutions, two clusters emerged consistently in rostro-ventral and caudo-ventral aspects of the parietal VOI. Both clusters were functionally significantly associated with social-cognitive and language processing. In particular, the rostro-ventral cluster was associated with lower-level processing facets, while the caudo-ventral cluster was associated with higher-level processing facets in both mental capacities. Contrarily, in the (less stable) dorsal parietal VOI, all clusters reflected computation of general-purpose processes, such as working memory and matching tasks, that are frequently co-recruited by social or language processes. Our results hence favour a rostro-caudal distinction of lower- versus higher-level processes underlying social cognition and language in the left inferior parietal lobe." 27251183,PMC4890474,10.1186/s12993-016-0100-5,Chronic cigarette smoking is linked with structural alterations in brain regions showing acute nicotinic drug-induced functional modulations,"['Sutherland MT', 'Riedel MC', 'Flannery JS', 'Yanes JA', 'Fox PT', 'Stein EA', 'Laird AR']",2016,6,2,Behav Brain Funct,12,1,16,"BACKGROUND: Whereas acute nicotine administration alters brain function which may, in turn, contribute to enhanced attention and performance, chronic cigarette smoking is linked with regional brain atrophy and poorer cognition. However, results from structural magnetic resonance imaging (MRI) studies comparing smokers versus nonsmokers have been inconsistent and measures of gray matter possess limited ability to inform functional relations or behavioral implications. The purpose of this study was to address these interpretational challenges through meta-analytic techniques in the service of clarifying the impact of chronic smoking on gray matter integrity and more fully contextualizing such structural alterations. METHODS: We first conducted a coordinate-based meta-analysis of structural MRI studies to identify consistent structural alterations associated with chronic smoking. Subsequently, we conducted two additional meta-analytic assessments to enhance insight into potential functional and behavioral relations. Specifically, we performed a multimodal meta-analytic assessment to test the structural-functional hypothesis that smoking-related structural alterations overlapped those same regions showing acute nicotinic drug-induced functional modulations. Finally, we employed database driven tools to identify pairs of structurally impacted regions that were also functionally related via meta-analytic connectivity modeling, and then delineated behavioral phenomena associated with such functional interactions via behavioral decoding. RESULTS: Across studies, smoking was associated with convergent structural decreases in the left insula, right cerebellum, parahippocampus, multiple prefrontal cortex (PFC) regions, and the thalamus. Indicating a structural-functional relation, we observed that smoking-related gray matter decreases overlapped with the acute functional effects of nicotinic agonist administration in the left insula, ventromedial PFC, and mediodorsal thalamus. Suggesting structural-behavioral implications, we observed that the left insula's task-based, functional interactions with multiple other structurally impacted regions were linked with pain perception, the right cerebellum's interactions with other regions were associated with overt body movements, interactions between the parahippocampus and thalamus were linked with memory processes, and interactions between medial PFC regions were associated with face processing. CONCLUSIONS: Collectively, these findings emphasize brain regions (e.g., ventromedial PFC, insula, thalamus) critically linked with cigarette smoking, suggest neuroimaging paradigms warranting additional consideration among smokers (e.g., pain processing), and highlight regions in need of further elucidation in addiction (e.g., cerebellum)." 27251183,PMC4890474,10.1186/s12993-016-0100-5,Chronic cigarette smoking is linked with structural alterations in brain regions showing acute nicotinic drug-induced functional modulations,"['Sutherland MT', 'Riedel MC', 'Flannery JS', 'Yanes JA', 'Fox PT', 'Stein EA', 'Laird AR']",2016,6,2,Behav Brain Funct,12,1,16,"BACKGROUND: Whereas acute nicotine administration alters brain function which may, in turn, contribute to enhanced attention and performance, chronic cigarette smoking is linked with regional brain atrophy and poorer cognition. However, results from structural magnetic resonance imaging (MRI) studies comparing smokers versus nonsmokers have been inconsistent and measures of gray matter possess limited ability to inform functional relations or behavioral implications. The purpose of this study was to address these interpretational challenges through meta-analytic techniques in the service of clarifying the impact of chronic smoking on gray matter integrity and more fully contextualizing such structural alterations. METHODS: We first conducted a coordinate-based meta-analysis of structural MRI studies to identify consistent structural alterations associated with chronic smoking. Subsequently, we conducted two additional meta-analytic assessments to enhance insight into potential functional and behavioral relations. Specifically, we performed a multimodal meta-analytic assessment to test the structural-functional hypothesis that smoking-related structural alterations overlapped those same regions showing acute nicotinic drug-induced functional modulations. Finally, we employed database driven tools to identify pairs of structurally impacted regions that were also functionally related via meta-analytic connectivity modeling, and then delineated behavioral phenomena associated with such functional interactions via behavioral decoding. RESULTS: Across studies, smoking was associated with convergent structural decreases in the left insula, right cerebellum, parahippocampus, multiple prefrontal cortex (PFC) regions, and the thalamus. Indicating a structural-functional relation, we observed that smoking-related gray matter decreases overlapped with the acute functional effects of nicotinic agonist administration in the left insula, ventromedial PFC, and mediodorsal thalamus. Suggesting structural-behavioral implications, we observed that the left insula's task-based, functional interactions with multiple other structurally impacted regions were linked with pain perception, the right cerebellum's interactions with other regions were associated with overt body movements, interactions between the parahippocampus and thalamus were linked with memory processes, and interactions between medial PFC regions were associated with face processing. CONCLUSIONS: Collectively, these findings emphasize brain regions (e.g., ventromedial PFC, insula, thalamus) critically linked with cigarette smoking, suggest neuroimaging paradigms warranting additional consideration among smokers (e.g., pain processing), and highlight regions in need of further elucidation in addiction (e.g., cerebellum)." -27339689,PMC5003731,10.1016/j.neubiorev.2016.06.025,A neural circuit encoding sexual preference in humans,"['Poeppl TB', 'Langguth B', 'Rupprecht R', 'Laird AR', 'Eickhoff SB']",2016,9,17,Neurosci Biobehav Rev,68,,530-536,"Sexual preference determines mate choice for reproduction and hence guarantees conservation of species in mammals. Despite this fundamental role in human behavior, current knowledge on its target-specific neurofunctional substrate is based on lesion studies and therefore limited. We used meta-analytic remodeling of neuroimaging data from 364 human subjects with diverse sexual interests during sexual stimulation to quantify neural regions associated with sexual preference manipulations. We found that sexual preference is encoded by four phylogenetically old, subcortical brain structures. More specifically, sexual preference is controlled by the anterior and preoptic area of the hypothalamus, the anterior and mediodorsal thalamus, the septal area, and the perirhinal parahippocampus including the dentate gyrus. In contrast, sexual non-preference is regulated by the substantia innominata. We anticipate the identification of a core neural circuit for sexual preferences to be a starting point for further sophisticated investigations into the neural principles of sexual behavior and particularly of its aberrations." -27372336,PMC5205581,10.1007/s00429-016-1264-3,A seed-based cross-modal comparison of brain connectivity measures,"['Reid AT', 'Hoffstaedter F', 'Gong G', 'Laird AR', 'Fox P', 'Evans AC', 'Amunts K', 'Eickhoff SB']",2017,4,17,Brain Struct Funct,222,3,1131-1151,"Human neuroimaging methods have provided a number of means by which the connectivity structure of the human brain can be inferred. For instance, correlations in blood-oxygen-level-dependent (BOLD) signal time series are commonly used to make inferences about ""functional connectivity."" Correlations across samples in structural morphometric measures, such as voxel-based morphometry (VBM) or cortical thickness (CT), have also been used to estimate connectivity, putatively through mutually trophic effects on connected brain areas. In this study, we have compared seed-based connectivity estimates obtained from four common correlational approaches: resting-state functional connectivity (RS-fMRI), meta-analytic connectivity modeling (MACM), VBM correlations, and CT correlations. We found that the two functional approaches (RS-fMRI and MACM) had the best agreement. While the two structural approaches (CT and VBM) had better-than-random convergence, they were no more similar to each other than to the functional approaches. The degree of correspondence between modalities varied considerably across seed regions, and also depended on the threshold applied to the connectivity distribution. These results demonstrate some degrees of similarity between connectivity inferred from structural and functional covariances, particularly for the most robust functionally connected regions (e.g., the default mode network). However, they also caution that these measures likely capture very different aspects of brain structure and function." -27378909,PMC4905965,10.3389/fnagi.2016.00137,Progressive Bidirectional Age-Related Changes in Default Mode Network Effective Connectivity across Six Decades,"['Li K', 'Laird AR', 'Price LR', 'McKay DR', 'Blangero J', 'Glahn DC', 'Fox PT']",2016,3,17,Front Aging Neurosci,8,,137,"The default mode network (DMN) is a set of regions that is tonically engaged during the resting state and exhibits task-related deactivation that is readily reproducible across a wide range of paradigms and modalities. The DMN has been implicated in numerous disorders of cognition and, in particular, in disorders exhibiting age-related cognitive decline. Despite these observations, investigations of the DMN in normal aging are scant. Here, we used blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) acquired during rest to investigate age-related changes in functional connectivity of the DMN in 120 healthy normal volunteers comprising six, 20-subject, decade cohorts (from 20-29 to 70-79). Structural equation modeling (SEM) was used to assess age-related changes in inter-regional connectivity within the DMN. SEM was applied both using a previously published, meta-analytically derived, node-and-edge model, and using exploratory modeling searching for connections that optimized model fit improvement. Although the two models were highly similar (only 3 of 13 paths differed), the sample demonstrated significantly better fit with the exploratory model. For this reason, the exploratory model was used to assess age-related changes across the decade cohorts. Progressive, highly significant changes in path weights were found in 8 (of 13) paths: four rising, and four falling (most changes were significant by the third or fourth decade). In all cases, rising paths and falling paths projected in pairs onto the same nodes, suggesting compensatory increases associated with age-related decreases. This study demonstrates that age-related changes in DMN physiology (inter-regional connectivity) are bidirectional, progressive, of early onset and part of normal aging." -27511454,PMC5323082,10.1002/hbm.23342,Implementation errors in the GingerALE Software: Description and recommendations,"['Eickhoff SB', 'Laird AR', 'Fox PM', 'Lancaster JL', 'Fox PT']",2017,1,17,Hum Brain Mapp,38,1,7-11,"Neuroscience imaging is a burgeoning, highly sophisticated field the growth of which has been fostered by grant-funded, freely distributed software libraries that perform voxel-wise analyses in anatomically standardized three-dimensional space on multi-subject, whole-brain, primary datasets. Despite the ongoing advances made using these non-commercial computational tools, the replicability of individual studies is an acknowledged limitation. Coordinate-based meta-analysis offers a practical solution to this limitation and, consequently, plays an important role in filtering and consolidating the enormous corpus of functional and structural neuroimaging results reported in the peer-reviewed literature. In both primary data and meta-analytic neuroimaging analyses, correction for multiple comparisons is a complex but critical step for ensuring statistical rigor. Reports of errors in multiple-comparison corrections in primary-data analyses have recently appeared. Here, we report two such errors in GingerALE, a widely used, US National Institutes of Health (NIH)-funded, freely distributed software package for coordinate-based meta-analysis. These errors have given rise to published reports with more liberal statistical inferences than were specified by the authors. The intent of this technical report is threefold. First, we inform authors who used GingerALE of these errors so that they can take appropriate actions including re-analyses and corrective publications. Second, we seek to exemplify and promote an open approach to error management. Third, we discuss the implications of these and similar errors in a scientific environment dependent on third-party software. Hum Brain Mapp 38:7-11, 2017. (c) 2016 Wiley Periodicals, Inc." +27339689,PMC5003731,10.1016/j.neubiorev.2016.06.025,A neural circuit encoding sexual preference in humans,"['Poeppl TB', 'Langguth B', 'Rupprecht R', 'Laird AR', 'Eickhoff SB']",2016,9,8,Neurosci Biobehav Rev,68,,530-536,"Sexual preference determines mate choice for reproduction and hence guarantees conservation of species in mammals. Despite this fundamental role in human behavior, current knowledge on its target-specific neurofunctional substrate is based on lesion studies and therefore limited. We used meta-analytic remodeling of neuroimaging data from 364 human subjects with diverse sexual interests during sexual stimulation to quantify neural regions associated with sexual preference manipulations. We found that sexual preference is encoded by four phylogenetically old, subcortical brain structures. More specifically, sexual preference is controlled by the anterior and preoptic area of the hypothalamus, the anterior and mediodorsal thalamus, the septal area, and the perirhinal parahippocampus including the dentate gyrus. In contrast, sexual non-preference is regulated by the substantia innominata. We anticipate the identification of a core neural circuit for sexual preferences to be a starting point for further sophisticated investigations into the neural principles of sexual behavior and particularly of its aberrations." +27372336,PMC5205581,10.1007/s00429-016-1264-3,A seed-based cross-modal comparison of brain connectivity measures,"['Reid AT', 'Hoffstaedter F', 'Gong G', 'Laird AR', 'Fox P', 'Evans AC', 'Amunts K', 'Eickhoff SB']",2017,4,8,Brain Struct Funct,222,3,1131-1151,"Human neuroimaging methods have provided a number of means by which the connectivity structure of the human brain can be inferred. For instance, correlations in blood-oxygen-level-dependent (BOLD) signal time series are commonly used to make inferences about ""functional connectivity."" Correlations across samples in structural morphometric measures, such as voxel-based morphometry (VBM) or cortical thickness (CT), have also been used to estimate connectivity, putatively through mutually trophic effects on connected brain areas. In this study, we have compared seed-based connectivity estimates obtained from four common correlational approaches: resting-state functional connectivity (RS-fMRI), meta-analytic connectivity modeling (MACM), VBM correlations, and CT correlations. We found that the two functional approaches (RS-fMRI and MACM) had the best agreement. While the two structural approaches (CT and VBM) had better-than-random convergence, they were no more similar to each other than to the functional approaches. The degree of correspondence between modalities varied considerably across seed regions, and also depended on the threshold applied to the connectivity distribution. These results demonstrate some degrees of similarity between connectivity inferred from structural and functional covariances, particularly for the most robust functionally connected regions (e.g., the default mode network). However, they also caution that these measures likely capture very different aspects of brain structure and function." +27378909,PMC4905965,10.3389/fnagi.2016.00137,Progressive Bidirectional Age-Related Changes in Default Mode Network Effective Connectivity across Six Decades,"['Li K', 'Laird AR', 'Price LR', 'McKay DR', 'Blangero J', 'Glahn DC', 'Fox PT']",2016,6,8,Front Aging Neurosci,8,,137,"The default mode network (DMN) is a set of regions that is tonically engaged during the resting state and exhibits task-related deactivation that is readily reproducible across a wide range of paradigms and modalities. The DMN has been implicated in numerous disorders of cognition and, in particular, in disorders exhibiting age-related cognitive decline. Despite these observations, investigations of the DMN in normal aging are scant. Here, we used blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) acquired during rest to investigate age-related changes in functional connectivity of the DMN in 120 healthy normal volunteers comprising six, 20-subject, decade cohorts (from 20-29 to 70-79). Structural equation modeling (SEM) was used to assess age-related changes in inter-regional connectivity within the DMN. SEM was applied both using a previously published, meta-analytically derived, node-and-edge model, and using exploratory modeling searching for connections that optimized model fit improvement. Although the two models were highly similar (only 3 of 13 paths differed), the sample demonstrated significantly better fit with the exploratory model. For this reason, the exploratory model was used to assess age-related changes across the decade cohorts. Progressive, highly significant changes in path weights were found in 8 (of 13) paths: four rising, and four falling (most changes were significant by the third or fourth decade). In all cases, rising paths and falling paths projected in pairs onto the same nodes, suggesting compensatory increases associated with age-related decreases. This study demonstrates that age-related changes in DMN physiology (inter-regional connectivity) are bidirectional, progressive, of early onset and part of normal aging." +27511454,PMC5323082,10.1002/hbm.23342,Implementation errors in the GingerALE Software: Description and recommendations,"['Eickhoff SB', 'Laird AR', 'Fox PM', 'Lancaster JL', 'Fox PT']",2017,1,8,Hum Brain Mapp,38,1,7-11,"Neuroscience imaging is a burgeoning, highly sophisticated field the growth of which has been fostered by grant-funded, freely distributed software libraries that perform voxel-wise analyses in anatomically standardized three-dimensional space on multi-subject, whole-brain, primary datasets. Despite the ongoing advances made using these non-commercial computational tools, the replicability of individual studies is an acknowledged limitation. Coordinate-based meta-analysis offers a practical solution to this limitation and, consequently, plays an important role in filtering and consolidating the enormous corpus of functional and structural neuroimaging results reported in the peer-reviewed literature. In both primary data and meta-analytic neuroimaging analyses, correction for multiple comparisons is a complex but critical step for ensuring statistical rigor. Reports of errors in multiple-comparison corrections in primary-data analyses have recently appeared. Here, we report two such errors in GingerALE, a widely used, US National Institutes of Health (NIH)-funded, freely distributed software package for coordinate-based meta-analysis. These errors have given rise to published reports with more liberal statistical inferences than were specified by the authors. The intent of this technical report is threefold. First, we inform authors who used GingerALE of these errors so that they can take appropriate actions including re-analyses and corrective publications. Second, we seek to exemplify and promote an open approach to error management. Third, we discuss the implications of these and similar errors in a scientific environment dependent on third-party software. Hum Brain Mapp 38:7-11, 2017. (c) 2016 Wiley Periodicals, Inc." 27569542,PMC5108674,10.1016/j.biopsych.2016.06.014,Functional Decoding and Meta-analytic Connectivity Modeling in Adult Attention-Deficit/Hyperactivity Disorder,"['Cortese S', 'Castellanos FX', 'Eickhoff CR', ""D'Acunto G"", 'Masi G', 'Fox PT', 'Laird AR', 'Eickhoff SB']",2016,12,15,Biol Psychiatry,80,12,896-904,"BACKGROUND: Task-based functional magnetic resonance imaging (fMRI) studies of adult attention-deficit/hyperactivity disorder (ADHD) have revealed various ADHD-related dysfunctional brain regions, with heterogeneous findings across studies. Here, we used novel meta-analytic data-driven approaches to characterize the function and connectivity profile of ADHD-related dysfunctional regions consistently detected across studies. METHODS: We first conducted an activation likelihood estimation meta-analysis of 24 task-based fMRI studies in adults with ADHD. Each ADHD-related dysfunctional region resulting from the activation likelihood estimation meta-analysis was then analyzed using functional decoding based on ~7500 fMRI experiments in the BrainMap database. This approach allows mapping brain regions to functions not necessarily tested in individual studies, thus suggesting possible novel functions for those regions. Additionally, ADHD-related dysfunctional regions were clustered based on their functional coactivation profiles across all the experiments stored in BrainMap (meta-analytic connectivity modeling). RESULTS: ADHD-related hypoactivation was found in the left putamen, left inferior frontal gyrus (pars opercularis), left temporal pole, and right caudate. Functional decoding mapped the left putamen to cognitive aspects of music perception/reproduction and the left temporal lobe to language semantics; both these regions clustered together on the basis of their meta-analytic functional connectivity. Left inferior gyrus mapped to executive function tasks; right caudate mapped to both executive function tasks and music-related processes. CONCLUSIONS: Our study provides meta-analytic support to the hypothesis that, in addition to well-known deficits in typical executive functions, impairment in processes related to music perception/reproduction and language semantics may be involved in the pathophysiology of adult ADHD." -27742561,PMC5123903,10.1016/j.yfrne.2016.10.001,The neural basis of sex differences in sexual behavior: A quantitative meta-analysis,"['Poeppl TB', 'Langguth B', 'Rupprecht R', 'Safron A', 'Bzdok D', 'Laird AR', 'Eickhoff SB']",2016,10,17,Front Neuroendocrinol,43,,28-43,"Sexuality as to its etymology presupposes the duality of sexes. Using quantitative neuroimaging meta-analyses, we demonstrate robust sex differences in the neural processing of sexual stimuli in thalamus, hypothalamus, and basal ganglia. In a narrative review, we show how these relate to the well-established sex differences on the behavioral level. More specifically, we describe the neural bases of known poor agreement between self-reported and genital measures of female sexual arousal, of previously proposed male proneness to affective sexual conditioning, as well as hints of unconscious activation of bonding mechanisms during sexual stimulation in women. In summary, our meta-analytic review demonstrates that neurofunctional sex differences during sexual stimulation can account for well-established sex differences in sexual behavior." +27742561,PMC5123903,10.1016/j.yfrne.2016.10.001,The neural basis of sex differences in sexual behavior: A quantitative meta-analysis,"['Poeppl TB', 'Langguth B', 'Rupprecht R', 'Safron A', 'Bzdok D', 'Laird AR', 'Eickhoff SB']",2016,10,8,Front Neuroendocrinol,43,,28-43,"Sexuality as to its etymology presupposes the duality of sexes. Using quantitative neuroimaging meta-analyses, we demonstrate robust sex differences in the neural processing of sexual stimuli in thalamus, hypothalamus, and basal ganglia. In a narrative review, we show how these relate to the well-established sex differences on the behavioral level. More specifically, we describe the neural bases of known poor agreement between self-reported and genital measures of female sexual arousal, of previously proposed male proneness to affective sexual conditioning, as well as hints of unconscious activation of bonding mechanisms during sexual stimulation in women. In summary, our meta-analytic review demonstrates that neurofunctional sex differences during sexual stimulation can account for well-established sex differences in sexual behavior." 27829086,PMC5293141,10.1001/jamapsychiatry.2016.2783,Altered Brain Activity in Unipolar Depression Revisited: Meta-analyses of Neuroimaging Studies,"['Muller VI', 'Cieslik EC', 'Serbanescu I', 'Laird AR', 'Fox PT', 'Eickhoff SB']",2017,1,1,JAMA Psychiatry,74,1,47-55,"Importance: During the past 20 years, numerous neuroimaging experiments have investigated aberrant brain activation during cognitive and emotional processing in patients with unipolar depression (UD). The results of those investigations, however, vary considerably; moreover, previous meta-analyses also yielded inconsistent findings. Objective: To readdress aberrant brain activation in UD as evidenced by neuroimaging experiments on cognitive and/or emotional processing. Data Sources: Neuroimaging experiments published from January 1, 1997, to October 1, 2015, were identified by a literature search of PubMed, Web of Science, and Google Scholar using different combinations of the terms fMRI (functional magnetic resonance imaging), PET (positron emission tomography), neural, major depression, depression, major depressive disorder, unipolar depression, dysthymia, emotion, emotional, affective, cognitive, task, memory, working memory, inhibition, control, n-back, and Stroop. Study Selection: Neuroimaging experiments (using fMRI or PET) reporting whole-brain results of group comparisons between adults with UD and healthy control individuals as coordinates in a standard anatomic reference space and using an emotional or/and cognitive challenging task were selected. Data Extraction and Synthesis: Coordinates reported to show significant activation differences between UD and healthy controls during emotional or cognitive processing were extracted. By using the revised activation likelihood estimation algorithm, different meta-analyses were calculated. Main Outcomes and Measures: Meta-analyses tested for brain regions consistently found to show aberrant brain activation in UD compared with controls. Analyses were calculated across all emotional processing experiments, all cognitive processing experiments, positive emotion processing, negative emotion processing, experiments using emotional face stimuli, experiments with a sex discrimination task, and memory processing. All meta-analyses were calculated across experiments independent of reporting an increase or decrease of activity in major depressive disorder. For meta-analyses with a minimum of 17 experiments available, separate analyses were performed for increases and decreases. Results: In total, 57 studies with 99 individual neuroimaging experiments comprising in total 1058 patients were included; 34 of them tested cognitive and 65 emotional processing. Overall analyses across cognitive processing experiments (P > .29) and across emotional processing experiments (P > .47) revealed no significant results. Similarly, no convergence was found in analyses investigating positive (all P > .15), negative (all P > .76), or memory (all P > .48) processes. Analyses that restricted inclusion of confounds (eg, medication, comorbidity, age) did not change the results. Conclusions and Relevance: Inconsistencies exist across individual experiments investigating aberrant brain activity in UD and replication problems across previous neuroimaging meta-analyses. For individual experiments, these inconsistencies may relate to use of uncorrected inference procedures, differences in experimental design and contrasts, or heterogeneous clinical populations; meta-analytically, differences may be attributable to varying inclusion and exclusion criteria or rather liberal statistical inference approaches." 28213119,PMC5555826,10.1016/j.neuroimage.2017.02.034,The heterogeneity of the left dorsal premotor cortex evidenced by multimodal connectivity-based parcellation and functional characterization,"['Genon S', 'Reid A', 'Li H', 'Fan L', 'Muller VI', 'Cieslik EC', 'Hoffstaedter F', 'Langner R', 'Grefkes C', 'Laird AR', 'Fox PT', 'Jiang T', 'Amunts K', 'Eickhoff SB']",2018,4,15,Neuroimage,170,,400-411,"Despite the common conception of the dorsal premotor cortex (PMd) as a single brain region, its diverse connectivity profiles and behavioral heterogeneity argue for a differentiated organization of the PMd. A previous study revealed that the right PMd is characterized by a rostro-caudal and a ventro-dorsal distinction dividing it into five subregions: rostral, central, caudal, ventral and dorsal. The present study assessed whether a similar organization is present in the left hemisphere, by capitalizing on a multimodal data-driven approach combining connectivity-based parcellation (CBP) based on meta-analytic modeling, resting-state functional connectivity, and probabilistic diffusion tractography. The resulting PMd modules were then characterized based on multimodal functional connectivity and a quantitative analysis of associated behavioral functions. Analyzing the clusters consistent across all modalities revealed an organization of the left PMd that mirrored its right counterpart to a large degree. Again, caudal, central and rostral modules reflected a cognitive-motor gradient and a premotor eye-field was found in the ventral part of the left PMd. In addition, a distinct module linked to abstract cognitive functions was observed in the rostro-ventral left PMd across all CBP modalities, implying greater differentiation of higher cognitive functions for the left than the right PMd." 28222386,PMC5408583,10.1016/j.neuroimage.2016.12.037,Heterogeneous fractionation profiles of meta-analytic coactivation networks,"['Laird AR', 'Riedel MC', 'Okoe M', 'Jianu R', 'Ray KL', 'Eickhoff SB', 'Smith SM', 'Fox PT', 'Sutherland MT']",2017,4,1,Neuroimage,149,,424-435,"Computational cognitive neuroimaging approaches can be leveraged to characterize the hierarchical organization of distributed, functionally specialized networks in the human brain. To this end, we performed large-scale mining across the BrainMap database of coordinate-based activation locations from over 10,000 task-based experiments. Meta-analytic coactivation networks were identified by jointly applying independent component analysis (ICA) and meta-analytic connectivity modeling (MACM) across a wide range of model orders (i.e., d=20-300). We then iteratively computed pairwise correlation coefficients for consecutive model orders to compare spatial network topologies, ultimately yielding fractionation profiles delineating how ""parent"" functional brain systems decompose into constituent ""child"" sub-networks. Fractionation profiles differed dramatically across canonical networks: some exhibited complex and extensive fractionation into a large number of sub-networks across the full range of model orders, whereas others exhibited little to no decomposition as model order increased. Hierarchical clustering was applied to evaluate this heterogeneity, yielding three distinct groups of network fractionation profiles: high, moderate, and low fractionation. BrainMap-based functional decoding of resultant coactivation networks revealed a multi-domain association regardless of fractionation complexity. Rather than emphasize a cognitive-motor-perceptual gradient, these outcomes suggest the importance of inter-lobar connectivity in functional brain organization. We conclude that high fractionation networks are complex and comprised of many constituent sub-networks reflecting long-range, inter-lobar connectivity, particularly in fronto-parietal regions. In contrast, low fractionation networks may reflect persistent and stable networks that are more internally coherent and exhibit reduced inter-lobar communication." 28222386,PMC5408583,10.1016/j.neuroimage.2016.12.037,Heterogeneous fractionation profiles of meta-analytic coactivation networks,"['Laird AR', 'Riedel MC', 'Okoe M', 'Jianu R', 'Ray KL', 'Eickhoff SB', 'Smith SM', 'Fox PT', 'Sutherland MT']",2017,4,1,Neuroimage,149,,424-435,"Computational cognitive neuroimaging approaches can be leveraged to characterize the hierarchical organization of distributed, functionally specialized networks in the human brain. To this end, we performed large-scale mining across the BrainMap database of coordinate-based activation locations from over 10,000 task-based experiments. Meta-analytic coactivation networks were identified by jointly applying independent component analysis (ICA) and meta-analytic connectivity modeling (MACM) across a wide range of model orders (i.e., d=20-300). We then iteratively computed pairwise correlation coefficients for consecutive model orders to compare spatial network topologies, ultimately yielding fractionation profiles delineating how ""parent"" functional brain systems decompose into constituent ""child"" sub-networks. Fractionation profiles differed dramatically across canonical networks: some exhibited complex and extensive fractionation into a large number of sub-networks across the full range of model orders, whereas others exhibited little to no decomposition as model order increased. Hierarchical clustering was applied to evaluate this heterogeneity, yielding three distinct groups of network fractionation profiles: high, moderate, and low fractionation. BrainMap-based functional decoding of resultant coactivation networks revealed a multi-domain association regardless of fractionation complexity. Rather than emphasize a cognitive-motor-perceptual gradient, these outcomes suggest the importance of inter-lobar connectivity in functional brain organization. We conclude that high fractionation networks are complex and comprised of many constituent sub-networks reflecting long-range, inter-lobar connectivity, particularly in fronto-parietal regions. In contrast, low fractionation networks may reflect persistent and stable networks that are more internally coherent and exhibit reduced inter-lobar communication." 28403383,PMC5539833,10.1001/jamapsychiatry.2017.0400,Neural Signatures of Cognitive Flexibility and Reward Sensitivity Following Nicotinic Receptor Stimulation in Dependent Smokers: A Randomized Trial,"['Lesage E', 'Aronson SE', 'Sutherland MT', 'Ross TJ', 'Salmeron BJ', 'Stein EA']",2017,6,1,JAMA Psychiatry,74,6,632-640,"Importance: Withdrawal from nicotine is an important contributor to smoking relapse. Understanding how reward-based decision making is affected by abstinence and by pharmacotherapies such as nicotine replacement therapy and varenicline tartrate may aid cessation treatment. Objective: To independently assess the effects of nicotine dependence and stimulation of the nicotinic acetylcholine receptor on the ability to interpret valence information (reward sensitivity) and subsequently alter behavior as reward contingencies change (cognitive flexibility) in a probabilistic reversal learning task. Design, Setting, and Participants: Nicotine-dependent smokers and nonsmokers completed a probabilistic reversal learning task during acquisition of functional magnetic resonance imaging (fMRI) in a 2-drug, double-blind placebo-controlled crossover design conducted from January 21, 2009, to September 29, 2011. Smokers were abstinent from cigarette smoking for 12 hours for all sessions. In a fully Latin square fashion, participants in both groups underwent MRI twice while receiving varenicline and twice while receiving a placebo pill, wearing either a nicotine or a placebo patch. Imaging analysis was performed from June 15, 2015, to August 10, 2016. Main Outcome and Measures: A well-established computational model captured effects of smoking status and administration of nicotine and varenicline on probabilistic reversal learning choice behavior. Neural effects of smoking status, nicotine, and varenicline were tested for on MRI contrasts that captured reward sensitivity and cognitive flexibility. Results: The study included 24 nicotine-dependent smokers (12 women and 12 men; mean [SD] age, 35.8 [9.9] years) and 20 nonsmokers (10 women and 10 men; mean [SD] age, 30.4 [7.2] years). Computational modeling indicated that abstinent smokers were biased toward response shifting and that their decisions were less sensitive to the available evidence, suggesting increased impulsivity during withdrawal. These behavioral impairments were mitigated with nicotine and varenicline. Similarly, decreased mesocorticolimbic activity associated with cognitive flexibility in abstinent smokers was restored to the level of nonsmokers following stimulation of nicotinic acetylcholine receptors (familywise error-corrected P < .05). Conversely, neural signatures of decreased reward sensitivity in smokers (vs nonsmokers; familywise error-corrected P < .05) in the dorsal striatum and anterior cingulate cortex were not mitigated by nicotine or varenicline. Conclusions and Relevance: There was a double dissociation between the effects of chronic nicotine dependence on neural representations of reward sensitivity and acute effects of stimulation of nicotinic acetylcholine receptors on behavioral and neural signatures of cognitive flexibility in smokers. These chronic and acute pharmacologic effects were observed in overlapping mesocorticolimbic regions, suggesting that available pharmacotherapies may alleviate deficits in the same circuitry for certain mental computations but not for others. Trial Registration: clinicaltrials.gov Identifier: NCT00830739." -28467917,,10.1016/j.cortex.2017.03.016,Resting-state functional reorganization in Parkinson's disease: An activation likelihood estimation meta-analysis,"['Tahmasian M', 'Eickhoff SB', 'Giehl K', 'Schwartz F', 'Herz DM', 'Drzezga A', 'van Eimeren T', 'Laird AR', 'Fox PT', 'Khazaie H', 'Zarei M', 'Eggers C', 'Eickhoff CR']",2017,7,17,Cortex,92,,119-138,"Parkinson's disease (PD) is a common progressive neurodegenerative disorder. Studies using resting-state functional magnetic resonance imaging (fMRI) to investigate underlying pathophysiology of motor and non-motor symptoms in PD yielded largely inconsistent results. This quantitative neuroimaging meta-analysis aims to identify consistent abnormal intrinsic functional patterns in PD across studies. We used PubMed to retrieve suitable resting-state studies and stereotactic data were extracted from 28 individual between-group comparisons. Convergence across their findings was tested using the activation likelihood estimation (ALE) approach. We found convergent evidence for intrinsic functional disturbances in bilateral inferior parietal lobule (IPL) and the supramarginal gyrus in PD patients compared to healthy subjects. In follow-up task-based and task-independent functional connectivity (FC) analyses using two independent healthy subject data sets, we found that the regions showing convergent aberrations in PD formed an interconnected network mainly with the default mode network (DMN). Behavioral characterization of these regions using the BrainMap database suggested associated dysfunction of perception and executive processes. Taken together, our findings highlight the role of parietal cortex in the pathophysiology of PD." +28467917,,10.1016/j.cortex.2017.03.016,Resting-state functional reorganization in Parkinson's disease: An activation likelihood estimation meta-analysis,"['Tahmasian M', 'Eickhoff SB', 'Giehl K', 'Schwartz F', 'Herz DM', 'Drzezga A', 'van Eimeren T', 'Laird AR', 'Fox PT', 'Khazaie H', 'Zarei M', 'Eggers C', 'Eickhoff CR']",2017,7,8,Cortex,92,,119-138,"Parkinson's disease (PD) is a common progressive neurodegenerative disorder. Studies using resting-state functional magnetic resonance imaging (fMRI) to investigate underlying pathophysiology of motor and non-motor symptoms in PD yielded largely inconsistent results. This quantitative neuroimaging meta-analysis aims to identify consistent abnormal intrinsic functional patterns in PD across studies. We used PubMed to retrieve suitable resting-state studies and stereotactic data were extracted from 28 individual between-group comparisons. Convergence across their findings was tested using the activation likelihood estimation (ALE) approach. We found convergent evidence for intrinsic functional disturbances in bilateral inferior parietal lobule (IPL) and the supramarginal gyrus in PD patients compared to healthy subjects. In follow-up task-based and task-independent functional connectivity (FC) analyses using two independent healthy subject data sets, we found that the regions showing convergent aberrations in PD formed an interconnected network mainly with the default mode network (DMN). Behavioral characterization of these regions using the BrainMap database suggested associated dysfunction of perception and executive processes. Taken together, our findings highlight the role of parietal cortex in the pathophysiology of PD." 28521007,,10.1093/cercor/bhx121,Computing the Social Brain Connectome Across Systems and States,"['Alcala-Lopez D', 'Smallwood J', 'Jefferies E', 'Van Overwalle F', 'Vogeley K', 'Mars RB', 'Turetsky BI', 'Laird AR', 'Fox PT', 'Eickhoff SB', 'Bzdok D']",2018,7,1,Cereb Cortex,28,7,2207-2232,"Social skills probably emerge from the interaction between different neural processing levels. However, social neuroscience is fragmented into highly specialized, rarely cross-referenced topics. The present study attempts a systematic reconciliation by deriving a social brain definition from neural activity meta-analyses on social-cognitive capacities. The social brain was characterized by meta-analytic connectivity modeling evaluating coactivation in task-focused brain states and physiological fluctuations evaluating correlations in task-free brain states. Network clustering proposed a functional segregation into (1) lower sensory, (2) limbic, (3) intermediate, and (4) high associative neural circuits that together mediate various social phenomena. Functional profiling suggested that no brain region or network is exclusively devoted to social processes. Finally, nodes of the putative mirror-neuron system were coherently cross-connected during tasks and more tightly coupled to embodied simulation systems rather than abstract emulation systems. These first steps may help reintegrate the specialized research agendas in the social and affective sciences." -28650075,PMC5685895,10.1002/jbmr.3202,Isl1 Controls Patterning and Mineralization of Enamel in the Continuously Renewing Mouse Incisor,"['Naveau A', 'Zhang B', 'Meng B', 'Sutherland MT', 'Prochazkova M', 'Wen T', 'Marangoni P', 'Jones KB', 'Cox TC', 'Ganss B', 'Jheon AH', 'Klein OD']",2017,11,17,J Bone Miner Res,32,11,2219-2231,"Rodents are characterized by continuously renewing incisors whose growth is fueled by epithelial and mesenchymal stem cells housed in the proximal compartments of the tooth. The epithelial stem cells reside in structures known as the labial (toward the lip) and lingual (toward the tongue) cervical loops (laCL and liCL, respectively). An important feature of the rodent incisor is that enamel, the outer, highly mineralized layer, is asymmetrically distributed, because it is normally generated by the laCL but not the liCL. Here, we show that epithelial-specific deletion of the transcription factor Islet1 (Isl1) is sufficient to drive formation of ectopic enamel by the liCL stem cells, and also that it leads to production of altered enamel on the labial surface. Molecular analyses of developing and adult incisors revealed that epithelial deletion of Isl1 affected multiple, major pathways: Bmp (bone morphogenetic protein), Hh (hedgehog), Fgf (fibroblast growth factor), and Notch signaling were upregulated and associated with liCL-generated ectopic enamel; on the labial side, upregulation of Bmp and Fgf signaling, and downregulation of Shh were associated with premature enamel formation. Transcriptome profiling studies identified a suite of differentially regulated genes in developing Isl1 mutant incisors. Our studies demonstrate that ISL1 plays a central role in proper patterning of stem cell-derived enamel in the incisor and indicate that this factor is an important upstream regulator of signaling pathways during tooth development and renewal. (c) 2017 American Society for Bone and Mineral Research." +28650075,PMC5685895,10.1002/jbmr.3202,Isl1 Controls Patterning and Mineralization of Enamel in the Continuously Renewing Mouse Incisor,"['Naveau A', 'Zhang B', 'Meng B', 'Sutherland MT', 'Prochazkova M', 'Wen T', 'Marangoni P', 'Jones KB', 'Cox TC', 'Ganss B', 'Jheon AH', 'Klein OD']",2017,11,8,J Bone Miner Res,32,11,2219-2231,"Rodents are characterized by continuously renewing incisors whose growth is fueled by epithelial and mesenchymal stem cells housed in the proximal compartments of the tooth. The epithelial stem cells reside in structures known as the labial (toward the lip) and lingual (toward the tongue) cervical loops (laCL and liCL, respectively). An important feature of the rodent incisor is that enamel, the outer, highly mineralized layer, is asymmetrically distributed, because it is normally generated by the laCL but not the liCL. Here, we show that epithelial-specific deletion of the transcription factor Islet1 (Isl1) is sufficient to drive formation of ectopic enamel by the liCL stem cells, and also that it leads to production of altered enamel on the labial surface. Molecular analyses of developing and adult incisors revealed that epithelial deletion of Isl1 affected multiple, major pathways: Bmp (bone morphogenetic protein), Hh (hedgehog), Fgf (fibroblast growth factor), and Notch signaling were upregulated and associated with liCL-generated ectopic enamel; on the labial side, upregulation of Bmp and Fgf signaling, and downregulation of Shh were associated with premature enamel formation. Transcriptome profiling studies identified a suite of differentially regulated genes in developing Isl1 mutant incisors. Our studies demonstrate that ISL1 plays a central role in proper patterning of stem cell-derived enamel in the incisor and indicate that this factor is an important upstream regulator of signaling pathways during tooth development and renewal. (c) 2017 American Society for Bone and Mineral Research." 29030105,PMC5732056,10.1016/j.neuroimage.2017.10.020,Definition and characterization of an extended multiple-demand network,"['Camilleri JA', 'Muller VI', 'Fox P', 'Laird AR', 'Hoffstaedter F', 'Kalenscher T', 'Eickhoff SB']",2018,1,15,Neuroimage,165,,138-147,"Neuroimaging evidence suggests that executive functions (EF) depend on brain regions that are not closely tied to specific cognitive demands but rather to a wide range of behaviors. A multiple-demand (MD) system has been proposed, consisting of regions showing conjoint activation across multiple demands. Additionally, a number of studies defining networks specific to certain cognitive tasks suggest that the MD system may be composed of a number of sub-networks each subserving specific roles within the system. We here provide a robust definition of an extended MDN (eMDN) based on task-dependent and task-independent functional connectivity analyses seeded from regions previously shown to be convergently recruited across neuroimaging studies probing working memory, attention and inhibition, i.e., the proposed key components of EF. Additionally, we investigated potential sub-networks within the eMDN based on their connectional and functional similarities. We propose an eMDN network consisting of a core whose integrity should be crucial to performance of most operations that are considered higher cognitive or EF. This then recruits additional areas depending on specific demands." -29180258,PMC5918306,10.1016/j.neubiorev.2017.11.012,Ten simple rules for neuroimaging meta-analysis,"['Muller VI', 'Cieslik EC', 'Laird AR', 'Fox PT', 'Radua J', 'Mataix-Cols D', 'Tench CR', 'Yarkoni T', 'Nichols TE', 'Turkeltaub PE', 'Wager TD', 'Eickhoff SB']",2018,1,17,Neurosci Biobehav Rev,84,,151-161,"Neuroimaging has evolved into a widely used method to investigate the functional neuroanatomy, brain-behaviour relationships, and pathophysiology of brain disorders, yielding a literature of more than 30,000 papers. With such an explosion of data, it is increasingly difficult to sift through the literature and distinguish spurious from replicable findings. Furthermore, due to the large number of studies, it is challenging to keep track of the wealth of findings. A variety of meta-analytical methods (coordinate-based and image-based) have been developed to help summarise and integrate the vast amount of data arising from neuroimaging studies. However, the field lacks specific guidelines for the conduct of such meta-analyses. Based on our combined experience, we propose best-practice recommendations that researchers from multiple disciplines may find helpful. In addition, we provide specific guidelines and a checklist that will hopefully improve the transparency, traceability, replicability and reporting of meta-analytical results of neuroimaging data." -29311863,PMC5732997,10.3389/fnbeh.2017.00245,Higher Trait Psychopathy Is Associated with Increased Risky Decision-Making and Less Coincident Insula and Striatal Activity,"['Sutherland MT', 'Fishbein DH']",2017,3,17,Front Behav Neurosci,11,,245,"Higher trait levels of psychopathy have been associated with both a tendency to maintain disadvantageous decision-making strategies and aberrant cortico-limbic neural activity. To explore the neural mechanisms associated with the psychopathy-related propensity to continue selecting risky choices, a non-forensic sample of participants completed a self-report psychopathy questionnaire and two runs of a risky decision-making task during H2(15)O positron emission tomography (PET) scanning. In this secondary data analysis study, we leveraged data previously collected to examine the impact of previous drug use on risky decision-making to explore the relations between self-reported psychopathy and behavioral and brain metrics during performance of the Cambridge Decision-Making Task (CDMT), in which volunteers chose between small/likely or large/unlikely potential reward outcomes. Behaviorally, we observed that psychopathy scores were differentially correlated with the percent of risky decisions made in run 1 vs. run 2 of the task. Specifically, higher levels of psychopathy, above and beyond that attributable to drug use or sex, were associated with greater tendencies to make risky selections only in the second half (run 2) of the task. In parallel, psychopathy scores negatively correlated with regional cerebral blood flow (rCBF) in the right insula and right ventral striatum during run 2 of the CDMT. These exploratory outcomes suggest that greater levels of psychopathy may be associated with an inability to translate experience with negative outcomes into behavioral adaptations possibly due to decreased neural efficiency in regions related to somatic and/or reward feedback processes." -29338547,PMC5858977,10.1177/0269881117744995,Neuroimaging meta-analysis of cannabis use studies reveals convergent functional alterations in brain regions supporting cognitive control and reward processing,"['Yanes JA', 'Riedel MC', 'Ray KL', 'Kirkland AE', 'Bird RT', 'Boeving ER', 'Reid MA', 'Gonzalez R', 'Robinson JL', 'Laird AR', 'Sutherland MT']",2018,3,17,J Psychopharmacol,32,3,283-295,"Lagging behind rapid changes to state laws, societal views, and medical practice is the scientific investigation of cannabis's impact on the human brain. While several brain imaging studies have contributed important insight into neurobiological alterations linked with cannabis use, our understanding remains limited. Here, we sought to delineate those brain regions that consistently demonstrate functional alterations among cannabis users versus non-users across neuroimaging studies using the activation likelihood estimation meta-analysis framework. In ancillary analyses, we characterized task-related brain networks that co-activate with cannabis-affected regions using data archived in a large neuroimaging repository, and then determined which psychological processes may be disrupted via functional decoding techniques. When considering convergent alterations among users, decreased activation was observed in the anterior cingulate cortex, which co-activated with frontal, parietal, and limbic areas and was linked with cognitive control processes. Similarly, decreased activation was observed in the dorsolateral prefrontal cortex, which co-activated with frontal and occipital areas and linked with attention-related processes. Conversely, increased activation among users was observed in the striatum, which co-activated with frontal, parietal, and other limbic areas and linked with reward processing. These meta-analytic outcomes indicate that cannabis use is linked with differential, region-specific effects across the brain." -29338547,PMC5858977,10.1177/0269881117744995,Neuroimaging meta-analysis of cannabis use studies reveals convergent functional alterations in brain regions supporting cognitive control and reward processing,"['Yanes JA', 'Riedel MC', 'Ray KL', 'Kirkland AE', 'Bird RT', 'Boeving ER', 'Reid MA', 'Gonzalez R', 'Robinson JL', 'Laird AR', 'Sutherland MT']",2018,3,17,J Psychopharmacol,32,3,283-295,"Lagging behind rapid changes to state laws, societal views, and medical practice is the scientific investigation of cannabis's impact on the human brain. While several brain imaging studies have contributed important insight into neurobiological alterations linked with cannabis use, our understanding remains limited. Here, we sought to delineate those brain regions that consistently demonstrate functional alterations among cannabis users versus non-users across neuroimaging studies using the activation likelihood estimation meta-analysis framework. In ancillary analyses, we characterized task-related brain networks that co-activate with cannabis-affected regions using data archived in a large neuroimaging repository, and then determined which psychological processes may be disrupted via functional decoding techniques. When considering convergent alterations among users, decreased activation was observed in the anterior cingulate cortex, which co-activated with frontal, parietal, and limbic areas and was linked with cognitive control processes. Similarly, decreased activation was observed in the dorsolateral prefrontal cortex, which co-activated with frontal and occipital areas and linked with attention-related processes. Conversely, increased activation among users was observed in the striatum, which co-activated with frontal, parietal, and other limbic areas and linked with reward processing. These meta-analytic outcomes indicate that cannabis use is linked with differential, region-specific effects across the brain." -29398401,PMC5928775,10.1016/j.molmed.2017.12.002,Functional Neurocircuits and Neuroimaging Biomarkers of Tobacco Use Disorder,"['Sutherland MT', 'Stein EA']",2018,2,17,Trends Mol Med,24,2,129-143,"Drug abuse and addiction remain major public health issues, exemplified by the opioid epidemic currently devastating the United States. Treatment outcomes across substance use disorders remain unacceptably poor, wherein drug discovery/development for this multifaceted neuropsychiatric disorder focuses on single molecular-level targets. Rather, our opinion is that a systems-level neuroimaging perspective is crucial for identifying novel therapeutic targets, biomarkers to stratify patients, and individualized treatment strategies. Focusing on tobacco use disorder, we advocate a brain systems-level perspective linking two abuse-related facets (i.e., statelike withdrawal and traitlike addiction severity) with specific neurocircuitry (insula- and striatum-centered networks). To the extent that precise neurocircuits mediate distinct facets of abuse, treatment development must adopt not only a systems-level perspective, but also multi-intervention rather than mono-intervention practices." -29484767,PMC5951754,10.1002/hbm.24018,Dissociable meta-analytic brain networks contribute to coordinated emotional processing,"['Riedel MC', 'Yanes JA', 'Ray KL', 'Eickhoff SB', 'Fox PT', 'Sutherland MT', 'Laird AR']",2018,6,17,Hum Brain Mapp,39,6,2514-2531,"Meta-analytic techniques for mining the neuroimaging literature continue to exert an impact on our conceptualization of functional brain networks contributing to human emotion and cognition. Traditional theories regarding the neurobiological substrates contributing to affective processing are shifting from regional- towards more network-based heuristic frameworks. To elucidate differential brain network involvement linked to distinct aspects of emotion processing, we applied an emergent meta-analytic clustering approach to the extensive body of affective neuroimaging results archived in the BrainMap database. Specifically, we performed hierarchical clustering on the modeled activation maps from 1,747 experiments in the affective processing domain, resulting in five meta-analytic groupings of experiments demonstrating whole-brain recruitment. Behavioral inference analyses conducted for each of these groupings suggested dissociable networks supporting: (1) visual perception within primary and associative visual cortices, (2) auditory perception within primary auditory cortices, (3) attention to emotionally salient information within insular, anterior cingulate, and subcortical regions, (4) appraisal and prediction of emotional events within medial prefrontal and posterior cingulate cortices, and (5) induction of emotional responses within amygdala and fusiform gyri. These meta-analytic outcomes are consistent with a contemporary psychological model of affective processing in which emotionally salient information from perceived stimuli are integrated with previous experiences to engender a subjective affective response. This study highlights the utility of using emergent meta-analytic methods to inform and extend psychological theories and suggests that emotions are manifest as the eventual consequence of interactions between large-scale brain networks." -29484767,PMC5951754,10.1002/hbm.24018,Dissociable meta-analytic brain networks contribute to coordinated emotional processing,"['Riedel MC', 'Yanes JA', 'Ray KL', 'Eickhoff SB', 'Fox PT', 'Sutherland MT', 'Laird AR']",2018,6,17,Hum Brain Mapp,39,6,2514-2531,"Meta-analytic techniques for mining the neuroimaging literature continue to exert an impact on our conceptualization of functional brain networks contributing to human emotion and cognition. Traditional theories regarding the neurobiological substrates contributing to affective processing are shifting from regional- towards more network-based heuristic frameworks. To elucidate differential brain network involvement linked to distinct aspects of emotion processing, we applied an emergent meta-analytic clustering approach to the extensive body of affective neuroimaging results archived in the BrainMap database. Specifically, we performed hierarchical clustering on the modeled activation maps from 1,747 experiments in the affective processing domain, resulting in five meta-analytic groupings of experiments demonstrating whole-brain recruitment. Behavioral inference analyses conducted for each of these groupings suggested dissociable networks supporting: (1) visual perception within primary and associative visual cortices, (2) auditory perception within primary auditory cortices, (3) attention to emotionally salient information within insular, anterior cingulate, and subcortical regions, (4) appraisal and prediction of emotional events within medial prefrontal and posterior cingulate cortices, and (5) induction of emotional responses within amygdala and fusiform gyri. These meta-analytic outcomes are consistent with a contemporary psychological model of affective processing in which emotionally salient information from perceived stimuli are integrated with previous experiences to engender a subjective affective response. This study highlights the utility of using emergent meta-analytic methods to inform and extend psychological theories and suggests that emotions are manifest as the eventual consequence of interactions between large-scale brain networks." -29567376,PMC5999559,10.1016/j.dcn.2018.03.001,The Adolescent Brain Cognitive Development (ABCD) study: Imaging acquisition across 21 sites,"['Casey BJ', 'Cannonier T', 'Conley MI', 'Cohen AO', 'Barch DM', 'Heitzeg MM', 'Soules ME', 'Teslovich T', 'Dellarco DV', 'Garavan H', 'Orr CA', 'Wager TD', 'Banich MT', 'Speer NK', 'Sutherland MT', 'Riedel MC', 'Dick AS', 'Bjork JM', 'Thomas KM', 'Chaarani B', 'Mejia MH', 'Hagler DJ Jr', 'Daniela Cornejo M', 'Sicat CS', 'Harms MP', 'Dosenbach NUF', 'Rosenberg M', 'Earl E', 'Bartsch H', 'Watts R', 'Polimeni JR', 'Kuperman JM', 'Fair DA', 'Dale AM']",2018,8,17,Dev Cogn Neurosci,32,,43-54,"The ABCD study is recruiting and following the brain development and health of over 10,000 9-10year olds through adolescence. The imaging component of the study was developed by the ABCD Data Analysis and Informatics Center (DAIC) and the ABCD Imaging Acquisition Workgroup. Imaging methods and assessments were selected, optimized and harmonized across all 21 sites to measure brain structure and function relevant to adolescent development and addiction. This article provides an overview of the imaging procedures of the ABCD study, the basis for their selection and preliminary quality assurance and results that provide evidence for the feasibility and age-appropriateness of procedures and generalizability of findings to the existent literature." -29868451,PMC5984594,10.1016/j.nicl.2018.01.020,Convergence Analysis of Micro-Lesions (CAML): An approach to mapping of diffuse lesions from carotid revascularization,"['Rosen AC', 'Soman S', 'Bhat J', 'Laird AR', 'Stephens J', 'Eickhoff SB', 'Fox PM', 'Long B', 'Dinishak D', 'Ortega M', 'Lane B', 'Wintermark M', 'Hitchner E', 'Zhou W']",2018,3,17,Neuroimage Clin,18,,553-559,"Carotid revascularization (endarterectomy, stenting) prevents stroke; however, procedure-related embolization is common and results in small brain lesions easily identified by diffusion weighted magnetic resonance imaging (DWI). A crucial barrier to understanding the clinical significance of these lesions has been the lack of a statistical approach to identify vulnerable brain areas. The problem is that the lesions are small, numerous, and non-overlapping. Here we address this problem with a new method, the Convergence Analysis of Micro-Lesions (CAML) technique, an extension of the Anatomic Likelihood Analysis (ALE). The method combines manual lesion tracing, constraints based on known lesion patterns, and convergence analysis to represent regions vulnerable to lesions as probabilistic brain atlases. Two studies were conducted over the course of 12years in an active, vascular surgery clinic. An analysis in an initial group of 126 patients at 1.5 T MRI was cross-validated in a second group of 80 patients at 3T MRI. In CAML, lesions were manually defined and center points identified. Brains were aligned according to side of surgery since this factor powerfully determines lesion distribution. A convergence based analysis, was performed on each of these groups. Results indicated the most consistent region of vulnerability was in motor and premotor cortex regions. Smaller regions common to both groups included the dorsolateral prefrontal cortex and medial parietal regions. Vulnerability of motor cortex is consistent with previous work showing changes in hand dexterity associated with these procedures. The consistency of CAML also demonstrates the feasibility of this new approach to characterize small, diffuse, non-overlapping lesions in patients with multifocal pathologies." -29944961,PMC6425494,10.1016/j.neubiorev.2018.06.009,Meta-analytic evidence for a core problem solving network across multiple representational domains,"['Bartley JE', 'Boeving ER', 'Riedel MC', 'Bottenhorn KL', 'Salo T', 'Eickhoff SB', 'Brewe E', 'Sutherland MT', 'Laird AR']",2018,9,17,Neurosci Biobehav Rev,92,,318-337,"Problem solving is a complex skill engaging multi-stepped reasoning processes to find unknown solutions. The breadth of real-world contexts requiring problem solving is mirrored by a similarly broad, yet unfocused neuroimaging literature, and the domain-general or context-specific brain networks associated with problem solving are not well understood. To more fully characterize those brain networks, we performed activation likelihood estimation meta-analysis on 280 neuroimaging problem solving experiments reporting 3166 foci from 1919 individuals across 131 papers. The general map of problem solving revealed broad fronto-cingulo-parietal convergence, regions similarly identified when considering separate mathematical, verbal, and visuospatial problem solving domain-specific analyses. Conjunction analysis revealed a common network supporting problem solving across diverse contexts, and difference maps distinguished functionally-selective sub-networks specific to task type. Our results suggest cooperation between representationally specialized sub-network and whole-brain systems provide a neural basis for problem solving, with the core network contributing general purpose resources to perform cognitive operations and manage problem demand. Further characterization of cross-network dynamics could inform neuroeducational studies on problem solving skill development." -29944961,PMC6425494,10.1016/j.neubiorev.2018.06.009,Meta-analytic evidence for a core problem solving network across multiple representational domains,"['Bartley JE', 'Boeving ER', 'Riedel MC', 'Bottenhorn KL', 'Salo T', 'Eickhoff SB', 'Brewe E', 'Sutherland MT', 'Laird AR']",2018,9,17,Neurosci Biobehav Rev,92,,318-337,"Problem solving is a complex skill engaging multi-stepped reasoning processes to find unknown solutions. The breadth of real-world contexts requiring problem solving is mirrored by a similarly broad, yet unfocused neuroimaging literature, and the domain-general or context-specific brain networks associated with problem solving are not well understood. To more fully characterize those brain networks, we performed activation likelihood estimation meta-analysis on 280 neuroimaging problem solving experiments reporting 3166 foci from 1919 individuals across 131 papers. The general map of problem solving revealed broad fronto-cingulo-parietal convergence, regions similarly identified when considering separate mathematical, verbal, and visuospatial problem solving domain-specific analyses. Conjunction analysis revealed a common network supporting problem solving across diverse contexts, and difference maps distinguished functionally-selective sub-networks specific to task type. Our results suggest cooperation between representationally specialized sub-network and whole-brain systems provide a neural basis for problem solving, with the core network contributing general purpose resources to perform cognitive operations and manage problem demand. Further characterization of cross-network dynamics could inform neuroeducational studies on problem solving skill development." -30038232,PMC6344321,10.1038/s41380-018-0122-5,A view behind the mask of sanity: meta-analysis of aberrant brain activity in psychopaths,"['Poeppl TB', 'Donges MR', 'Mokros A', 'Rupprecht R', 'Fox PT', 'Laird AR', 'Bzdok D', 'Langguth B', 'Eickhoff SB']",2019,3,17,Mol Psychiatry,24,3,463-470,"Psychopathy is a disorder of high public concern because it predicts violence and offense recidivism. Recent brain imaging studies suggest abnormal brain activity underlying psychopathic behavior. No reliable pattern of altered neural activity has been disclosed so far. This study sought to identify consistent changes of brain activity in psychopaths and to investigate whether these could explain known psychopathology. First, we used activation likelihood estimation (p < 0.05, corrected) to meta-analyze brain activation changes associated with psychopathy across 28 functional magnetic resonance imaging studies reporting 753 foci from 155 experiments. Second, we characterized the ensuing regions functionally by employing metadata of a large-scale neuroimaging database (p < 0.05, corrected). Psychopathy was consistently associated with decreased brain activity in the right laterobasal amygdala, the dorsomedial prefrontal cortex, and bilaterally in the lateral prefrontal cortex. A robust increase of activity was observed in the fronto-insular cortex on both hemispheres. Data-driven functional characterization revealed associations with semantic language processing (left lateral prefrontal and fronto-insular cortex), action execution and pain processing (right lateral prefrontal and left fronto-insular), social cognition (dorsomedial prefrontal cortex), and emotional as well as cognitive reward processing (right amygdala and fronto-insular cortex). Aberrant brain activity related to psychopathy is located in prefrontal, insular, and limbic regions. Physiological mental functions fulfilled by these brain regions correspond to disturbed behavioral patterns pathognomonic for psychopathy. Hence, aberrant brain activity may not just be an epiphenomenon of psychopathy but directly related to the psychopathology of this disorder." +29180258,PMC5918306,10.1016/j.neubiorev.2017.11.012,Ten simple rules for neuroimaging meta-analysis,"['Muller VI', 'Cieslik EC', 'Laird AR', 'Fox PT', 'Radua J', 'Mataix-Cols D', 'Tench CR', 'Yarkoni T', 'Nichols TE', 'Turkeltaub PE', 'Wager TD', 'Eickhoff SB']",2018,1,8,Neurosci Biobehav Rev,84,,151-161,"Neuroimaging has evolved into a widely used method to investigate the functional neuroanatomy, brain-behaviour relationships, and pathophysiology of brain disorders, yielding a literature of more than 30,000 papers. With such an explosion of data, it is increasingly difficult to sift through the literature and distinguish spurious from replicable findings. Furthermore, due to the large number of studies, it is challenging to keep track of the wealth of findings. A variety of meta-analytical methods (coordinate-based and image-based) have been developed to help summarise and integrate the vast amount of data arising from neuroimaging studies. However, the field lacks specific guidelines for the conduct of such meta-analyses. Based on our combined experience, we propose best-practice recommendations that researchers from multiple disciplines may find helpful. In addition, we provide specific guidelines and a checklist that will hopefully improve the transparency, traceability, replicability and reporting of meta-analytical results of neuroimaging data." +29311863,PMC5732997,10.3389/fnbeh.2017.00245,Higher Trait Psychopathy Is Associated with Increased Risky Decision-Making and Less Coincident Insula and Striatal Activity,"['Sutherland MT', 'Fishbein DH']",2017,6,8,Front Behav Neurosci,11,,245,"Higher trait levels of psychopathy have been associated with both a tendency to maintain disadvantageous decision-making strategies and aberrant cortico-limbic neural activity. To explore the neural mechanisms associated with the psychopathy-related propensity to continue selecting risky choices, a non-forensic sample of participants completed a self-report psychopathy questionnaire and two runs of a risky decision-making task during H2(15)O positron emission tomography (PET) scanning. In this secondary data analysis study, we leveraged data previously collected to examine the impact of previous drug use on risky decision-making to explore the relations between self-reported psychopathy and behavioral and brain metrics during performance of the Cambridge Decision-Making Task (CDMT), in which volunteers chose between small/likely or large/unlikely potential reward outcomes. Behaviorally, we observed that psychopathy scores were differentially correlated with the percent of risky decisions made in run 1 vs. run 2 of the task. Specifically, higher levels of psychopathy, above and beyond that attributable to drug use or sex, were associated with greater tendencies to make risky selections only in the second half (run 2) of the task. In parallel, psychopathy scores negatively correlated with regional cerebral blood flow (rCBF) in the right insula and right ventral striatum during run 2 of the CDMT. These exploratory outcomes suggest that greater levels of psychopathy may be associated with an inability to translate experience with negative outcomes into behavioral adaptations possibly due to decreased neural efficiency in regions related to somatic and/or reward feedback processes." +29338547,PMC5858977,10.1177/0269881117744995,Neuroimaging meta-analysis of cannabis use studies reveals convergent functional alterations in brain regions supporting cognitive control and reward processing,"['Yanes JA', 'Riedel MC', 'Ray KL', 'Kirkland AE', 'Bird RT', 'Boeving ER', 'Reid MA', 'Gonzalez R', 'Robinson JL', 'Laird AR', 'Sutherland MT']",2018,3,8,J Psychopharmacol,32,3,283-295,"Lagging behind rapid changes to state laws, societal views, and medical practice is the scientific investigation of cannabis's impact on the human brain. While several brain imaging studies have contributed important insight into neurobiological alterations linked with cannabis use, our understanding remains limited. Here, we sought to delineate those brain regions that consistently demonstrate functional alterations among cannabis users versus non-users across neuroimaging studies using the activation likelihood estimation meta-analysis framework. In ancillary analyses, we characterized task-related brain networks that co-activate with cannabis-affected regions using data archived in a large neuroimaging repository, and then determined which psychological processes may be disrupted via functional decoding techniques. When considering convergent alterations among users, decreased activation was observed in the anterior cingulate cortex, which co-activated with frontal, parietal, and limbic areas and was linked with cognitive control processes. Similarly, decreased activation was observed in the dorsolateral prefrontal cortex, which co-activated with frontal and occipital areas and linked with attention-related processes. Conversely, increased activation among users was observed in the striatum, which co-activated with frontal, parietal, and other limbic areas and linked with reward processing. These meta-analytic outcomes indicate that cannabis use is linked with differential, region-specific effects across the brain." +29338547,PMC5858977,10.1177/0269881117744995,Neuroimaging meta-analysis of cannabis use studies reveals convergent functional alterations in brain regions supporting cognitive control and reward processing,"['Yanes JA', 'Riedel MC', 'Ray KL', 'Kirkland AE', 'Bird RT', 'Boeving ER', 'Reid MA', 'Gonzalez R', 'Robinson JL', 'Laird AR', 'Sutherland MT']",2018,3,8,J Psychopharmacol,32,3,283-295,"Lagging behind rapid changes to state laws, societal views, and medical practice is the scientific investigation of cannabis's impact on the human brain. While several brain imaging studies have contributed important insight into neurobiological alterations linked with cannabis use, our understanding remains limited. Here, we sought to delineate those brain regions that consistently demonstrate functional alterations among cannabis users versus non-users across neuroimaging studies using the activation likelihood estimation meta-analysis framework. In ancillary analyses, we characterized task-related brain networks that co-activate with cannabis-affected regions using data archived in a large neuroimaging repository, and then determined which psychological processes may be disrupted via functional decoding techniques. When considering convergent alterations among users, decreased activation was observed in the anterior cingulate cortex, which co-activated with frontal, parietal, and limbic areas and was linked with cognitive control processes. Similarly, decreased activation was observed in the dorsolateral prefrontal cortex, which co-activated with frontal and occipital areas and linked with attention-related processes. Conversely, increased activation among users was observed in the striatum, which co-activated with frontal, parietal, and other limbic areas and linked with reward processing. These meta-analytic outcomes indicate that cannabis use is linked with differential, region-specific effects across the brain." +29398401,PMC5928775,10.1016/j.molmed.2017.12.002,Functional Neurocircuits and Neuroimaging Biomarkers of Tobacco Use Disorder,"['Sutherland MT', 'Stein EA']",2018,2,8,Trends Mol Med,24,2,129-143,"Drug abuse and addiction remain major public health issues, exemplified by the opioid epidemic currently devastating the United States. Treatment outcomes across substance use disorders remain unacceptably poor, wherein drug discovery/development for this multifaceted neuropsychiatric disorder focuses on single molecular-level targets. Rather, our opinion is that a systems-level neuroimaging perspective is crucial for identifying novel therapeutic targets, biomarkers to stratify patients, and individualized treatment strategies. Focusing on tobacco use disorder, we advocate a brain systems-level perspective linking two abuse-related facets (i.e., statelike withdrawal and traitlike addiction severity) with specific neurocircuitry (insula- and striatum-centered networks). To the extent that precise neurocircuits mediate distinct facets of abuse, treatment development must adopt not only a systems-level perspective, but also multi-intervention rather than mono-intervention practices." +29484767,PMC5951754,10.1002/hbm.24018,Dissociable meta-analytic brain networks contribute to coordinated emotional processing,"['Riedel MC', 'Yanes JA', 'Ray KL', 'Eickhoff SB', 'Fox PT', 'Sutherland MT', 'Laird AR']",2018,6,8,Hum Brain Mapp,39,6,2514-2531,"Meta-analytic techniques for mining the neuroimaging literature continue to exert an impact on our conceptualization of functional brain networks contributing to human emotion and cognition. Traditional theories regarding the neurobiological substrates contributing to affective processing are shifting from regional- towards more network-based heuristic frameworks. To elucidate differential brain network involvement linked to distinct aspects of emotion processing, we applied an emergent meta-analytic clustering approach to the extensive body of affective neuroimaging results archived in the BrainMap database. Specifically, we performed hierarchical clustering on the modeled activation maps from 1,747 experiments in the affective processing domain, resulting in five meta-analytic groupings of experiments demonstrating whole-brain recruitment. Behavioral inference analyses conducted for each of these groupings suggested dissociable networks supporting: (1) visual perception within primary and associative visual cortices, (2) auditory perception within primary auditory cortices, (3) attention to emotionally salient information within insular, anterior cingulate, and subcortical regions, (4) appraisal and prediction of emotional events within medial prefrontal and posterior cingulate cortices, and (5) induction of emotional responses within amygdala and fusiform gyri. These meta-analytic outcomes are consistent with a contemporary psychological model of affective processing in which emotionally salient information from perceived stimuli are integrated with previous experiences to engender a subjective affective response. This study highlights the utility of using emergent meta-analytic methods to inform and extend psychological theories and suggests that emotions are manifest as the eventual consequence of interactions between large-scale brain networks." +29484767,PMC5951754,10.1002/hbm.24018,Dissociable meta-analytic brain networks contribute to coordinated emotional processing,"['Riedel MC', 'Yanes JA', 'Ray KL', 'Eickhoff SB', 'Fox PT', 'Sutherland MT', 'Laird AR']",2018,6,8,Hum Brain Mapp,39,6,2514-2531,"Meta-analytic techniques for mining the neuroimaging literature continue to exert an impact on our conceptualization of functional brain networks contributing to human emotion and cognition. Traditional theories regarding the neurobiological substrates contributing to affective processing are shifting from regional- towards more network-based heuristic frameworks. To elucidate differential brain network involvement linked to distinct aspects of emotion processing, we applied an emergent meta-analytic clustering approach to the extensive body of affective neuroimaging results archived in the BrainMap database. Specifically, we performed hierarchical clustering on the modeled activation maps from 1,747 experiments in the affective processing domain, resulting in five meta-analytic groupings of experiments demonstrating whole-brain recruitment. Behavioral inference analyses conducted for each of these groupings suggested dissociable networks supporting: (1) visual perception within primary and associative visual cortices, (2) auditory perception within primary auditory cortices, (3) attention to emotionally salient information within insular, anterior cingulate, and subcortical regions, (4) appraisal and prediction of emotional events within medial prefrontal and posterior cingulate cortices, and (5) induction of emotional responses within amygdala and fusiform gyri. These meta-analytic outcomes are consistent with a contemporary psychological model of affective processing in which emotionally salient information from perceived stimuli are integrated with previous experiences to engender a subjective affective response. This study highlights the utility of using emergent meta-analytic methods to inform and extend psychological theories and suggests that emotions are manifest as the eventual consequence of interactions between large-scale brain networks." +29567376,PMC5999559,10.1016/j.dcn.2018.03.001,The Adolescent Brain Cognitive Development (ABCD) study: Imaging acquisition across 21 sites,"['Casey BJ', 'Cannonier T', 'Conley MI', 'Cohen AO', 'Barch DM', 'Heitzeg MM', 'Soules ME', 'Teslovich T', 'Dellarco DV', 'Garavan H', 'Orr CA', 'Wager TD', 'Banich MT', 'Speer NK', 'Sutherland MT', 'Riedel MC', 'Dick AS', 'Bjork JM', 'Thomas KM', 'Chaarani B', 'Mejia MH', 'Hagler DJ Jr', 'Daniela Cornejo M', 'Sicat CS', 'Harms MP', 'Dosenbach NUF', 'Rosenberg M', 'Earl E', 'Bartsch H', 'Watts R', 'Polimeni JR', 'Kuperman JM', 'Fair DA', 'Dale AM']",2018,8,8,Dev Cogn Neurosci,32,,43-54,"The ABCD study is recruiting and following the brain development and health of over 10,000 9-10year olds through adolescence. The imaging component of the study was developed by the ABCD Data Analysis and Informatics Center (DAIC) and the ABCD Imaging Acquisition Workgroup. Imaging methods and assessments were selected, optimized and harmonized across all 21 sites to measure brain structure and function relevant to adolescent development and addiction. This article provides an overview of the imaging procedures of the ABCD study, the basis for their selection and preliminary quality assurance and results that provide evidence for the feasibility and age-appropriateness of procedures and generalizability of findings to the existent literature." +29868451,PMC5984594,10.1016/j.nicl.2018.01.020,Convergence Analysis of Micro-Lesions (CAML): An approach to mapping of diffuse lesions from carotid revascularization,"['Rosen AC', 'Soman S', 'Bhat J', 'Laird AR', 'Stephens J', 'Eickhoff SB', 'Fox PM', 'Long B', 'Dinishak D', 'Ortega M', 'Lane B', 'Wintermark M', 'Hitchner E', 'Zhou W']",2018,6,8,Neuroimage Clin,18,,553-559,"Carotid revascularization (endarterectomy, stenting) prevents stroke; however, procedure-related embolization is common and results in small brain lesions easily identified by diffusion weighted magnetic resonance imaging (DWI). A crucial barrier to understanding the clinical significance of these lesions has been the lack of a statistical approach to identify vulnerable brain areas. The problem is that the lesions are small, numerous, and non-overlapping. Here we address this problem with a new method, the Convergence Analysis of Micro-Lesions (CAML) technique, an extension of the Anatomic Likelihood Analysis (ALE). The method combines manual lesion tracing, constraints based on known lesion patterns, and convergence analysis to represent regions vulnerable to lesions as probabilistic brain atlases. Two studies were conducted over the course of 12years in an active, vascular surgery clinic. An analysis in an initial group of 126 patients at 1.5 T MRI was cross-validated in a second group of 80 patients at 3T MRI. In CAML, lesions were manually defined and center points identified. Brains were aligned according to side of surgery since this factor powerfully determines lesion distribution. A convergence based analysis, was performed on each of these groups. Results indicated the most consistent region of vulnerability was in motor and premotor cortex regions. Smaller regions common to both groups included the dorsolateral prefrontal cortex and medial parietal regions. Vulnerability of motor cortex is consistent with previous work showing changes in hand dexterity associated with these procedures. The consistency of CAML also demonstrates the feasibility of this new approach to characterize small, diffuse, non-overlapping lesions in patients with multifocal pathologies." +29944961,PMC6425494,10.1016/j.neubiorev.2018.06.009,Meta-analytic evidence for a core problem solving network across multiple representational domains,"['Bartley JE', 'Boeving ER', 'Riedel MC', 'Bottenhorn KL', 'Salo T', 'Eickhoff SB', 'Brewe E', 'Sutherland MT', 'Laird AR']",2018,9,8,Neurosci Biobehav Rev,92,,318-337,"Problem solving is a complex skill engaging multi-stepped reasoning processes to find unknown solutions. The breadth of real-world contexts requiring problem solving is mirrored by a similarly broad, yet unfocused neuroimaging literature, and the domain-general or context-specific brain networks associated with problem solving are not well understood. To more fully characterize those brain networks, we performed activation likelihood estimation meta-analysis on 280 neuroimaging problem solving experiments reporting 3166 foci from 1919 individuals across 131 papers. The general map of problem solving revealed broad fronto-cingulo-parietal convergence, regions similarly identified when considering separate mathematical, verbal, and visuospatial problem solving domain-specific analyses. Conjunction analysis revealed a common network supporting problem solving across diverse contexts, and difference maps distinguished functionally-selective sub-networks specific to task type. Our results suggest cooperation between representationally specialized sub-network and whole-brain systems provide a neural basis for problem solving, with the core network contributing general purpose resources to perform cognitive operations and manage problem demand. Further characterization of cross-network dynamics could inform neuroeducational studies on problem solving skill development." +29944961,PMC6425494,10.1016/j.neubiorev.2018.06.009,Meta-analytic evidence for a core problem solving network across multiple representational domains,"['Bartley JE', 'Boeving ER', 'Riedel MC', 'Bottenhorn KL', 'Salo T', 'Eickhoff SB', 'Brewe E', 'Sutherland MT', 'Laird AR']",2018,9,8,Neurosci Biobehav Rev,92,,318-337,"Problem solving is a complex skill engaging multi-stepped reasoning processes to find unknown solutions. The breadth of real-world contexts requiring problem solving is mirrored by a similarly broad, yet unfocused neuroimaging literature, and the domain-general or context-specific brain networks associated with problem solving are not well understood. To more fully characterize those brain networks, we performed activation likelihood estimation meta-analysis on 280 neuroimaging problem solving experiments reporting 3166 foci from 1919 individuals across 131 papers. The general map of problem solving revealed broad fronto-cingulo-parietal convergence, regions similarly identified when considering separate mathematical, verbal, and visuospatial problem solving domain-specific analyses. Conjunction analysis revealed a common network supporting problem solving across diverse contexts, and difference maps distinguished functionally-selective sub-networks specific to task type. Our results suggest cooperation between representationally specialized sub-network and whole-brain systems provide a neural basis for problem solving, with the core network contributing general purpose resources to perform cognitive operations and manage problem demand. Further characterization of cross-network dynamics could inform neuroeducational studies on problem solving skill development." +30038232,PMC6344321,10.1038/s41380-018-0122-5,A view behind the mask of sanity: meta-analysis of aberrant brain activity in psychopaths,"['Poeppl TB', 'Donges MR', 'Mokros A', 'Rupprecht R', 'Fox PT', 'Laird AR', 'Bzdok D', 'Langguth B', 'Eickhoff SB']",2019,3,8,Mol Psychiatry,24,3,463-470,"Psychopathy is a disorder of high public concern because it predicts violence and offense recidivism. Recent brain imaging studies suggest abnormal brain activity underlying psychopathic behavior. No reliable pattern of altered neural activity has been disclosed so far. This study sought to identify consistent changes of brain activity in psychopaths and to investigate whether these could explain known psychopathology. First, we used activation likelihood estimation (p < 0.05, corrected) to meta-analyze brain activation changes associated with psychopathy across 28 functional magnetic resonance imaging studies reporting 753 foci from 155 experiments. Second, we characterized the ensuing regions functionally by employing metadata of a large-scale neuroimaging database (p < 0.05, corrected). Psychopathy was consistently associated with decreased brain activity in the right laterobasal amygdala, the dorsomedial prefrontal cortex, and bilaterally in the lateral prefrontal cortex. A robust increase of activity was observed in the fronto-insular cortex on both hemispheres. Data-driven functional characterization revealed associations with semantic language processing (left lateral prefrontal and fronto-insular cortex), action execution and pain processing (right lateral prefrontal and left fronto-insular), social cognition (dorsomedial prefrontal cortex), and emotional as well as cognitive reward processing (right amygdala and fronto-insular cortex). Aberrant brain activity related to psychopathy is located in prefrontal, insular, and limbic regions. Physiological mental functions fulfilled by these brain regions correspond to disturbed behavioral patterns pathognomonic for psychopathy. Hence, aberrant brain activity may not just be an epiphenomenon of psychopathy but directly related to the psychopathology of this disorder." 30721944,PMC6917521,10.1093/cercor/bhy336,Multimodal Parcellations and Extensive Behavioral Profiling Tackling the Hippocampus Gradient,"['Plachti A', 'Eickhoff SB', 'Hoffstaedter F', 'Patil KR', 'Laird AR', 'Fox PT', 'Amunts K', 'Genon S']",2019,12,17,Cereb Cortex,29,11,4595-4612,"The hippocampus displays a complex organization and function that is perturbed in many neuropathologies. Histological work revealed a complex arrangement of subfields along the medial-lateral and the ventral-dorsal dimension, which contrasts with the anterior-posterior functional differentiation. The variety of maps has raised the need for an integrative multimodal view. We applied connectivity-based parcellation to 1) intrinsic connectivity 2) task-based connectivity, and 3) structural covariance, as complementary windows into structural and functional differentiation of the hippocampus. Strikingly, while functional properties (i.e., intrinsic and task-based) revealed similar partitions dominated by an anterior-posterior organization, structural covariance exhibited a hybrid pattern reflecting both functional and cytoarchitectonic subdivision. Capitalizing on the consistency of functional parcellations, we defined robust functional maps at different levels of partitions, which are openly available for the scientific community. Our functional maps demonstrated a head-body and tail partition, subdivided along the anterior-posterior and medial-lateral axis. Behavioral profiling of these fine partitions based on activation data indicated an emotion-cognition gradient along the anterior-posterior axis and additionally suggested a self-world-centric gradient supporting the role of the hippocampus in the construction of abstract representations for spatial navigation and episodic memory." -30793072,PMC6326731,10.1162/netn_a_00050,Cooperating yet distinct brain networks engaged during naturalistic paradigms: A meta-analysis of functional MRI results,"['Bottenhorn KL', 'Flannery JS', 'Boeving ER', 'Riedel MC', 'Eickhoff SB', 'Sutherland MT', 'Laird AR']",2019,3,17,Netw Neurosci,3,1,27-48,"Cognitive processes do not occur by pure insertion and instead depend on the full complement of co-occurring mental processes, including perceptual and motor functions. As such, there is limited ecological validity to human neuroimaging experiments that use highly controlled tasks to isolate mental processes of interest. However, a growing literature shows how dynamic, interactive tasks have allowed researchers to study cognition as it more naturally occurs. Collective analysis across such neuroimaging experiments may answer broader questions regarding how naturalistic cognition is biologically distributed throughout the brain. We applied an unbiased, data-driven, meta-analytic approach that uses k-means clustering to identify core brain networks engaged across the naturalistic functional neuroimaging literature. Functional decoding allowed us to, then, delineate how information is distributed between these networks throughout the execution of dynamical cognition in realistic settings. This analysis revealed six recurrent patterns of brain activation, representing sensory, domain-specific, and attentional neural networks that support the cognitive demands of naturalistic paradigms. Although gaps in the literature remain, these results suggest that naturalistic fMRI paradigms recruit a common set of networks that allow both separate processing of different streams of information and integration of relevant information to enable flexible cognition and complex behavior." -30793072,PMC6326731,10.1162/netn_a_00050,Cooperating yet distinct brain networks engaged during naturalistic paradigms: A meta-analysis of functional MRI results,"['Bottenhorn KL', 'Flannery JS', 'Boeving ER', 'Riedel MC', 'Eickhoff SB', 'Sutherland MT', 'Laird AR']",2019,3,17,Netw Neurosci,3,1,27-48,"Cognitive processes do not occur by pure insertion and instead depend on the full complement of co-occurring mental processes, including perceptual and motor functions. As such, there is limited ecological validity to human neuroimaging experiments that use highly controlled tasks to isolate mental processes of interest. However, a growing literature shows how dynamic, interactive tasks have allowed researchers to study cognition as it more naturally occurs. Collective analysis across such neuroimaging experiments may answer broader questions regarding how naturalistic cognition is biologically distributed throughout the brain. We applied an unbiased, data-driven, meta-analytic approach that uses k-means clustering to identify core brain networks engaged across the naturalistic functional neuroimaging literature. Functional decoding allowed us to, then, delineate how information is distributed between these networks throughout the execution of dynamical cognition in realistic settings. This analysis revealed six recurrent patterns of brain activation, representing sensory, domain-specific, and attentional neural networks that support the cognitive demands of naturalistic paradigms. Although gaps in the literature remain, these results suggest that naturalistic fMRI paradigms recruit a common set of networks that allow both separate processing of different streams of information and integration of relevant information to enable flexible cognition and complex behavior." -30926513,,10.1016/j.jsxm.2019.02.012,Meta-analytic Evidence for Neural Dysactivity Underlying Sexual Dysfunction,"['Poeppl TB', 'Langguth B', 'Laird AR', 'Eickhoff SB']",2019,5,17,J Sex Med,16,5,614-617,"INTRODUCTION: About 30-40% of the population report sexual dysfunction. Although it is well known that the brain controls sexual behavior, little is known about the neural basis of sexual dysfunction. AIM: To assess convergence of altered brain activity associated with sexual dysfunction across available functional imaging studies. METHODS: We used activation likelihood estimation meta-analysis to quantify interstudy concordance across 14 functional imaging studies reporting 179 foci from 40 individual analyses involving 191 subjects with sexual dysfunction and 123 controls. MAIN OUTCOME MEASURE: Activation likelihood estimation scores were used to assess convergence of findings. RESULTS: Consistently decreased brain activity associated with sexual dysfunction was identified in the dorsal anterior cingulate cortex, ventral striatum, dorsal midbrain, anterior midcingulate cortex, and lateral orbitofrontal cortex. CLINICAL IMPLICATION: These findings can serve as a basis for further studies on the pathophysiology of this highly common disorder with the view to development of more-specific treatment strategies. STRENGTH & LIMITATIONS: Findings are based on an observer-independent meta-analysis that provides robust evidence for and anatomic localization of altered brain activity related to sexual dysfunction. Our analysis cannot distinguish between the putative sources of sexual dysfunction, but it provides a more ubiquitous and general pattern of related altered neural activity. CONCLUSION: The identified regions have previously been shown to be critically involved in mediating sexual arousal and to be part of the sympathetic division of the autonomic nervous system. This suggests that the disturbance of brain activity associated with sexual dysfunction primarily affects sexual arousal already at early stages that are controlled by the sympathetic nervous system. Poeppl TB, Langguth B, Laird AR, et al. Meta-analytic Evidence for Neural Dysactivity Underlying Sexual Dysfunction. J Sex Med 2019;16:614-617." -31063939,,10.1016/j.smrv.2019.03.008,Functional brain alterations in acute sleep deprivation: An activation likelihood estimation meta-analysis,"['Javaheipour N', 'Shahdipour N', 'Noori K', 'Zarei M', 'Camilleri JA', 'Laird AR', 'Fox PT', 'Eickhoff SB', 'Eickhoff CR', 'Rosenzweig I', 'Khazaie H', 'Tahmasian M']",2019,8,17,Sleep Med Rev,46,,64-73,"Sleep deprivation (SD) is a common problem in modern societies, which leads to cognitive dysfunctions including attention lapses, impaired working memory, hindering decision making, impaired emotional processing, and motor vehicle accidents. Numerous neuroimaging studies have investigated the neural correlates of SD, but these studies have reported inconsistent results. Thus, we aimed to identify convergent patterns of abnormal brain functions due to acute SD. Based on the preferred reporting for systematic reviews and meta-analyses statement, we searched the PubMed database and performed reference tracking and finally retrieved 31 eligible functional neuroimaging studies. Then, we applied activation estimation likelihood meta-analysis and found reduced activity mainly in the right intraparietal sulcus and superior parietal lobule. The functional decoding analysis using the BrainMap database indicated that this region is mostly related to visuospatial perception, memory and reasoning. The significant co-activation of this region using the BrainMap database were found in the left superior parietal lobule, intraparietal sulcus, bilateral occipital cortex, left fusiform gyrus and thalamus. This region also connected with the superior parietal lobule, intraparietal sulcus, insula, inferior frontal gyrus, precentral, occipital and cerebellum through resting-state functional connectivity in healthy subjects. Taken together, our findings highlight the role of superior parietal cortex in SD." -31106219,PMC6519462,10.3389/fict.2018.00010,Toward a Neurobiological Basis for Understanding Learning in University Modeling Instruction Physics Courses,"['Brewe E', 'Bartley JE', 'Riedel MC', 'Sawtelle V', 'Salo T', 'Boeving ER', 'Bravo EI', 'Odean R', 'Nazareth A', 'Bottenhorn KL', 'Laird RW', 'Sutherland MT', 'Pruden SM', 'Laird AR']",2018,5,17,Front ICT,5,,,"Modeling Instruction (MI) for University Physics is a curricular and pedagogical approach to active learning in introductory physics. A basic tenet of science is that it is a model-driven endeavor that involves building models, then validating, deploying, and ultimately revising them in an iterative fashion. MI was developed to provide students a facsimile in the university classroom of this foundational scientific practice. As a curriculum, MI employs conceptual scientific models as the basis for the course content, and thus learning in a MI classroom involves students appropriating scientific models for their own use. Over the last 10 years, substantial evidence has accumulated supporting MI's efficacy, including gains in conceptual understanding, odds of success, attitudes toward learning, self-efficacy, and social networks centered around physics learning. However, we still do not fully understand the mechanisms of how students learn physics and develop mental models of physical phenomena. Herein, we explore the hypothesis that the MI curriculum and pedagogy promotes student engagement via conceptual model building. This emphasis on conceptual model building, in turn, leads to improved knowledge organization and problem solving abilities that manifest as quantifiable functional brain changes that can be assessed with functional magnetic resonance imaging (fMRI). We conducted a neuroeducation study wherein students completed a physics reasoning task while undergoing fMRI scanning before (pre) and after (post) completing a MI introductory physics course. Preliminary results indicated that performance of the physics reasoning task was linked with increased brain activity notably in lateral prefrontal and parietal cortices that previously have been associated with attention, working memory, and problem solving, and are collectively referred to as the central executive network. Critically, assessment of changes in brain activity during the physics reasoning task from pre- vs. post-instruction identified increased activity after the course notably in the posterior cingulate cortex (a brain region previously linked with episodic memory and self-referential thought) and in the frontal poles (regions linked with learning). These preliminary outcomes highlight brain regions linked with physics reasoning and, critically, suggest that brain activity during physics reasoning is modifiable by thoughtfully designed curriculum and pedagogy." -31106219,PMC6519462,10.3389/fict.2018.00010,Toward a Neurobiological Basis for Understanding Learning in University Modeling Instruction Physics Courses,"['Brewe E', 'Bartley JE', 'Riedel MC', 'Sawtelle V', 'Salo T', 'Boeving ER', 'Bravo EI', 'Odean R', 'Nazareth A', 'Bottenhorn KL', 'Laird RW', 'Sutherland MT', 'Pruden SM', 'Laird AR']",2018,5,17,Front ICT,5,,,"Modeling Instruction (MI) for University Physics is a curricular and pedagogical approach to active learning in introductory physics. A basic tenet of science is that it is a model-driven endeavor that involves building models, then validating, deploying, and ultimately revising them in an iterative fashion. MI was developed to provide students a facsimile in the university classroom of this foundational scientific practice. As a curriculum, MI employs conceptual scientific models as the basis for the course content, and thus learning in a MI classroom involves students appropriating scientific models for their own use. Over the last 10 years, substantial evidence has accumulated supporting MI's efficacy, including gains in conceptual understanding, odds of success, attitudes toward learning, self-efficacy, and social networks centered around physics learning. However, we still do not fully understand the mechanisms of how students learn physics and develop mental models of physical phenomena. Herein, we explore the hypothesis that the MI curriculum and pedagogy promotes student engagement via conceptual model building. This emphasis on conceptual model building, in turn, leads to improved knowledge organization and problem solving abilities that manifest as quantifiable functional brain changes that can be assessed with functional magnetic resonance imaging (fMRI). We conducted a neuroeducation study wherein students completed a physics reasoning task while undergoing fMRI scanning before (pre) and after (post) completing a MI introductory physics course. Preliminary results indicated that performance of the physics reasoning task was linked with increased brain activity notably in lateral prefrontal and parietal cortices that previously have been associated with attention, working memory, and problem solving, and are collectively referred to as the central executive network. Critically, assessment of changes in brain activity during the physics reasoning task from pre- vs. post-instruction identified increased activity after the course notably in the posterior cingulate cortex (a brain region previously linked with episodic memory and self-referential thought) and in the frontal poles (regions linked with learning). These preliminary outcomes highlight brain regions linked with physics reasoning and, critically, suggest that brain activity during physics reasoning is modifiable by thoughtfully designed curriculum and pedagogy." -31110341,,10.1038/s41562-019-0609-3,No evidence for a bilingual executive function advantage in the nationally representative ABCD study,"['Dick AS', 'Garcia NL', 'Pruden SM', 'Thompson WK', 'Hawes SW', 'Sutherland MT', 'Riedel MC', 'Laird AR', 'Gonzalez R']",2019,7,17,Nat Hum Behav,3,7,692-701,"Learning a second language in childhood is inherently advantageous for communication. However, parents, educators and scientists have been interested in determining whether there are additional cognitive advantages. One of the most exciting yet controversial(1) findings about bilinguals is a reported advantage for executive function. That is, several studies suggest that bilinguals perform better than monolinguals on tasks assessing cognitive abilities that are central to the voluntary control of thoughts and behaviours-the so-called 'executive functions' (for example, attention, inhibitory control, task switching and resolving conflict). Although a number of small-(2-4) and large-sample(5,6) studies have reported a bilingual executive function advantage (see refs. (7-9) for a review), there have been several failures to replicate these findings(10-15), and recent meta-analyses have called into question the reliability of the original empirical claims(8,9). Here we show, in a very large, demographically representative sample (n = 4,524) of 9- to 10-year-olds across the United States, that there is little evidence for a bilingual advantage for inhibitory control, attention and task switching, or cognitive flexibility, which are key aspects of executive function. We also replicate previously reported disadvantages in English vocabulary in bilinguals(7,16,17). However, these English vocabulary differences are substantially mitigated when we account for individual differences in socioeconomic status or intelligence. In summary, notwithstanding the inherently positive benefits of learning a second language in childhood(18), we found little evidence that it engenders additional benefits to executive function development." -31110341,,10.1038/s41562-019-0609-3,No evidence for a bilingual executive function advantage in the nationally representative ABCD study,"['Dick AS', 'Garcia NL', 'Pruden SM', 'Thompson WK', 'Hawes SW', 'Sutherland MT', 'Riedel MC', 'Laird AR', 'Gonzalez R']",2019,7,17,Nat Hum Behav,3,7,692-701,"Learning a second language in childhood is inherently advantageous for communication. However, parents, educators and scientists have been interested in determining whether there are additional cognitive advantages. One of the most exciting yet controversial(1) findings about bilinguals is a reported advantage for executive function. That is, several studies suggest that bilinguals perform better than monolinguals on tasks assessing cognitive abilities that are central to the voluntary control of thoughts and behaviours-the so-called 'executive functions' (for example, attention, inhibitory control, task switching and resolving conflict). Although a number of small-(2-4) and large-sample(5,6) studies have reported a bilingual executive function advantage (see refs. (7-9) for a review), there have been several failures to replicate these findings(10-15), and recent meta-analyses have called into question the reliability of the original empirical claims(8,9). Here we show, in a very large, demographically representative sample (n = 4,524) of 9- to 10-year-olds across the United States, that there is little evidence for a bilingual advantage for inhibitory control, attention and task switching, or cognitive flexibility, which are key aspects of executive function. We also replicate previously reported disadvantages in English vocabulary in bilinguals(7,16,17). However, these English vocabulary differences are substantially mitigated when we account for individual differences in socioeconomic status or intelligence. In summary, notwithstanding the inherently positive benefits of learning a second language in childhood(18), we found little evidence that it engenders additional benefits to executive function development." -31120281,PMC6663642,10.1037/pha0000281,Effects of cannabinoid administration for pain: A meta-analysis and meta-regression,"['Yanes JA', 'McKinnell ZE', 'Reid MA', 'Busler JN', 'Michel JS', 'Pangelinan MM', 'Sutherland MT', 'Younger JW', 'Gonzalez R', 'Robinson JL']",2019,8,17,Exp Clin Psychopharmacol,27,4,370-382,"Chronic pain states have resulted in an overreliance on opioid pain relievers, which can carry significant risks when used long term. As such, alternative pain treatments are increasingly desired. Although emerging research suggests that cannabinoids have therapeutic potential regarding pain, results from studies across pain populations have been inconsistent. To provide meta-analytic clarification regarding cannabis's impact on subjective pain, we identified studies that assessed drug-induced pain modulations under cannabinoid and corresponding placebo conditions. A literature search yielded 25 peer-reviewed records that underwent data extraction. Baseline and end-point data were used to compute standardized effect size estimates (Cohen's d) across cannabinoid administrations (k = 39) and placebo administrations (k = 26). Standardized effects were inverse-variance weighted and pooled across studies for meta-analytic comparison. Results revealed that cannabinoid administration produced a medium-to-large effect across included studies, Cohen's d = -0.58, 95% confidence interval (CI) [-0.74, -0.43], while placebo administration produced a small-to-medium effect, Cohen's d = -0.39, 95% CI [-0.52, -0.26]. Meta-regression revealed that cannabinoids, beta = -0.43, 95% CI [-0.62, -0.24], p < .05, synthetic cannabinoids, beta = -0.39, 95% CI [-0.65, -0.14], p < .05, and sample size, beta = 0.01, 95% CI [0.00, 0.01], p < .05, were associated with marked pain reduction. These outcomes suggest that cannabinoid-based pharmacotherapies may serve as effective replacement/adjunctive options regarding pain, however, additional research is warranted. Additionally, given demonstrated neurocognitive side effects associated with some constituent cannabinoids (i.e., THC), subsequent work may consider developing novel therapeutic agents that capitalize on cannabis's analgesic properties without producing adverse effects. (PsycINFO Database Record (c) 2019 APA, all rights reserved)." -31156374,PMC6530419,10.3389/fnins.2019.00494,"Automated, Efficient, and Accelerated Knowledge Modeling of the Cognitive Neuroimaging Literature Using the ATHENA Toolkit","['Riedel MC', 'Salo T', 'Hays J', 'Turner MD', 'Sutherland MT', 'Turner JA', 'Laird AR']",2019,3,17,Front Neurosci,13,,494,"Neuroimaging research is growing rapidly, providing expansive resources for synthesizing data. However, navigating these dense resources is complicated by the volume of research articles and variety of experimental designs implemented across studies. The advent of machine learning algorithms and text-mining techniques has advanced automated labeling of published articles in biomedical research to alleviate such obstacles. As of yet, a comprehensive examination of document features and classifier techniques for annotating neuroimaging articles has yet to be undertaken. Here, we evaluated which combination of corpus (abstract-only or full-article text), features (bag-of-words or Cognitive Atlas terms), and classifier (Bernoulli naive Bayes, k-nearest neighbors, logistic regression, or support vector classifier) resulted in the highest predictive performance in annotating a selection of 2,633 manually annotated neuroimaging articles. We found that, when utilizing full article text, data-driven features derived from the text performed the best, whereas if article abstracts were used for annotation, features derived from the Cognitive Atlas performed better. Additionally, we observed that when features were derived from article text, anatomical terms appeared to be the most frequently utilized for classification purposes and that cognitive concepts can be identified based on similar representations of these anatomical terms. Optimizing parameters for the automated classification of neuroimaging articles may result in a larger proportion of the neuroimaging literature being annotated with labels supporting the meta-analysis of psychological constructs." -31156374,PMC6530419,10.3389/fnins.2019.00494,"Automated, Efficient, and Accelerated Knowledge Modeling of the Cognitive Neuroimaging Literature Using the ATHENA Toolkit","['Riedel MC', 'Salo T', 'Hays J', 'Turner MD', 'Sutherland MT', 'Turner JA', 'Laird AR']",2019,3,17,Front Neurosci,13,,494,"Neuroimaging research is growing rapidly, providing expansive resources for synthesizing data. However, navigating these dense resources is complicated by the volume of research articles and variety of experimental designs implemented across studies. The advent of machine learning algorithms and text-mining techniques has advanced automated labeling of published articles in biomedical research to alleviate such obstacles. As of yet, a comprehensive examination of document features and classifier techniques for annotating neuroimaging articles has yet to be undertaken. Here, we evaluated which combination of corpus (abstract-only or full-article text), features (bag-of-words or Cognitive Atlas terms), and classifier (Bernoulli naive Bayes, k-nearest neighbors, logistic regression, or support vector classifier) resulted in the highest predictive performance in annotating a selection of 2,633 manually annotated neuroimaging articles. We found that, when utilizing full article text, data-driven features derived from the text performed the best, whereas if article abstracts were used for annotation, features derived from the Cognitive Atlas performed better. Additionally, we observed that when features were derived from article text, anatomical terms appeared to be the most frequently utilized for classification purposes and that cognitive concepts can be identified based on similar representations of these anatomical terms. Optimizing parameters for the automated classification of neuroimaging articles may result in a larger proportion of the neuroimaging literature being annotated with labels supporting the meta-analysis of psychological constructs." +30793072,PMC6326731,10.1162/netn_a_00050,Cooperating yet distinct brain networks engaged during naturalistic paradigms: A meta-analysis of functional MRI results,"['Bottenhorn KL', 'Flannery JS', 'Boeving ER', 'Riedel MC', 'Eickhoff SB', 'Sutherland MT', 'Laird AR']",2019,6,8,Netw Neurosci,3,1,27-48,"Cognitive processes do not occur by pure insertion and instead depend on the full complement of co-occurring mental processes, including perceptual and motor functions. As such, there is limited ecological validity to human neuroimaging experiments that use highly controlled tasks to isolate mental processes of interest. However, a growing literature shows how dynamic, interactive tasks have allowed researchers to study cognition as it more naturally occurs. Collective analysis across such neuroimaging experiments may answer broader questions regarding how naturalistic cognition is biologically distributed throughout the brain. We applied an unbiased, data-driven, meta-analytic approach that uses k-means clustering to identify core brain networks engaged across the naturalistic functional neuroimaging literature. Functional decoding allowed us to, then, delineate how information is distributed between these networks throughout the execution of dynamical cognition in realistic settings. This analysis revealed six recurrent patterns of brain activation, representing sensory, domain-specific, and attentional neural networks that support the cognitive demands of naturalistic paradigms. Although gaps in the literature remain, these results suggest that naturalistic fMRI paradigms recruit a common set of networks that allow both separate processing of different streams of information and integration of relevant information to enable flexible cognition and complex behavior." +30793072,PMC6326731,10.1162/netn_a_00050,Cooperating yet distinct brain networks engaged during naturalistic paradigms: A meta-analysis of functional MRI results,"['Bottenhorn KL', 'Flannery JS', 'Boeving ER', 'Riedel MC', 'Eickhoff SB', 'Sutherland MT', 'Laird AR']",2019,6,8,Netw Neurosci,3,1,27-48,"Cognitive processes do not occur by pure insertion and instead depend on the full complement of co-occurring mental processes, including perceptual and motor functions. As such, there is limited ecological validity to human neuroimaging experiments that use highly controlled tasks to isolate mental processes of interest. However, a growing literature shows how dynamic, interactive tasks have allowed researchers to study cognition as it more naturally occurs. Collective analysis across such neuroimaging experiments may answer broader questions regarding how naturalistic cognition is biologically distributed throughout the brain. We applied an unbiased, data-driven, meta-analytic approach that uses k-means clustering to identify core brain networks engaged across the naturalistic functional neuroimaging literature. Functional decoding allowed us to, then, delineate how information is distributed between these networks throughout the execution of dynamical cognition in realistic settings. This analysis revealed six recurrent patterns of brain activation, representing sensory, domain-specific, and attentional neural networks that support the cognitive demands of naturalistic paradigms. Although gaps in the literature remain, these results suggest that naturalistic fMRI paradigms recruit a common set of networks that allow both separate processing of different streams of information and integration of relevant information to enable flexible cognition and complex behavior." +30926513,PMC7211028,10.1016/j.jsxm.2019.02.012,Meta-analytic Evidence for Neural Dysactivity Underlying Sexual Dysfunction,"['Poeppl TB', 'Langguth B', 'Laird AR', 'Eickhoff SB']",2019,5,8,J Sex Med,16,5,614-617,"INTRODUCTION: About 30-40% of the population report sexual dysfunction. Although it is well known that the brain controls sexual behavior, little is known about the neural basis of sexual dysfunction. AIM: To assess convergence of altered brain activity associated with sexual dysfunction across available functional imaging studies. METHODS: We used activation likelihood estimation meta-analysis to quantify interstudy concordance across 14 functional imaging studies reporting 179 foci from 40 individual analyses involving 191 subjects with sexual dysfunction and 123 controls. MAIN OUTCOME MEASURE: Activation likelihood estimation scores were used to assess convergence of findings. RESULTS: Consistently decreased brain activity associated with sexual dysfunction was identified in the dorsal anterior cingulate cortex, ventral striatum, dorsal midbrain, anterior midcingulate cortex, and lateral orbitofrontal cortex. CLINICAL IMPLICATION: These findings can serve as a basis for further studies on the pathophysiology of this highly common disorder with the view to development of more-specific treatment strategies. STRENGTH & LIMITATIONS: Findings are based on an observer-independent meta-analysis that provides robust evidence for and anatomic localization of altered brain activity related to sexual dysfunction. Our analysis cannot distinguish between the putative sources of sexual dysfunction, but it provides a more ubiquitous and general pattern of related altered neural activity. CONCLUSION: The identified regions have previously been shown to be critically involved in mediating sexual arousal and to be part of the sympathetic division of the autonomic nervous system. This suggests that the disturbance of brain activity associated with sexual dysfunction primarily affects sexual arousal already at early stages that are controlled by the sympathetic nervous system. Poeppl TB, Langguth B, Laird AR, et al. Meta-analytic Evidence for Neural Dysactivity Underlying Sexual Dysfunction. J Sex Med 2019;16:614-617." +31063939,,10.1016/j.smrv.2019.03.008,Functional brain alterations in acute sleep deprivation: An activation likelihood estimation meta-analysis,"['Javaheripour N', 'Shahdipour N', 'Noori K', 'Zarei M', 'Camilleri JA', 'Laird AR', 'Fox PT', 'Eickhoff SB', 'Eickhoff CR', 'Rosenzweig I', 'Khazaie H', 'Tahmasian M']",2019,8,8,Sleep Med Rev,46,,64-73,"Sleep deprivation (SD) is a common problem in modern societies, which leads to cognitive dysfunctions including attention lapses, impaired working memory, hindering decision making, impaired emotional processing, and motor vehicle accidents. Numerous neuroimaging studies have investigated the neural correlates of SD, but these studies have reported inconsistent results. Thus, we aimed to identify convergent patterns of abnormal brain functions due to acute SD. Based on the preferred reporting for systematic reviews and meta-analyses statement, we searched the PubMed database and performed reference tracking and finally retrieved 31 eligible functional neuroimaging studies. Then, we applied activation estimation likelihood meta-analysis and found reduced activity mainly in the right intraparietal sulcus and superior parietal lobule. The functional decoding analysis using the BrainMap database indicated that this region is mostly related to visuospatial perception, memory and reasoning. The significant co-activation of this region using the BrainMap database were found in the left superior parietal lobule, intraparietal sulcus, bilateral occipital cortex, left fusiform gyrus and thalamus. This region also connected with the superior parietal lobule, intraparietal sulcus, insula, inferior frontal gyrus, precentral, occipital and cerebellum through resting-state functional connectivity in healthy subjects. Taken together, our findings highlight the role of superior parietal cortex in SD." +31106219,PMC6519462,10.3389/fict.2018.00010,Toward a Neurobiological Basis for Understanding Learning in University Modeling Instruction Physics Courses,"['Brewe E', 'Bartley JE', 'Riedel MC', 'Sawtelle V', 'Salo T', 'Boeving ER', 'Bravo EI', 'Odean R', 'Nazareth A', 'Bottenhorn KL', 'Laird RW', 'Sutherland MT', 'Pruden SM', 'Laird AR']",2018,5,8,Front ICT,5,,,"Modeling Instruction (MI) for University Physics is a curricular and pedagogical approach to active learning in introductory physics. A basic tenet of science is that it is a model-driven endeavor that involves building models, then validating, deploying, and ultimately revising them in an iterative fashion. MI was developed to provide students a facsimile in the university classroom of this foundational scientific practice. As a curriculum, MI employs conceptual scientific models as the basis for the course content, and thus learning in a MI classroom involves students appropriating scientific models for their own use. Over the last 10 years, substantial evidence has accumulated supporting MI's efficacy, including gains in conceptual understanding, odds of success, attitudes toward learning, self-efficacy, and social networks centered around physics learning. However, we still do not fully understand the mechanisms of how students learn physics and develop mental models of physical phenomena. Herein, we explore the hypothesis that the MI curriculum and pedagogy promotes student engagement via conceptual model building. This emphasis on conceptual model building, in turn, leads to improved knowledge organization and problem solving abilities that manifest as quantifiable functional brain changes that can be assessed with functional magnetic resonance imaging (fMRI). We conducted a neuroeducation study wherein students completed a physics reasoning task while undergoing fMRI scanning before (pre) and after (post) completing a MI introductory physics course. Preliminary results indicated that performance of the physics reasoning task was linked with increased brain activity notably in lateral prefrontal and parietal cortices that previously have been associated with attention, working memory, and problem solving, and are collectively referred to as the central executive network. Critically, assessment of changes in brain activity during the physics reasoning task from pre- vs. post-instruction identified increased activity after the course notably in the posterior cingulate cortex (a brain region previously linked with episodic memory and self-referential thought) and in the frontal poles (regions linked with learning). These preliminary outcomes highlight brain regions linked with physics reasoning and, critically, suggest that brain activity during physics reasoning is modifiable by thoughtfully designed curriculum and pedagogy." +31106219,PMC6519462,10.3389/fict.2018.00010,Toward a Neurobiological Basis for Understanding Learning in University Modeling Instruction Physics Courses,"['Brewe E', 'Bartley JE', 'Riedel MC', 'Sawtelle V', 'Salo T', 'Boeving ER', 'Bravo EI', 'Odean R', 'Nazareth A', 'Bottenhorn KL', 'Laird RW', 'Sutherland MT', 'Pruden SM', 'Laird AR']",2018,5,8,Front ICT,5,,,"Modeling Instruction (MI) for University Physics is a curricular and pedagogical approach to active learning in introductory physics. A basic tenet of science is that it is a model-driven endeavor that involves building models, then validating, deploying, and ultimately revising them in an iterative fashion. MI was developed to provide students a facsimile in the university classroom of this foundational scientific practice. As a curriculum, MI employs conceptual scientific models as the basis for the course content, and thus learning in a MI classroom involves students appropriating scientific models for their own use. Over the last 10 years, substantial evidence has accumulated supporting MI's efficacy, including gains in conceptual understanding, odds of success, attitudes toward learning, self-efficacy, and social networks centered around physics learning. However, we still do not fully understand the mechanisms of how students learn physics and develop mental models of physical phenomena. Herein, we explore the hypothesis that the MI curriculum and pedagogy promotes student engagement via conceptual model building. This emphasis on conceptual model building, in turn, leads to improved knowledge organization and problem solving abilities that manifest as quantifiable functional brain changes that can be assessed with functional magnetic resonance imaging (fMRI). We conducted a neuroeducation study wherein students completed a physics reasoning task while undergoing fMRI scanning before (pre) and after (post) completing a MI introductory physics course. Preliminary results indicated that performance of the physics reasoning task was linked with increased brain activity notably in lateral prefrontal and parietal cortices that previously have been associated with attention, working memory, and problem solving, and are collectively referred to as the central executive network. Critically, assessment of changes in brain activity during the physics reasoning task from pre- vs. post-instruction identified increased activity after the course notably in the posterior cingulate cortex (a brain region previously linked with episodic memory and self-referential thought) and in the frontal poles (regions linked with learning). These preliminary outcomes highlight brain regions linked with physics reasoning and, critically, suggest that brain activity during physics reasoning is modifiable by thoughtfully designed curriculum and pedagogy." +31110341,PMC7156280,10.1038/s41562-019-0609-3,No evidence for a bilingual executive function advantage in the nationally representative ABCD study,"['Dick AS', 'Garcia NL', 'Pruden SM', 'Thompson WK', 'Hawes SW', 'Sutherland MT', 'Riedel MC', 'Laird AR', 'Gonzalez R']",2019,7,8,Nat Hum Behav,3,7,692-701,"Learning a second language in childhood is inherently advantageous for communication. However, parents, educators and scientists have been interested in determining whether there are additional cognitive advantages. One of the most exciting yet controversial(1) findings about bilinguals is a reported advantage for executive function. That is, several studies suggest that bilinguals perform better than monolinguals on tasks assessing cognitive abilities that are central to the voluntary control of thoughts and behaviours-the so-called 'executive functions' (for example, attention, inhibitory control, task switching and resolving conflict). Although a number of small-(2-4) and large-sample(5,6) studies have reported a bilingual executive function advantage (see refs. (7-9) for a review), there have been several failures to replicate these findings(10-15), and recent meta-analyses have called into question the reliability of the original empirical claims(8,9). Here we show, in a very large, demographically representative sample (n = 4,524) of 9- to 10-year-olds across the United States, that there is little evidence for a bilingual advantage for inhibitory control, attention and task switching, or cognitive flexibility, which are key aspects of executive function. We also replicate previously reported disadvantages in English vocabulary in bilinguals(7,16,17). However, these English vocabulary differences are substantially mitigated when we account for individual differences in socioeconomic status or intelligence. In summary, notwithstanding the inherently positive benefits of learning a second language in childhood(18), we found little evidence that it engenders additional benefits to executive function development." +31110341,PMC7156280,10.1038/s41562-019-0609-3,No evidence for a bilingual executive function advantage in the nationally representative ABCD study,"['Dick AS', 'Garcia NL', 'Pruden SM', 'Thompson WK', 'Hawes SW', 'Sutherland MT', 'Riedel MC', 'Laird AR', 'Gonzalez R']",2019,7,8,Nat Hum Behav,3,7,692-701,"Learning a second language in childhood is inherently advantageous for communication. However, parents, educators and scientists have been interested in determining whether there are additional cognitive advantages. One of the most exciting yet controversial(1) findings about bilinguals is a reported advantage for executive function. That is, several studies suggest that bilinguals perform better than monolinguals on tasks assessing cognitive abilities that are central to the voluntary control of thoughts and behaviours-the so-called 'executive functions' (for example, attention, inhibitory control, task switching and resolving conflict). Although a number of small-(2-4) and large-sample(5,6) studies have reported a bilingual executive function advantage (see refs. (7-9) for a review), there have been several failures to replicate these findings(10-15), and recent meta-analyses have called into question the reliability of the original empirical claims(8,9). Here we show, in a very large, demographically representative sample (n = 4,524) of 9- to 10-year-olds across the United States, that there is little evidence for a bilingual advantage for inhibitory control, attention and task switching, or cognitive flexibility, which are key aspects of executive function. We also replicate previously reported disadvantages in English vocabulary in bilinguals(7,16,17). However, these English vocabulary differences are substantially mitigated when we account for individual differences in socioeconomic status or intelligence. In summary, notwithstanding the inherently positive benefits of learning a second language in childhood(18), we found little evidence that it engenders additional benefits to executive function development." +31120281,PMC6663642,10.1037/pha0000281,Effects of cannabinoid administration for pain: A meta-analysis and meta-regression,"['Yanes JA', 'McKinnell ZE', 'Reid MA', 'Busler JN', 'Michel JS', 'Pangelinan MM', 'Sutherland MT', 'Younger JW', 'Gonzalez R', 'Robinson JL']",2019,8,8,Exp Clin Psychopharmacol,27,4,370-382,"Chronic pain states have resulted in an overreliance on opioid pain relievers, which can carry significant risks when used long term. As such, alternative pain treatments are increasingly desired. Although emerging research suggests that cannabinoids have therapeutic potential regarding pain, results from studies across pain populations have been inconsistent. To provide meta-analytic clarification regarding cannabis's impact on subjective pain, we identified studies that assessed drug-induced pain modulations under cannabinoid and corresponding placebo conditions. A literature search yielded 25 peer-reviewed records that underwent data extraction. Baseline and end-point data were used to compute standardized effect size estimates (Cohen's d) across cannabinoid administrations (k = 39) and placebo administrations (k = 26). Standardized effects were inverse-variance weighted and pooled across studies for meta-analytic comparison. Results revealed that cannabinoid administration produced a medium-to-large effect across included studies, Cohen's d = -0.58, 95% confidence interval (CI) [-0.74, -0.43], while placebo administration produced a small-to-medium effect, Cohen's d = -0.39, 95% CI [-0.52, -0.26]. Meta-regression revealed that cannabinoids, beta = -0.43, 95% CI [-0.62, -0.24], p < .05, synthetic cannabinoids, beta = -0.39, 95% CI [-0.65, -0.14], p < .05, and sample size, beta = 0.01, 95% CI [0.00, 0.01], p < .05, were associated with marked pain reduction. These outcomes suggest that cannabinoid-based pharmacotherapies may serve as effective replacement/adjunctive options regarding pain, however, additional research is warranted. Additionally, given demonstrated neurocognitive side effects associated with some constituent cannabinoids (i.e., THC), subsequent work may consider developing novel therapeutic agents that capitalize on cannabis's analgesic properties without producing adverse effects. (PsycINFO Database Record (c) 2019 APA, all rights reserved)." +31156374,PMC6530419,10.3389/fnins.2019.00494,"Automated, Efficient, and Accelerated Knowledge Modeling of the Cognitive Neuroimaging Literature Using the ATHENA Toolkit","['Riedel MC', 'Salo T', 'Hays J', 'Turner MD', 'Sutherland MT', 'Turner JA', 'Laird AR']",2019,6,8,Front Neurosci,13,,494,"Neuroimaging research is growing rapidly, providing expansive resources for synthesizing data. However, navigating these dense resources is complicated by the volume of research articles and variety of experimental designs implemented across studies. The advent of machine learning algorithms and text-mining techniques has advanced automated labeling of published articles in biomedical research to alleviate such obstacles. As of yet, a comprehensive examination of document features and classifier techniques for annotating neuroimaging articles has yet to be undertaken. Here, we evaluated which combination of corpus (abstract-only or full-article text), features (bag-of-words or Cognitive Atlas terms), and classifier (Bernoulli naive Bayes, k-nearest neighbors, logistic regression, or support vector classifier) resulted in the highest predictive performance in annotating a selection of 2,633 manually annotated neuroimaging articles. We found that, when utilizing full article text, data-driven features derived from the text performed the best, whereas if article abstracts were used for annotation, features derived from the Cognitive Atlas performed better. Additionally, we observed that when features were derived from article text, anatomical terms appeared to be the most frequently utilized for classification purposes and that cognitive concepts can be identified based on similar representations of these anatomical terms. Optimizing parameters for the automated classification of neuroimaging articles may result in a larger proportion of the neuroimaging literature being annotated with labels supporting the meta-analysis of psychological constructs." +31156374,PMC6530419,10.3389/fnins.2019.00494,"Automated, Efficient, and Accelerated Knowledge Modeling of the Cognitive Neuroimaging Literature Using the ATHENA Toolkit","['Riedel MC', 'Salo T', 'Hays J', 'Turner MD', 'Sutherland MT', 'Turner JA', 'Laird AR']",2019,6,8,Front Neurosci,13,,494,"Neuroimaging research is growing rapidly, providing expansive resources for synthesizing data. However, navigating these dense resources is complicated by the volume of research articles and variety of experimental designs implemented across studies. The advent of machine learning algorithms and text-mining techniques has advanced automated labeling of published articles in biomedical research to alleviate such obstacles. As of yet, a comprehensive examination of document features and classifier techniques for annotating neuroimaging articles has yet to be undertaken. Here, we evaluated which combination of corpus (abstract-only or full-article text), features (bag-of-words or Cognitive Atlas terms), and classifier (Bernoulli naive Bayes, k-nearest neighbors, logistic regression, or support vector classifier) resulted in the highest predictive performance in annotating a selection of 2,633 manually annotated neuroimaging articles. We found that, when utilizing full article text, data-driven features derived from the text performed the best, whereas if article abstracts were used for annotation, features derived from the Cognitive Atlas performed better. Additionally, we observed that when features were derived from article text, anatomical terms appeared to be the most frequently utilized for classification purposes and that cognitive concepts can be identified based on similar representations of these anatomical terms. Optimizing parameters for the automated classification of neuroimaging articles may result in a larger proportion of the neuroimaging literature being annotated with labels supporting the meta-analysis of psychological constructs." 31313451,,10.1002/hbm.24716,Brain-based ranking of cognitive domains to predict schizophrenia,"['Karrer TM', 'Bassett DS', 'Derntl B', 'Gruber O', 'Aleman A', 'Jardri R', 'Laird AR', 'Fox PT', 'Eickhoff SB', 'Grisel O', 'Varoquaux G', 'Thirion B', 'Bzdok D']",2019,10,15,Hum Brain Mapp,40,15,4487-4507,"Schizophrenia is a devastating brain disorder that disturbs sensory perception, motor action, and abstract thought. Its clinical phenotype implies dysfunction of various mental domains, which has motivated a series of theories regarding the underlying pathophysiology. Aiming at a predictive benchmark of a catalog of cognitive functions, we developed a data-driven machine-learning strategy and provide a proof of principle in a multisite clinical dataset (n = 324). Existing neuroscientific knowledge on diverse cognitive domains was first condensed into neurotopographical maps. We then examined how the ensuing meta-analytic cognitive priors can distinguish patients and controls using brain morphology and intrinsic functional connectivity. Some affected cognitive domains supported well-studied directions of research on auditory evaluation and social cognition. However, rarely suspected cognitive domains also emerged as disease relevant, including self-oriented processing of bodily sensations in gustation and pain. Such algorithmic charting of the cognitive landscape can be used to make targeted recommendations for future mental health research." 31415884,PMC6981278,10.1016/j.neuroimage.2019.116091,Image processing and analysis methods for the Adolescent Brain Cognitive Development Study,"['Hagler DJ Jr', 'Hatton S', 'Cornejo MD', 'Makowski C', 'Fair DA', 'Dick AS', 'Sutherland MT', 'Casey BJ', 'Barch DM', 'Harms MP', 'Watts R', 'Bjork JM', 'Garavan HP', 'Hilmer L', 'Pung CJ', 'Sicat CS', 'Kuperman J', 'Bartsch H', 'Xue F', 'Heitzeg MM', 'Laird AR', 'Trinh TT', 'Gonzalez R', 'Tapert SF', 'Riedel MC', 'Squeglia LM', 'Hyde LW', 'Rosenberg MD', 'Earl EA', 'Howlett KD', 'Baker FC', 'Soules M', 'Diaz J', 'de Leon OR', 'Thompson WK', 'Neale MC', 'Herting M', 'Sowell ER', 'Alvarez RP', 'Hawes SW', 'Sanchez M', 'Bodurka J', 'Breslin FJ', 'Morris AS', 'Paulus MP', 'Simmons WK', 'Polimeni JR', 'van der Kouwe A', 'Nencka AS', 'Gray KM', 'Pierpaoli C', 'Matochik JA', 'Noronha A', 'Aklin WM', 'Conway K', 'Glantz M', 'Hoffman E', 'Little R', 'Lopez M', 'Pariyadath V', 'Weiss SR', 'Wolff-Hughes DL', 'DelCarmen-Wiggins R', 'Feldstein Ewing SW', 'Miranda-Dominguez O', 'Nagel BJ', 'Perrone AJ', 'Sturgeon DT', 'Goldstone A', 'Pfefferbaum A', 'Pohl KM', 'Prouty D', 'Uban K', 'Bookheimer SY', 'Dapretto M', 'Galvan A', 'Bagot K', 'Giedd J', 'Infante MA', 'Jacobus J', 'Patrick K', 'Shilling PD', 'Desikan R', 'Li Y', 'Sugrue L', 'Banich MT', 'Friedman N', 'Hewitt JK', 'Hopfer C', 'Sakai J', 'Tanabe J', 'Cottler LB', 'Nixon SJ', 'Chang L', 'Cloak C', 'Ernst T', 'Reeves G', 'Kennedy DN', 'Heeringa S', 'Peltier S', 'Schulenberg J', 'Sripada C', 'Zucker RA', 'Iacono WG', 'Luciana M', 'Calabro FJ', 'Clark DB', 'Lewis DA', 'Luna B', 'Schirda C', 'Brima T', 'Foxe JJ', 'Freedman EG', 'Mruzek DW', 'Mason MJ', 'Huber R', 'McGlade E', 'Prescot A', 'Renshaw PF', 'Yurgelun-Todd DA', 'Allgaier NA', 'Dumas JA', 'Ivanova M', 'Potter A', 'Florsheim P', 'Larson C', 'Lisdahl K', 'Charness ME', 'Fuemmeler B', 'Hettema JM', 'Maes HH', 'Steinberg J', 'Anokhin AP', 'Glaser P', 'Heath AC', 'Madden PA', 'Baskin-Sommers A', 'Constable RT', 'Grant SJ', 'Dowling GJ', 'Brown SA', 'Jernigan TL', 'Dale AM']",2019,11,15,Neuroimage,202,,116091,"The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data is a resource of unprecedented scale and depth for studying typical and atypical development. The aim of this manuscript is to describe the baseline neuroimaging processing and subject-level analysis methods used by ABCD. Processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI. This manuscript serves as a methodological reference for users of publicly shared neuroimaging data from the ABCD Study." 31415884,PMC6981278,10.1016/j.neuroimage.2019.116091,Image processing and analysis methods for the Adolescent Brain Cognitive Development Study,"['Hagler DJ Jr', 'Hatton S', 'Cornejo MD', 'Makowski C', 'Fair DA', 'Dick AS', 'Sutherland MT', 'Casey BJ', 'Barch DM', 'Harms MP', 'Watts R', 'Bjork JM', 'Garavan HP', 'Hilmer L', 'Pung CJ', 'Sicat CS', 'Kuperman J', 'Bartsch H', 'Xue F', 'Heitzeg MM', 'Laird AR', 'Trinh TT', 'Gonzalez R', 'Tapert SF', 'Riedel MC', 'Squeglia LM', 'Hyde LW', 'Rosenberg MD', 'Earl EA', 'Howlett KD', 'Baker FC', 'Soules M', 'Diaz J', 'de Leon OR', 'Thompson WK', 'Neale MC', 'Herting M', 'Sowell ER', 'Alvarez RP', 'Hawes SW', 'Sanchez M', 'Bodurka J', 'Breslin FJ', 'Morris AS', 'Paulus MP', 'Simmons WK', 'Polimeni JR', 'van der Kouwe A', 'Nencka AS', 'Gray KM', 'Pierpaoli C', 'Matochik JA', 'Noronha A', 'Aklin WM', 'Conway K', 'Glantz M', 'Hoffman E', 'Little R', 'Lopez M', 'Pariyadath V', 'Weiss SR', 'Wolff-Hughes DL', 'DelCarmen-Wiggins R', 'Feldstein Ewing SW', 'Miranda-Dominguez O', 'Nagel BJ', 'Perrone AJ', 'Sturgeon DT', 'Goldstone A', 'Pfefferbaum A', 'Pohl KM', 'Prouty D', 'Uban K', 'Bookheimer SY', 'Dapretto M', 'Galvan A', 'Bagot K', 'Giedd J', 'Infante MA', 'Jacobus J', 'Patrick K', 'Shilling PD', 'Desikan R', 'Li Y', 'Sugrue L', 'Banich MT', 'Friedman N', 'Hewitt JK', 'Hopfer C', 'Sakai J', 'Tanabe J', 'Cottler LB', 'Nixon SJ', 'Chang L', 'Cloak C', 'Ernst T', 'Reeves G', 'Kennedy DN', 'Heeringa S', 'Peltier S', 'Schulenberg J', 'Sripada C', 'Zucker RA', 'Iacono WG', 'Luciana M', 'Calabro FJ', 'Clark DB', 'Lewis DA', 'Luna B', 'Schirda C', 'Brima T', 'Foxe JJ', 'Freedman EG', 'Mruzek DW', 'Mason MJ', 'Huber R', 'McGlade E', 'Prescot A', 'Renshaw PF', 'Yurgelun-Todd DA', 'Allgaier NA', 'Dumas JA', 'Ivanova M', 'Potter A', 'Florsheim P', 'Larson C', 'Lisdahl K', 'Charness ME', 'Fuemmeler B', 'Hettema JM', 'Maes HH', 'Steinberg J', 'Anokhin AP', 'Glaser P', 'Heath AC', 'Madden PA', 'Baskin-Sommers A', 'Constable RT', 'Grant SJ', 'Dowling GJ', 'Brown SA', 'Jernigan TL', 'Dale AM']",2019,11,15,Neuroimage,202,,116091,"The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data is a resource of unprecedented scale and depth for studying typical and atypical development. The aim of this manuscript is to describe the baseline neuroimaging processing and subject-level analysis methods used by ABCD. Processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI. This manuscript serves as a methodological reference for users of publicly shared neuroimaging data from the ABCD Study." -31633021,PMC6785263,10.1126/sciadv.aax2084,Habenular and striatal activity during performance feedback are differentially linked with state-like and trait-like aspects of tobacco use disorder,"['Flannery JS', 'Riedel MC', 'Poudel R', 'Laird AR', 'Ross TJ', 'Salmeron BJ', 'Stein EA', 'Sutherland MT']",2019,10,17,Sci Adv,5,10,eaax2084,"The habenula, an epithalamic nucleus involved in reward and aversive processing, may contribute to negative reinforcement mechanisms maintaining nicotine use. We used a performance feedback task that differentially activates the striatum and habenula and administered nicotine and varenicline (versus placebos) to overnight-abstinent smokers and nonsmokers to delineate feedback-related functional brain alterations both as a function of smoking trait (smokers versus nonsmokers) and drug administration state (drug versus placebo). Smokers showed less striatal responsivity to positive feedback, an alteration not mitigated by drug administration, but rather correlated with trait-level addiction severity. Conversely, nicotine administration reduced habenula activity following both positive and negative feedback among abstinent smokers, but not nonsmokers, and increased habenula activity among smokers correlated with elevated state-level tobacco cravings. These outcomes highlight a dissociation between neurobiological processes linked with the dependence severity trait and the nicotine withdrawal state. Interventions simultaneously targeting both aspects may improve currently poor cessation outcomes." -31633021,PMC6785263,10.1126/sciadv.aax2084,Habenular and striatal activity during performance feedback are differentially linked with state-like and trait-like aspects of tobacco use disorder,"['Flannery JS', 'Riedel MC', 'Poudel R', 'Laird AR', 'Ross TJ', 'Salmeron BJ', 'Stein EA', 'Sutherland MT']",2019,10,17,Sci Adv,5,10,eaax2084,"The habenula, an epithalamic nucleus involved in reward and aversive processing, may contribute to negative reinforcement mechanisms maintaining nicotine use. We used a performance feedback task that differentially activates the striatum and habenula and administered nicotine and varenicline (versus placebos) to overnight-abstinent smokers and nonsmokers to delineate feedback-related functional brain alterations both as a function of smoking trait (smokers versus nonsmokers) and drug administration state (drug versus placebo). Smokers showed less striatal responsivity to positive feedback, an alteration not mitigated by drug administration, but rather correlated with trait-level addiction severity. Conversely, nicotine administration reduced habenula activity following both positive and negative feedback among abstinent smokers, but not nonsmokers, and increased habenula activity among smokers correlated with elevated state-level tobacco cravings. These outcomes highlight a dissociation between neurobiological processes linked with the dependence severity trait and the nicotine withdrawal state. Interventions simultaneously targeting both aspects may improve currently poor cessation outcomes." -31700677,PMC6825125,10.1038/s41539-019-0058-9,Sex differences in brain correlates of STEM anxiety,"['Gonzalez AA', 'Bottenhorn KL', 'Bartley JE', 'Hayes T', 'Riedel MC', 'Salo T', 'Bravo EI', 'Odean R', 'Nazareth A', 'Laird RW', 'Sutherland MT', 'Brewe E', 'Pruden SM', 'Laird AR']",2019,3,17,NPJ Sci Learn,4,,18,"Anxiety is known to dysregulate the salience, default mode, and central executive networks of the human brain, yet this phenomenon has not been fully explored across the STEM learning experience, where anxiety can impact negatively academic performance. Here, we evaluated anxiety and large-scale brain connectivity in 101 undergraduate physics students. We found sex differences in STEM-related and clinical anxiety, with longitudinal increases in science anxiety observed for both female and male students. Sex-specific relationships between STEM anxiety and brain connectivity emerged, with male students exhibiting distinct inter-network connectivity for STEM and clinical anxiety, and female students demonstrating no significant within-sex correlations. Anxiety was negatively correlated with academic performance in sex-specific ways at both pre- and post-instruction. Moreover, math anxiety in male students mediated the relation between default mode-salience connectivity and course grade. Together, these results reveal complex sex differences in the neural mechanisms driving how anxiety is related to STEM learning." -31700677,PMC6825125,10.1038/s41539-019-0058-9,Sex differences in brain correlates of STEM anxiety,"['Gonzalez AA', 'Bottenhorn KL', 'Bartley JE', 'Hayes T', 'Riedel MC', 'Salo T', 'Bravo EI', 'Odean R', 'Nazareth A', 'Laird RW', 'Sutherland MT', 'Brewe E', 'Pruden SM', 'Laird AR']",2019,3,17,NPJ Sci Learn,4,,18,"Anxiety is known to dysregulate the salience, default mode, and central executive networks of the human brain, yet this phenomenon has not been fully explored across the STEM learning experience, where anxiety can impact negatively academic performance. Here, we evaluated anxiety and large-scale brain connectivity in 101 undergraduate physics students. We found sex differences in STEM-related and clinical anxiety, with longitudinal increases in science anxiety observed for both female and male students. Sex-specific relationships between STEM anxiety and brain connectivity emerged, with male students exhibiting distinct inter-network connectivity for STEM and clinical anxiety, and female students demonstrating no significant within-sex correlations. Anxiety was negatively correlated with academic performance in sex-specific ways at both pre- and post-instruction. Moreover, math anxiety in male students mediated the relation between default mode-salience connectivity and course grade. Together, these results reveal complex sex differences in the neural mechanisms driving how anxiety is related to STEM learning." -31814997,PMC6889284,10.1038/s41539-019-0059-8,Brain activity links performance in science reasoning with conceptual approach,"['Bartley JE', 'Riedel MC', 'Salo T', 'Boeving ER', 'Bottenhorn KL', 'Bravo EI', 'Odean R', 'Nazareth A', 'Laird RW', 'Sutherland MT', 'Pruden SM', 'Brewe E', 'Laird AR']",2019,3,17,NPJ Sci Learn,4,,20,"Understanding how students learn is crucial for helping them succeed. We examined brain function in 107 undergraduate students during a task known to be challenging for many students-physics problem solving-to characterize the underlying neural mechanisms and determine how these support comprehension and proficiency. Further, we applied module analysis to response distributions, defining groups of students who answered by using similar physics conceptions, and probed for brain differences linked with different conceptual approaches. We found that integrated executive, attentional, visual motion, and default mode brain systems cooperate to achieve sequential and sustained physics-related cognition. While accuracy alone did not predict brain function, dissociable brain patterns were observed when students solved problems by using different physics conceptions, and increased success was linked to conceptual coherence. Our analyses demonstrate that episodic associations and control processes operate in tandem to support physics reasoning, offering potential insight to support student learning." -31814997,PMC6889284,10.1038/s41539-019-0059-8,Brain activity links performance in science reasoning with conceptual approach,"['Bartley JE', 'Riedel MC', 'Salo T', 'Boeving ER', 'Bottenhorn KL', 'Bravo EI', 'Odean R', 'Nazareth A', 'Laird RW', 'Sutherland MT', 'Pruden SM', 'Brewe E', 'Laird AR']",2019,3,17,NPJ Sci Learn,4,,20,"Understanding how students learn is crucial for helping them succeed. We examined brain function in 107 undergraduate students during a task known to be challenging for many students-physics problem solving-to characterize the underlying neural mechanisms and determine how these support comprehension and proficiency. Further, we applied module analysis to response distributions, defining groups of students who answered by using similar physics conceptions, and probed for brain differences linked with different conceptual approaches. We found that integrated executive, attentional, visual motion, and default mode brain systems cooperate to achieve sequential and sustained physics-related cognition. While accuracy alone did not predict brain function, dissociable brain patterns were observed when students solved problems by using different physics conceptions, and increased success was linked to conceptual coherence. Our analyses demonstrate that episodic associations and control processes operate in tandem to support physics reasoning, offering potential insight to support student learning." -31827430,PMC6890833,10.3389/fninf.2019.00070,ASD-DiagNet: A Hybrid Learning Approach for Detection of Autism Spectrum Disorder Using fMRI Data,"['Eslami T', 'Mirjalili V', 'Fong A', 'Laird AR', 'Saeed F']",2019,3,17,Front Neuroinform,13,,70,"Heterogeneous mental disorders such as Autism Spectrum Disorder (ASD) are notoriously difficult to diagnose, especially in children. The current psychiatric diagnostic process is based purely on the behavioral observation of symptomology (DSM-5/ICD-10) and may be prone to misdiagnosis. In order to move the field toward more quantitative diagnosis, we need advanced and scalable machine learning infrastructure that will allow us to identify reliable biomarkers of mental health disorders. In this paper, we propose a framework called ASD-DiagNet for classifying subjects with ASD from healthy subjects by using only fMRI data. We designed and implemented a joint learning procedure using an autoencoder and a single layer perceptron (SLP) which results in improved quality of extracted features and optimized parameters for the model. Further, we designed and implemented a data augmentation strategy, based on linear interpolation on available feature vectors, that allows us to produce synthetic datasets needed for training of machine learning models. The proposed approach is evaluated on a public dataset provided by Autism Brain Imaging Data Exchange including 1, 035 subjects coming from 17 different brain imaging centers. Our machine learning model outperforms other state of the art methods from 10 imaging centers with increase in classification accuracy up to 28% with maximum accuracy of 82%. The machine learning technique presented in this paper, in addition to yielding better quality, gives enormous advantages in terms of execution time (40 min vs. 7 h on other methods). The implemented code is available as GPL license on GitHub portal of our lab (https://github.com/pcdslab/ASD-DiagNet)." -31872334,,10.3758/s13415-019-00763-7,Meta-analytic clustering dissociates brain activity and behavior profiles across reward processing paradigms,"['Flannery JS', 'Riedel MC', 'Bottenhorn KL', 'Poudel R', 'Salo T', 'Hill-Bowen LD', 'Laird AR', 'Sutherland MT']",2019,12,23,Cogn Affect Behav Neurosci,,,,"Reward learning is a ubiquitous cognitive mechanism guiding adaptive choices and behaviors, and when impaired, can lead to considerable mental health consequences. Reward-related functional neuroimaging studies have begun to implicate networks of brain regions essential for processing various peripheral influences (e.g., risk, subjective preference, delay, social context) involved in the multifaceted reward processing construct. To provide a more complete neurocognitive perspective on reward processing that synthesizes findings across the literature while also appreciating these peripheral influences, we used emerging meta-analytic techniques to elucidate brain regions, and in turn networks, consistently engaged in distinct aspects of reward processing. Using a data-driven, meta-analytic, k-means clustering approach, we dissociated seven meta-analytic groupings (MAGs) of neuroimaging results (i.e., brain activity maps) from 749 experimental contrasts across 176 reward processing studies involving 13,358 healthy participants. We then performed an exploratory functional decoding approach to gain insight into the putative functions associated with each MAG. We identified a seven-MAG clustering solution that represented dissociable patterns of convergent brain activity across reward processing tasks. Additionally, our functional decoding analyses revealed that each of these MAGs mapped onto discrete behavior profiles that suggested specialized roles in predicting value (MAG-1 & MAG-2) and processing a variety of emotional (MAG-3), external (MAG-4 & MAG-5), and internal (MAG-6 & MAG-7) influences across reward processing paradigms. These findings support and extend aspects of well-accepted reward learning theories and highlight large-scale brain network activity associated with distinct aspects of reward processing." -31872334,,10.3758/s13415-019-00763-7,Meta-analytic clustering dissociates brain activity and behavior profiles across reward processing paradigms,"['Flannery JS', 'Riedel MC', 'Bottenhorn KL', 'Poudel R', 'Salo T', 'Hill-Bowen LD', 'Laird AR', 'Sutherland MT']",2019,12,23,Cogn Affect Behav Neurosci,,,,"Reward learning is a ubiquitous cognitive mechanism guiding adaptive choices and behaviors, and when impaired, can lead to considerable mental health consequences. Reward-related functional neuroimaging studies have begun to implicate networks of brain regions essential for processing various peripheral influences (e.g., risk, subjective preference, delay, social context) involved in the multifaceted reward processing construct. To provide a more complete neurocognitive perspective on reward processing that synthesizes findings across the literature while also appreciating these peripheral influences, we used emerging meta-analytic techniques to elucidate brain regions, and in turn networks, consistently engaged in distinct aspects of reward processing. Using a data-driven, meta-analytic, k-means clustering approach, we dissociated seven meta-analytic groupings (MAGs) of neuroimaging results (i.e., brain activity maps) from 749 experimental contrasts across 176 reward processing studies involving 13,358 healthy participants. We then performed an exploratory functional decoding approach to gain insight into the putative functions associated with each MAG. We identified a seven-MAG clustering solution that represented dissociable patterns of convergent brain activity across reward processing tasks. Additionally, our functional decoding analyses revealed that each of these MAGs mapped onto discrete behavior profiles that suggested specialized roles in predicting value (MAG-1 & MAG-2) and processing a variety of emotional (MAG-3), external (MAG-4 & MAG-5), and internal (MAG-6 & MAG-7) influences across reward processing paradigms. These findings support and extend aspects of well-accepted reward learning theories and highlight large-scale brain network activity associated with distinct aspects of reward processing." -31995811,,10.1038/s41386-020-0623-1,Nicotine dependence (trait) and acute nicotinic stimulation (state) modulate attention but not inhibitory control: converging fMRI evidence from Go-Nogo and Flanker tasks,"['Lesage E', 'Sutherland MT', 'Ross TJ', 'Salmeron BJ', 'Stein EA']",2020,4,17,Neuropsychopharmacology,45,5,857-865,"Cognitive deficits during nicotine withdrawal may contribute to smoking relapse. However, interacting effects of chronic nicotine dependence and acute nicotine withdrawal on cognitive control are poorly understood. Here we examine the effects of nicotine dependence (trait; smokers (n = 24) vs. non-smoking controls; n = 20) and acute nicotinic stimulation (state; administration of nicotine and varenicline, two FDA-approved smoking cessation aids, during abstinence), on two well-established tests of inhibitory control, the Go-Nogo task and the Flanker task, during fMRI scanning. We compared performance and neural responses between these four pharmacological manipulations in a double-blind, placebo-controlled crossover design. As expected, performance in both tasks was modulated by nicotine dependence, abstinence, and pharmacological manipulation. However, effects were driven entirely by conditions that required less inhibitory control. When demand for inhibitory control was high, abstinent smokers showed no deficits. By contrast, acutely abstinent smokers showed performance deficits in easier conditions and missed more trials. Go-Nogo fMRI results showed decreased inhibition-related neural activity in right anterior insula and right putamen in smokers and decreased dorsal anterior cingulate cortex activity on nicotine across groups. No effects were found on inhibition-related activity during the Flanker task or on error-related activity in either task. Given robust nicotinic effects on physiology and behavioral deficits in attention, we are confident that pharmacological manipulations were effective. Thus findings fit a recent proposal that abstinent smokers show decreased ability to divert cognitive resources at low or intermediate cognitive demand, while performance at high cognitive demand remains relatively unaffected, suggesting a primary attentional deficit during acute abstinence." -32038473,PMC6993791,10.3389/fneur.2020.00018,Functional Characterization of Atrophy Patterns Related to Cognitive Impairment,"['Schnellbacher GJ', 'Hoffstaedter F', 'Eickhoff SB', 'Caspers S', 'Nickl-Jockschat T', 'Fox PT', 'Laird AR', 'Schulz JB', 'Reetz K', 'Dogan I']",2020,3,17,Front Neurol,11,,18,"Introduction: Mild cognitive impairment (MCI) is a heterogenous syndrome considered as a risk factor for developing dementia. Previous work examining morphological brain changes in MCI has identified a temporo-parietal atrophy pattern that suggests a common neuroanatomical denominator of cognitive impairment. Using functional connectivity analyses of structurally affected regions in MCI, we aimed to investigate and characterize functional networks formed by these regions that appear to be particularly vulnerable to disease-related disruptions. Methods: Areas of convergent atrophy in MCI were derived from a quantitative meta-analysis and encompassed left and right medial temporal (i.e., hippocampus, amygdala), as well as parietal regions (precuneus), which were defined as seed regions for connectivity analyses. Both task-based meta-analytical connectivity modeling (MACM) based on the BrainMap database and task-free resting-state functional MRI in a large cohort of older adults from the 1000BRAINS study were applied. We additionally assessed behavioral characteristics associated with the seed regions using BrainMap meta-data and investigated correlations of resting-state connectivity with age. Results: The left temporal seed showed stronger associations with a fronto-temporal network, whereas the right temporal atrophy cluster was more linked to cortico-striatal regions. In accordance with this, behavioral analysis indicated an emphasis of the left temporal seed on language generation, and the right temporal seed was associated with the domains of emotion and attention. Task-independent co-activation was more pronounced in the parietal seed, which demonstrated stronger connectivity with a frontoparietal network and associations with introspection and social cognition. Correlation analysis revealed both decreasing and increasing functional connectivity with higher age that may add to pathological processes but also indicates compensatory mechanisms of functional reorganization with increasing age. Conclusion: Our findings provide an important pathophysiological link between morphological changes and the clinical relevance of major structural damage in MCI. Multimodal analysis of functional networks related to areas of MCI-typical atrophy may help to explain cognitive decline and behavioral alterations not tractable by a mere anatomical interpretation and therefore contribute to prognostic evaluations." +31633021,PMC6785263,10.1126/sciadv.aax2084,Habenular and striatal activity during performance feedback are differentially linked with state-like and trait-like aspects of tobacco use disorder,"['Flannery JS', 'Riedel MC', 'Poudel R', 'Laird AR', 'Ross TJ', 'Salmeron BJ', 'Stein EA', 'Sutherland MT']",2019,10,8,Sci Adv,5,10,eaax2084,"The habenula, an epithalamic nucleus involved in reward and aversive processing, may contribute to negative reinforcement mechanisms maintaining nicotine use. We used a performance feedback task that differentially activates the striatum and habenula and administered nicotine and varenicline (versus placebos) to overnight-abstinent smokers and nonsmokers to delineate feedback-related functional brain alterations both as a function of smoking trait (smokers versus nonsmokers) and drug administration state (drug versus placebo). Smokers showed less striatal responsivity to positive feedback, an alteration not mitigated by drug administration, but rather correlated with trait-level addiction severity. Conversely, nicotine administration reduced habenula activity following both positive and negative feedback among abstinent smokers, but not nonsmokers, and increased habenula activity among smokers correlated with elevated state-level tobacco cravings. These outcomes highlight a dissociation between neurobiological processes linked with the dependence severity trait and the nicotine withdrawal state. Interventions simultaneously targeting both aspects may improve currently poor cessation outcomes." +31633021,PMC6785263,10.1126/sciadv.aax2084,Habenular and striatal activity during performance feedback are differentially linked with state-like and trait-like aspects of tobacco use disorder,"['Flannery JS', 'Riedel MC', 'Poudel R', 'Laird AR', 'Ross TJ', 'Salmeron BJ', 'Stein EA', 'Sutherland MT']",2019,10,8,Sci Adv,5,10,eaax2084,"The habenula, an epithalamic nucleus involved in reward and aversive processing, may contribute to negative reinforcement mechanisms maintaining nicotine use. We used a performance feedback task that differentially activates the striatum and habenula and administered nicotine and varenicline (versus placebos) to overnight-abstinent smokers and nonsmokers to delineate feedback-related functional brain alterations both as a function of smoking trait (smokers versus nonsmokers) and drug administration state (drug versus placebo). Smokers showed less striatal responsivity to positive feedback, an alteration not mitigated by drug administration, but rather correlated with trait-level addiction severity. Conversely, nicotine administration reduced habenula activity following both positive and negative feedback among abstinent smokers, but not nonsmokers, and increased habenula activity among smokers correlated with elevated state-level tobacco cravings. These outcomes highlight a dissociation between neurobiological processes linked with the dependence severity trait and the nicotine withdrawal state. Interventions simultaneously targeting both aspects may improve currently poor cessation outcomes." +31700677,PMC6825125,10.1038/s41539-019-0058-9,Sex differences in brain correlates of STEM anxiety,"['Gonzalez AA', 'Bottenhorn KL', 'Bartley JE', 'Hayes T', 'Riedel MC', 'Salo T', 'Bravo EI', 'Odean R', 'Nazareth A', 'Laird RW', 'Sutherland MT', 'Brewe E', 'Pruden SM', 'Laird AR']",2019,6,8,NPJ Sci Learn,4,,18,"Anxiety is known to dysregulate the salience, default mode, and central executive networks of the human brain, yet this phenomenon has not been fully explored across the STEM learning experience, where anxiety can impact negatively academic performance. Here, we evaluated anxiety and large-scale brain connectivity in 101 undergraduate physics students. We found sex differences in STEM-related and clinical anxiety, with longitudinal increases in science anxiety observed for both female and male students. Sex-specific relationships between STEM anxiety and brain connectivity emerged, with male students exhibiting distinct inter-network connectivity for STEM and clinical anxiety, and female students demonstrating no significant within-sex correlations. Anxiety was negatively correlated with academic performance in sex-specific ways at both pre- and post-instruction. Moreover, math anxiety in male students mediated the relation between default mode-salience connectivity and course grade. Together, these results reveal complex sex differences in the neural mechanisms driving how anxiety is related to STEM learning." +31700677,PMC6825125,10.1038/s41539-019-0058-9,Sex differences in brain correlates of STEM anxiety,"['Gonzalez AA', 'Bottenhorn KL', 'Bartley JE', 'Hayes T', 'Riedel MC', 'Salo T', 'Bravo EI', 'Odean R', 'Nazareth A', 'Laird RW', 'Sutherland MT', 'Brewe E', 'Pruden SM', 'Laird AR']",2019,6,8,NPJ Sci Learn,4,,18,"Anxiety is known to dysregulate the salience, default mode, and central executive networks of the human brain, yet this phenomenon has not been fully explored across the STEM learning experience, where anxiety can impact negatively academic performance. Here, we evaluated anxiety and large-scale brain connectivity in 101 undergraduate physics students. We found sex differences in STEM-related and clinical anxiety, with longitudinal increases in science anxiety observed for both female and male students. Sex-specific relationships between STEM anxiety and brain connectivity emerged, with male students exhibiting distinct inter-network connectivity for STEM and clinical anxiety, and female students demonstrating no significant within-sex correlations. Anxiety was negatively correlated with academic performance in sex-specific ways at both pre- and post-instruction. Moreover, math anxiety in male students mediated the relation between default mode-salience connectivity and course grade. Together, these results reveal complex sex differences in the neural mechanisms driving how anxiety is related to STEM learning." +31814997,PMC6889284,10.1038/s41539-019-0059-8,Brain activity links performance in science reasoning with conceptual approach,"['Bartley JE', 'Riedel MC', 'Salo T', 'Boeving ER', 'Bottenhorn KL', 'Bravo EI', 'Odean R', 'Nazareth A', 'Laird RW', 'Sutherland MT', 'Pruden SM', 'Brewe E', 'Laird AR']",2019,6,8,NPJ Sci Learn,4,,20,"Understanding how students learn is crucial for helping them succeed. We examined brain function in 107 undergraduate students during a task known to be challenging for many students-physics problem solving-to characterize the underlying neural mechanisms and determine how these support comprehension and proficiency. Further, we applied module analysis to response distributions, defining groups of students who answered by using similar physics conceptions, and probed for brain differences linked with different conceptual approaches. We found that integrated executive, attentional, visual motion, and default mode brain systems cooperate to achieve sequential and sustained physics-related cognition. While accuracy alone did not predict brain function, dissociable brain patterns were observed when students solved problems by using different physics conceptions, and increased success was linked to conceptual coherence. Our analyses demonstrate that episodic associations and control processes operate in tandem to support physics reasoning, offering potential insight to support student learning." +31814997,PMC6889284,10.1038/s41539-019-0059-8,Brain activity links performance in science reasoning with conceptual approach,"['Bartley JE', 'Riedel MC', 'Salo T', 'Boeving ER', 'Bottenhorn KL', 'Bravo EI', 'Odean R', 'Nazareth A', 'Laird RW', 'Sutherland MT', 'Pruden SM', 'Brewe E', 'Laird AR']",2019,6,8,NPJ Sci Learn,4,,20,"Understanding how students learn is crucial for helping them succeed. We examined brain function in 107 undergraduate students during a task known to be challenging for many students-physics problem solving-to characterize the underlying neural mechanisms and determine how these support comprehension and proficiency. Further, we applied module analysis to response distributions, defining groups of students who answered by using similar physics conceptions, and probed for brain differences linked with different conceptual approaches. We found that integrated executive, attentional, visual motion, and default mode brain systems cooperate to achieve sequential and sustained physics-related cognition. While accuracy alone did not predict brain function, dissociable brain patterns were observed when students solved problems by using different physics conceptions, and increased success was linked to conceptual coherence. Our analyses demonstrate that episodic associations and control processes operate in tandem to support physics reasoning, offering potential insight to support student learning." +31827430,PMC6890833,10.3389/fninf.2019.00070,ASD-DiagNet: A Hybrid Learning Approach for Detection of Autism Spectrum Disorder Using fMRI Data,"['Eslami T', 'Mirjalili V', 'Fong A', 'Laird AR', 'Saeed F']",2019,6,8,Front Neuroinform,13,,70,"Heterogeneous mental disorders such as Autism Spectrum Disorder (ASD) are notoriously difficult to diagnose, especially in children. The current psychiatric diagnostic process is based purely on the behavioral observation of symptomology (DSM-5/ICD-10) and may be prone to misdiagnosis. In order to move the field toward more quantitative diagnosis, we need advanced and scalable machine learning infrastructure that will allow us to identify reliable biomarkers of mental health disorders. In this paper, we propose a framework called ASD-DiagNet for classifying subjects with ASD from healthy subjects by using only fMRI data. We designed and implemented a joint learning procedure using an autoencoder and a single layer perceptron (SLP) which results in improved quality of extracted features and optimized parameters for the model. Further, we designed and implemented a data augmentation strategy, based on linear interpolation on available feature vectors, that allows us to produce synthetic datasets needed for training of machine learning models. The proposed approach is evaluated on a public dataset provided by Autism Brain Imaging Data Exchange including 1, 035 subjects coming from 17 different brain imaging centers. Our machine learning model outperforms other state of the art methods from 10 imaging centers with increase in classification accuracy up to 28% with maximum accuracy of 82%. The machine learning technique presented in this paper, in addition to yielding better quality, gives enormous advantages in terms of execution time (40 min vs. 7 h on other methods). The implemented code is available as GPL license on GitHub portal of our lab (https://github.com/pcdslab/ASD-DiagNet)." +31872334,PMC7117996,10.3758/s13415-019-00763-7,Meta-analytic clustering dissociates brain activity and behavior profiles across reward processing paradigms,"['Flannery JS', 'Riedel MC', 'Bottenhorn KL', 'Poudel R', 'Salo T', 'Hill-Bowen LD', 'Laird AR', 'Sutherland MT']",2020,4,8,Cogn Affect Behav Neurosci,20,2,215-235,"Reward learning is a ubiquitous cognitive mechanism guiding adaptive choices and behaviors, and when impaired, can lead to considerable mental health consequences. Reward-related functional neuroimaging studies have begun to implicate networks of brain regions essential for processing various peripheral influences (e.g., risk, subjective preference, delay, social context) involved in the multifaceted reward processing construct. To provide a more complete neurocognitive perspective on reward processing that synthesizes findings across the literature while also appreciating these peripheral influences, we used emerging meta-analytic techniques to elucidate brain regions, and in turn networks, consistently engaged in distinct aspects of reward processing. Using a data-driven, meta-analytic, k-means clustering approach, we dissociated seven meta-analytic groupings (MAGs) of neuroimaging results (i.e., brain activity maps) from 749 experimental contrasts across 176 reward processing studies involving 13,358 healthy participants. We then performed an exploratory functional decoding approach to gain insight into the putative functions associated with each MAG. We identified a seven-MAG clustering solution that represented dissociable patterns of convergent brain activity across reward processing tasks. Additionally, our functional decoding analyses revealed that each of these MAGs mapped onto discrete behavior profiles that suggested specialized roles in predicting value (MAG-1 & MAG-2) and processing a variety of emotional (MAG-3), external (MAG-4 & MAG-5), and internal (MAG-6 & MAG-7) influences across reward processing paradigms. These findings support and extend aspects of well-accepted reward learning theories and highlight large-scale brain network activity associated with distinct aspects of reward processing." +31872334,PMC7117996,10.3758/s13415-019-00763-7,Meta-analytic clustering dissociates brain activity and behavior profiles across reward processing paradigms,"['Flannery JS', 'Riedel MC', 'Bottenhorn KL', 'Poudel R', 'Salo T', 'Hill-Bowen LD', 'Laird AR', 'Sutherland MT']",2020,4,8,Cogn Affect Behav Neurosci,20,2,215-235,"Reward learning is a ubiquitous cognitive mechanism guiding adaptive choices and behaviors, and when impaired, can lead to considerable mental health consequences. Reward-related functional neuroimaging studies have begun to implicate networks of brain regions essential for processing various peripheral influences (e.g., risk, subjective preference, delay, social context) involved in the multifaceted reward processing construct. To provide a more complete neurocognitive perspective on reward processing that synthesizes findings across the literature while also appreciating these peripheral influences, we used emerging meta-analytic techniques to elucidate brain regions, and in turn networks, consistently engaged in distinct aspects of reward processing. Using a data-driven, meta-analytic, k-means clustering approach, we dissociated seven meta-analytic groupings (MAGs) of neuroimaging results (i.e., brain activity maps) from 749 experimental contrasts across 176 reward processing studies involving 13,358 healthy participants. We then performed an exploratory functional decoding approach to gain insight into the putative functions associated with each MAG. We identified a seven-MAG clustering solution that represented dissociable patterns of convergent brain activity across reward processing tasks. Additionally, our functional decoding analyses revealed that each of these MAGs mapped onto discrete behavior profiles that suggested specialized roles in predicting value (MAG-1 & MAG-2) and processing a variety of emotional (MAG-3), external (MAG-4 & MAG-5), and internal (MAG-6 & MAG-7) influences across reward processing paradigms. These findings support and extend aspects of well-accepted reward learning theories and highlight large-scale brain network activity associated with distinct aspects of reward processing." +31995811,PMC7075893,10.1038/s41386-020-0623-1,Nicotine dependence (trait) and acute nicotinic stimulation (state) modulate attention but not inhibitory control: converging fMRI evidence from Go-Nogo and Flanker tasks,"['Lesage E', 'Sutherland MT', 'Ross TJ', 'Salmeron BJ', 'Stein EA']",2020,4,8,Neuropsychopharmacology,45,5,857-865,"Cognitive deficits during nicotine withdrawal may contribute to smoking relapse. However, interacting effects of chronic nicotine dependence and acute nicotine withdrawal on cognitive control are poorly understood. Here we examine the effects of nicotine dependence (trait; smokers (n = 24) vs. non-smoking controls; n = 20) and acute nicotinic stimulation (state; administration of nicotine and varenicline, two FDA-approved smoking cessation aids, during abstinence), on two well-established tests of inhibitory control, the Go-Nogo task and the Flanker task, during fMRI scanning. We compared performance and neural responses between these four pharmacological manipulations in a double-blind, placebo-controlled crossover design. As expected, performance in both tasks was modulated by nicotine dependence, abstinence, and pharmacological manipulation. However, effects were driven entirely by conditions that required less inhibitory control. When demand for inhibitory control was high, abstinent smokers showed no deficits. By contrast, acutely abstinent smokers showed performance deficits in easier conditions and missed more trials. Go-Nogo fMRI results showed decreased inhibition-related neural activity in right anterior insula and right putamen in smokers and decreased dorsal anterior cingulate cortex activity on nicotine across groups. No effects were found on inhibition-related activity during the Flanker task or on error-related activity in either task. Given robust nicotinic effects on physiology and behavioral deficits in attention, we are confident that pharmacological manipulations were effective. Thus findings fit a recent proposal that abstinent smokers show decreased ability to divert cognitive resources at low or intermediate cognitive demand, while performance at high cognitive demand remains relatively unaffected, suggesting a primary attentional deficit during acute abstinence." +32038473,PMC6993791,10.3389/fneur.2020.00018,Functional Characterization of Atrophy Patterns Related to Cognitive Impairment,"['Schnellbacher GJ', 'Hoffstaedter F', 'Eickhoff SB', 'Caspers S', 'Nickl-Jockschat T', 'Fox PT', 'Laird AR', 'Schulz JB', 'Reetz K', 'Dogan I']",2020,6,8,Front Neurol,11,,18,"Introduction: Mild cognitive impairment (MCI) is a heterogenous syndrome considered as a risk factor for developing dementia. Previous work examining morphological brain changes in MCI has identified a temporo-parietal atrophy pattern that suggests a common neuroanatomical denominator of cognitive impairment. Using functional connectivity analyses of structurally affected regions in MCI, we aimed to investigate and characterize functional networks formed by these regions that appear to be particularly vulnerable to disease-related disruptions. Methods: Areas of convergent atrophy in MCI were derived from a quantitative meta-analysis and encompassed left and right medial temporal (i.e., hippocampus, amygdala), as well as parietal regions (precuneus), which were defined as seed regions for connectivity analyses. Both task-based meta-analytical connectivity modeling (MACM) based on the BrainMap database and task-free resting-state functional MRI in a large cohort of older adults from the 1000BRAINS study were applied. We additionally assessed behavioral characteristics associated with the seed regions using BrainMap meta-data and investigated correlations of resting-state connectivity with age. Results: The left temporal seed showed stronger associations with a fronto-temporal network, whereas the right temporal atrophy cluster was more linked to cortico-striatal regions. In accordance with this, behavioral analysis indicated an emphasis of the left temporal seed on language generation, and the right temporal seed was associated with the domains of emotion and attention. Task-independent co-activation was more pronounced in the parietal seed, which demonstrated stronger connectivity with a frontoparietal network and associations with introspection and social cognition. Correlation analysis revealed both decreasing and increasing functional connectivity with higher age that may add to pathological processes but also indicates compensatory mechanisms of functional reorganization with increasing age. Conclusion: Our findings provide an important pathophysiological link between morphological changes and the clinical relevance of major structural damage in MCI. Multimodal analysis of functional networks related to areas of MCI-typical atrophy may help to explain cognitive decline and behavioral alterations not tractable by a mere anatomical interpretation and therefore contribute to prognostic evaluations." 32067196,,10.1007/s12021-020-09454-y,Ontological Dimensions of Cognitive-Neural Mappings,"['Bolt T', 'Nomi JS', 'Arens R', 'Vij SG', 'Riedel M', 'Salo T', 'Laird AR', 'Eickhoff SB', 'Uddin LQ']",2020,2,18,Neuroinformatics,,,,"The growing literature reporting results of cognitive-neural mappings has increased calls for an adequate organizing ontology, or taxonomy, of these mappings. This enterprise is non-trivial, as relevant dimensions that might contribute to such an ontology are not yet agreed upon. We propose that any candidate dimensions should be evaluated on their ability to explain observed differences in functional neuroimaging activation patterns. In this study, we use a large sample of task-based functional magnetic resonance imaging (task-fMRI) results and a data-driven strategy to identify these dimensions. First, using a data-driven dimension reduction approach and multivariate distance matrix regression (MDMR), we quantify the variance among activation maps that is explained by existing ontological dimensions. We find that 'task paradigm' categories explain more variance among task-activation maps than other dimensions, including latent cognitive categories. Surprisingly, 'study ID', or the study from which each activation map was reported, explained close to 50% of the variance in activation patterns. Using a clustering approach that allows for overlapping clusters, we derived data-driven latent activation states, associated with re-occurring configurations of the canonical frontoparietal, salience, sensory-motor, and default mode network activation patterns. Importantly, with only four data-driven latent dimensions, one can explain greater variance among activation maps than all conventional ontological dimensions combined. These latent dimensions may inform a data-driven cognitive ontology, and suggest that current descriptions of cognitive processes and the tasks used to elicit them do not accurately reflect activation patterns commonly observed in the human brain." -32078973,,10.1016/j.drugalcdep.2020.107884,Common and distinct brain activity associated with risky and ambiguous decision-making,"['Poudel R', 'Riedel MC', 'Salo T', 'Flannery JS', 'Hill-Bowen LD', 'Eickhoff SB', 'Laird AR', 'Sutherland MT']",2020,2,4,Drug Alcohol Depend,209,,107884,"Two often-studied forms of uncertain decision-making (DM) are risky-DM (outcome probabilities known) and ambiguous-DM (outcome probabilities unknown). While DM in general is associated with activation of several brain regions, previous neuroimaging efforts suggest a dissociation between activity linked with risky and ambiguous choices. However, the common and distinct neurobiological correlates associated with risky- and ambiguous-DM, as well as their specificity when compared to perceptual-DM (as a 'control condition'), remains to be clarified. We conducted multiple meta-analyses on neuroimaging results from 151 studies to characterize common and domain-specific brain activity during risky-, ambiguous-, and perceptual-DM. When considering all DM tasks, convergent activity was observed in brain regions considered to be consituents of the canonical salience, valuation, and executive control networks. When considering subgroups of studies, risky-DM (vs. perceptual-DM) was linked with convergent activity in the striatum and anterior cingulate cortex (ACC), regions associated with reward-related processes (determined by objective functional decoding). When considering ambiguous-DM (vs. perceptual-DM), activity convergence was observed in the lateral prefrontal cortex and insula, regions implicated in affectively-neutral mental processes (e.g., cognitive control and behavioral responding; determined by functional decoding). An exploratory meta-analysis comparing brain activity between substance users and non-users during risky-DM identified reduced convergent activity among users in the striatum, cingulate, and thalamus. Taken together, these findings suggest a dissociation of brain regions linked with risky- and ambiguous-DM reflecting possible differential functionality and highlight brain alterations potentially contributing to poor decision-making in the context of substance use disorders." -32078973,,10.1016/j.drugalcdep.2020.107884,Common and distinct brain activity associated with risky and ambiguous decision-making,"['Poudel R', 'Riedel MC', 'Salo T', 'Flannery JS', 'Hill-Bowen LD', 'Eickhoff SB', 'Laird AR', 'Sutherland MT']",2020,2,4,Drug Alcohol Depend,209,,107884,"Two often-studied forms of uncertain decision-making (DM) are risky-DM (outcome probabilities known) and ambiguous-DM (outcome probabilities unknown). While DM in general is associated with activation of several brain regions, previous neuroimaging efforts suggest a dissociation between activity linked with risky and ambiguous choices. However, the common and distinct neurobiological correlates associated with risky- and ambiguous-DM, as well as their specificity when compared to perceptual-DM (as a 'control condition'), remains to be clarified. We conducted multiple meta-analyses on neuroimaging results from 151 studies to characterize common and domain-specific brain activity during risky-, ambiguous-, and perceptual-DM. When considering all DM tasks, convergent activity was observed in brain regions considered to be consituents of the canonical salience, valuation, and executive control networks. When considering subgroups of studies, risky-DM (vs. perceptual-DM) was linked with convergent activity in the striatum and anterior cingulate cortex (ACC), regions associated with reward-related processes (determined by objective functional decoding). When considering ambiguous-DM (vs. perceptual-DM), activity convergence was observed in the lateral prefrontal cortex and insula, regions implicated in affectively-neutral mental processes (e.g., cognitive control and behavioral responding; determined by functional decoding). An exploratory meta-analysis comparing brain activity between substance users and non-users during risky-DM identified reduced convergent activity among users in the striatum, cingulate, and thalamus. Taken together, these findings suggest a dissociation of brain regions linked with risky- and ambiguous-DM reflecting possible differential functionality and highlight brain alterations potentially contributing to poor decision-making in the context of substance use disorders." -32144045,,10.1016/j.bpsc.2020.01.002,"Disruptive Behavior Problems, Callous-Unemotional Traits, and Regional Gray Matter Volume in the Adolescent Brain and Cognitive Development Study","['Waller R', 'Hawes SW', 'Byrd AL', 'Dick AS', 'Sutherland MT', 'Riedel MC', 'Tobia MJ', 'Bottenhorn KL', 'Laird AR', 'Gonzalez R']",2020,1,22,Biol Psychiatry Cogn Neurosci Neuroimaging,,,,"BACKGROUND: Neurobiological differences linked to socioemotional and cognitive processing are well documented in youths with disruptive behavior disorders (DBDs), especially youths with callous-unemotional (CU) traits. The current study expanded this literature by examining gray matter volume (GMV) differences among youths with DBD with CU traits (DBDCU+), youths with DBD without CU traits (DBD-only), and youths that were typically developing (TD). METHODS: Data were from the first full sample release of the Adolescent Brain and Cognitive Development Study (mean age = 9.49 years; 49% female). We tested whether the GMVs of 11 regions of interest selected a priori differentiated between our 3 groups: DBDCU+ (n = 288), DBD-only (n = 362), and TD (n = 915). Models accounted for demographic confounders, attention-deficit/hyperactivity disorder, and intracranial volume. We examined two potential moderators of the relationship between GMVs and group membership: sex and clinically significant anxiety (i.e., primary vs. secondary CU traits subtype). RESULTS: Youths in the DBDCU+ group had lower right amygdala GMV, and youths in the DBD-only group had lower bilateral amygdala GMV relative to TD youths. Youths in the DBDCU+ group had lower bilateral hippocampal GMV, and youths in the DBD-only group had lower left hippocampal GMV relative to TD youths. Youths in the DBDCU+ group evidenced lower left insula GMV relative to TD youths. Finally, youths in the DBD-only group had lower left superior frontal gyrus and lower right caudal anterior cingulate cortex GMVs relative to TD youths. There was no moderation of associations between GMV and group membership by sex. CONCLUSIONS: Our findings implicate structural aberrations in both the amygdala and hippocampus in the etiology of DBDs, with minimal evidence for differences based on the presence or absence of CU traits." -32144045,,10.1016/j.bpsc.2020.01.002,"Disruptive Behavior Problems, Callous-Unemotional Traits, and Regional Gray Matter Volume in the Adolescent Brain and Cognitive Development Study","['Waller R', 'Hawes SW', 'Byrd AL', 'Dick AS', 'Sutherland MT', 'Riedel MC', 'Tobia MJ', 'Bottenhorn KL', 'Laird AR', 'Gonzalez R']",2020,1,22,Biol Psychiatry Cogn Neurosci Neuroimaging,,,,"BACKGROUND: Neurobiological differences linked to socioemotional and cognitive processing are well documented in youths with disruptive behavior disorders (DBDs), especially youths with callous-unemotional (CU) traits. The current study expanded this literature by examining gray matter volume (GMV) differences among youths with DBD with CU traits (DBDCU+), youths with DBD without CU traits (DBD-only), and youths that were typically developing (TD). METHODS: Data were from the first full sample release of the Adolescent Brain and Cognitive Development Study (mean age = 9.49 years; 49% female). We tested whether the GMVs of 11 regions of interest selected a priori differentiated between our 3 groups: DBDCU+ (n = 288), DBD-only (n = 362), and TD (n = 915). Models accounted for demographic confounders, attention-deficit/hyperactivity disorder, and intracranial volume. We examined two potential moderators of the relationship between GMVs and group membership: sex and clinically significant anxiety (i.e., primary vs. secondary CU traits subtype). RESULTS: Youths in the DBDCU+ group had lower right amygdala GMV, and youths in the DBD-only group had lower bilateral amygdala GMV relative to TD youths. Youths in the DBDCU+ group had lower bilateral hippocampal GMV, and youths in the DBD-only group had lower left hippocampal GMV relative to TD youths. Youths in the DBDCU+ group evidenced lower left insula GMV relative to TD youths. Finally, youths in the DBD-only group had lower left superior frontal gyrus and lower right caudal anterior cingulate cortex GMVs relative to TD youths. There was no moderation of associations between GMV and group membership by sex. CONCLUSIONS: Our findings implicate structural aberrations in both the amygdala and hippocampus in the etiology of DBDs, with minimal evidence for differences based on the presence or absence of CU traits." +32078973,PMC7127964,10.1016/j.drugalcdep.2020.107884,Common and distinct brain activity associated with risky and ambiguous decision-making,"['Poudel R', 'Riedel MC', 'Salo T', 'Flannery JS', 'Hill-Bowen LD', 'Eickhoff SB', 'Laird AR', 'Sutherland MT']",2020,4,1,Drug Alcohol Depend,209,,107884,"Two often-studied forms of uncertain decision-making (DM) are risky-DM (outcome probabilities known) and ambiguous-DM (outcome probabilities unknown). While DM in general is associated with activation of several brain regions, previous neuroimaging efforts suggest a dissociation between activity linked with risky and ambiguous choices. However, the common and distinct neurobiological correlates associated with risky- and ambiguous-DM, as well as their specificity when compared to perceptual-DM (as a 'control condition'), remains to be clarified. We conducted multiple meta-analyses on neuroimaging results from 151 studies to characterize common and domain-specific brain activity during risky-, ambiguous-, and perceptual-DM. When considering all DM tasks, convergent activity was observed in brain regions considered to be consituents of the canonical salience, valuation, and executive control networks. When considering subgroups of studies, risky-DM (vs. perceptual-DM) was linked with convergent activity in the striatum and anterior cingulate cortex (ACC), regions associated with reward-related processes (determined by objective functional decoding). When considering ambiguous-DM (vs. perceptual-DM), activity convergence was observed in the lateral prefrontal cortex and insula, regions implicated in affectively-neutral mental processes (e.g., cognitive control and behavioral responding; determined by functional decoding). An exploratory meta-analysis comparing brain activity between substance users and non-users during risky-DM identified reduced convergent activity among users in the striatum, cingulate, and thalamus. Taken together, these findings suggest a dissociation of brain regions linked with risky- and ambiguous-DM reflecting possible differential functionality and highlight brain alterations potentially contributing to poor decision-making in the context of substance use disorders." +32078973,PMC7127964,10.1016/j.drugalcdep.2020.107884,Common and distinct brain activity associated with risky and ambiguous decision-making,"['Poudel R', 'Riedel MC', 'Salo T', 'Flannery JS', 'Hill-Bowen LD', 'Eickhoff SB', 'Laird AR', 'Sutherland MT']",2020,4,1,Drug Alcohol Depend,209,,107884,"Two often-studied forms of uncertain decision-making (DM) are risky-DM (outcome probabilities known) and ambiguous-DM (outcome probabilities unknown). While DM in general is associated with activation of several brain regions, previous neuroimaging efforts suggest a dissociation between activity linked with risky and ambiguous choices. However, the common and distinct neurobiological correlates associated with risky- and ambiguous-DM, as well as their specificity when compared to perceptual-DM (as a 'control condition'), remains to be clarified. We conducted multiple meta-analyses on neuroimaging results from 151 studies to characterize common and domain-specific brain activity during risky-, ambiguous-, and perceptual-DM. When considering all DM tasks, convergent activity was observed in brain regions considered to be consituents of the canonical salience, valuation, and executive control networks. When considering subgroups of studies, risky-DM (vs. perceptual-DM) was linked with convergent activity in the striatum and anterior cingulate cortex (ACC), regions associated with reward-related processes (determined by objective functional decoding). When considering ambiguous-DM (vs. perceptual-DM), activity convergence was observed in the lateral prefrontal cortex and insula, regions implicated in affectively-neutral mental processes (e.g., cognitive control and behavioral responding; determined by functional decoding). An exploratory meta-analysis comparing brain activity between substance users and non-users during risky-DM identified reduced convergent activity among users in the striatum, cingulate, and thalamus. Taken together, these findings suggest a dissociation of brain regions linked with risky- and ambiguous-DM reflecting possible differential functionality and highlight brain alterations potentially contributing to poor decision-making in the context of substance use disorders." +32144045,PMC7214118,10.1016/j.bpsc.2020.01.002,"Disruptive Behavior Problems, Callous-Unemotional Traits, and Regional Gray Matter Volume in the Adolescent Brain and Cognitive Development Study","['Waller R', 'Hawes SW', 'Byrd AL', 'Dick AS', 'Sutherland MT', 'Riedel MC', 'Tobia MJ', 'Bottenhorn KL', 'Laird AR', 'Gonzalez R']",2020,5,8,Biol Psychiatry Cogn Neurosci Neuroimaging,5,5,481-489,"BACKGROUND: Neurobiological differences linked to socioemotional and cognitive processing are well documented in youths with disruptive behavior disorders (DBDs), especially youths with callous-unemotional (CU) traits. The current study expanded this literature by examining gray matter volume (GMV) differences among youths with DBD with CU traits (DBDCU+), youths with DBD without CU traits (DBD-only), and youths that were typically developing (TD). METHODS: Data were from the first full sample release of the Adolescent Brain and Cognitive Development Study (mean age = 9.49 years; 49% female). We tested whether the GMVs of 11 regions of interest selected a priori differentiated between our 3 groups: DBDCU+ (n = 288), DBD-only (n = 362), and TD (n = 915). Models accounted for demographic confounders, attention-deficit/hyperactivity disorder, and intracranial volume. We examined two potential moderators of the relationship between GMVs and group membership: sex and clinically significant anxiety (i.e., primary vs. secondary CU traits subtype). RESULTS: Youths in the DBDCU+ group had lower right amygdala GMV, and youths in the DBD-only group had lower bilateral amygdala GMV relative to TD youths. Youths in the DBDCU+ group had lower bilateral hippocampal GMV, and youths in the DBD-only group had lower left hippocampal GMV relative to TD youths. Youths in the DBDCU+ group evidenced lower left insula GMV relative to TD youths. Finally, youths in the DBD-only group had lower left superior frontal gyrus and lower right caudal anterior cingulate cortex GMVs relative to TD youths. There was no moderation of associations between GMV and group membership by sex. CONCLUSIONS: Our findings implicate structural aberrations in both the amygdala and hippocampus in the etiology of DBDs, with minimal evidence for differences based on the presence or absence of CU traits." +32144045,PMC7214118,10.1016/j.bpsc.2020.01.002,"Disruptive Behavior Problems, Callous-Unemotional Traits, and Regional Gray Matter Volume in the Adolescent Brain and Cognitive Development Study","['Waller R', 'Hawes SW', 'Byrd AL', 'Dick AS', 'Sutherland MT', 'Riedel MC', 'Tobia MJ', 'Bottenhorn KL', 'Laird AR', 'Gonzalez R']",2020,5,8,Biol Psychiatry Cogn Neurosci Neuroimaging,5,5,481-489,"BACKGROUND: Neurobiological differences linked to socioemotional and cognitive processing are well documented in youths with disruptive behavior disorders (DBDs), especially youths with callous-unemotional (CU) traits. The current study expanded this literature by examining gray matter volume (GMV) differences among youths with DBD with CU traits (DBDCU+), youths with DBD without CU traits (DBD-only), and youths that were typically developing (TD). METHODS: Data were from the first full sample release of the Adolescent Brain and Cognitive Development Study (mean age = 9.49 years; 49% female). We tested whether the GMVs of 11 regions of interest selected a priori differentiated between our 3 groups: DBDCU+ (n = 288), DBD-only (n = 362), and TD (n = 915). Models accounted for demographic confounders, attention-deficit/hyperactivity disorder, and intracranial volume. We examined two potential moderators of the relationship between GMVs and group membership: sex and clinically significant anxiety (i.e., primary vs. secondary CU traits subtype). RESULTS: Youths in the DBDCU+ group had lower right amygdala GMV, and youths in the DBD-only group had lower bilateral amygdala GMV relative to TD youths. Youths in the DBDCU+ group had lower bilateral hippocampal GMV, and youths in the DBD-only group had lower left hippocampal GMV relative to TD youths. Youths in the DBDCU+ group evidenced lower left insula GMV relative to TD youths. Finally, youths in the DBD-only group had lower left superior frontal gyrus and lower right caudal anterior cingulate cortex GMVs relative to TD youths. There was no moderation of associations between GMV and group membership by sex. CONCLUSIONS: Our findings implicate structural aberrations in both the amygdala and hippocampus in the etiology of DBDs, with minimal evidence for differences based on the presence or absence of CU traits." +32483374,,10.1038/s41586-020-2314-9,Variability in the analysis of a single neuroimaging dataset by many teams,"['Botvinik-Nezer R', 'Holzmeister F', 'Camerer CF', 'Dreber A', 'Huber J', 'Johannesson M', 'Kirchler M', 'Iwanir R', 'Mumford JA', 'Adcock RA', 'Avesani P', 'Baczkowski BM', 'Bajracharya A', 'Bakst L', 'Ball S', 'Barilari M', 'Bault N', 'Beaton D', 'Beitner J', 'Benoit RG', 'Berkers RMWJ', 'Bhanji JP', 'Biswal BB', 'Bobadilla-Suarez S', 'Bortolini T', 'Bottenhorn KL', 'Bowring A', 'Braem S', 'Brooks HR', 'Brudner EG', 'Calderon CB', 'Camilleri JA', 'Castrellon JJ', 'Cecchetti L', 'Cieslik EC', 'Cole ZJ', 'Collignon O', 'Cox RW', 'Cunningham WA', 'Czoschke S', 'Dadi K', 'Davis CP', 'Luca A', 'Delgado MR', 'Demetriou L', 'Dennison JB', 'Di X', 'Dickie EW', 'Dobryakova E', 'Donnat CL', 'Dukart J', 'Duncan NW', 'Durnez J', 'Eed A', 'Eickhoff SB', 'Erhart A', 'Fontanesi L', 'Fricke GM', 'Fu S', 'Galvan A', 'Gau R', 'Genon S', 'Glatard T', 'Glerean E', 'Goeman JJ', 'Golowin SAE', 'Gonzalez-Garcia C', 'Gorgolewski KJ', 'Grady CL', 'Green MA', 'Guassi Moreira JF', 'Guest O', 'Hakimi S', 'Hamilton JP', 'Hancock R', 'Handjaras G', 'Harry BB', 'Hawco C', 'Herholz P', 'Herman G', 'Heunis S', 'Hoffstaedter F', 'Hogeveen J', 'Holmes S', 'Hu CP', 'Huettel SA', 'Hughes ME', 'Iacovella V', 'Iordan AD', 'Isager PM', 'Isik AI', 'Jahn A', 'Johnson MR', 'Johnstone T', 'Joseph MJE', 'Juliano AC', 'Kable JW', 'Kassinopoulos M', 'Koba C', 'Kong XZ', 'Koscik TR', 'Kucukboyaci NE', 'Kuhl BA', 'Kupek S', 'Laird AR', 'Lamm C', 'Langner R', 'Lauharatanahirun N', 'Lee H', 'Lee S', 'Leemans A', 'Leo A', 'Lesage E', 'Li F', 'Li MYC', 'Lim PC', 'Lintz EN', 'Liphardt SW', 'Losecaat Vermeer AB', 'Love BC', 'Mack ML', 'Malpica N', 'Marins T', 'Maumet C', 'McDonald K', 'McGuire JT', 'Melero H', 'Mendez Leal AS', 'Meyer B', 'Meyer KN', 'Mihai G', 'Mitsis GD', 'Moll J', 'Nielson DM', 'Nilsonne G', 'Notter MP', 'Olivetti E', 'Onicas AI', 'Papale P', 'Patil KR', 'Peelle JE', 'Perez A', 'Pischedda D', 'Poline JB', 'Prystauka Y', 'Ray S', 'Reuter-Lorenz PA', 'Reynolds RC', 'Ricciardi E', 'Rieck JR', 'Rodriguez-Thompson AM', 'Romyn A', 'Salo T', 'Samanez-Larkin GR', 'Sanz-Morales E', 'Schlichting ML', 'Schultz DH', 'Shen Q', 'Sheridan MA', 'Silvers JA', 'Skagerlund K', 'Smith A', 'Smith DV', 'Sokol-Hessner P', 'Steinkamp SR', 'Tashjian SM', 'Thirion B', 'Thorp JN', 'Tinghog G', 'Tisdall L', 'Tompson SH', 'Toro-Serey C', 'Torre Tresols JJ', 'Tozzi L', 'Truong V', 'Turella L', ""van 't Veer AE"", 'Verguts T', 'Vettel JM', 'Vijayarajah S', 'Vo K', 'Wall MB', 'Weeda WD', 'Weis S', 'White DJ', 'Wisniewski D', 'Xifra-Porxas A', 'Yearling EA', 'Yoon S', 'Yuan R', 'Yuen KSL', 'Zhang L', 'Zhang X', 'Zosky JE', 'Nichols TE', 'Poldrack RA', 'Schonberg T']",2020,6,8,Nature,582,7810,84-88,"Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses(1). The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset(2-5). Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed." diff --git a/assets/images/papers/nature.png b/assets/images/papers/nature.png new file mode 100644 index 0000000000000000000000000000000000000000..14fb561dae4c4f5c32eb82f1e4da31312638cb63 GIT binary patch literal 13323 zcmeHt^;cX$ux4=A;LhN|g4^Kk7J|D6m*5hDyF0-l!QCwcXOQ5|;O>Jnz>@dgzTN!? z_Ltpz&h+W-Tm4m6-+Oziy1qy?6*+j<31V2~DbAhU~njgneHeP>E%Qq^<8>|(P zM)p)xy5(6aMv=z*V6}tj(&J1au1wqZx^>GlKgf^sT;H=c>vM#IwsM`cL_8RRtZG(5 z&Mmj__y}R^`lV<_mppA_1|sRy!2XcBn`dfJPuC9dOe@C|KXI&1tJ~?RSUhVH5@nnH~y``X!o!)Y{{;qif zr-yzAkdQQ1Bxp%`N-%zZa718%jQH*T)=S;00yZ4+7m{81K(?eJOnvrkLx<9XNkw!* zzFA5|g5$>^jr>=shG^GsHM)ou>M^mZ%dBlj#}DcQ6NG+wexbY-L4n;E4JZhV86U&D zP?dGya4Zh@5y;c*If01y+Ql`@ex#f{mHuz1@FOUWSK_gCANa8b4Ts zi+m@jCxOOQ63kd$R)iXuzZVT);e!>WC#J$(3Z69Ll)p`M;e-KrM*)>@lgaAeTbw^G zD%eXK0r}>iJ7c&sO0%Wc1R6W?OdxjRI*?;htYtTo)8SXpo7MB28S$s>djlk 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AND (\"2012/01/01\"[PDAT] : \"3000/12/31\"[PDAT]): 110\n", + "Total number of publications containing \"Laird AR\"[AUTH] AND (\"2012/01/01\"[PDAT] : \"3000/12/31\"[PDAT]): 111\n", "Total number of publications containing \"Sutherland MT\"[AUTH] AND (\"2012/01/01\"[PDAT] : \"3000/12/31\"[PDAT]): 34\n" ] } @@ -119,8 +119,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "124\n", - "121\n" + "125\n", + "122\n" ] } ], @@ -167,7 +167,7 @@ " 'dev cogn neurosci' 'mol psychiatry' 'netw neurosci' 'j sex med'\n", " 'sleep med rev' 'front ict' 'nat hum behav' 'exp clin psychopharmacol'\n", " 'sci adv' 'npj sci learn' 'front neurol' 'drug alcohol depend'\n", - " 'biol psychiatry cogn neurosci neuroimaging']\n" + " 'biol psychiatry cogn neurosci neuroimaging' 'nature']\n" ] } ], @@ -185,8 +185,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "New file created for 32144045\n", - "New file created for 32144045\n" + "New file created for 32483374\n" ] } ], diff --git a/papers/_posts/2020-06-08-botvinik-nezer-variability-in-the.md b/papers/_posts/2020-06-08-botvinik-nezer-variability-in-the.md new file mode 100644 index 00000000..cbf807a2 --- /dev/null +++ b/papers/_posts/2020-06-08-botvinik-nezer-variability-in-the.md @@ -0,0 +1,40 @@ +--- +layout: paper +title: "Variability in the analysis of a single neuroimaging dataset by many teams" +nickname: 2020-06-08-botvinik-nezer-variability-in-the +authors: "Botvinik-Nezer R, Holzmeister F, Camerer CF, Dreber A, Huber J, Johannesson M, Kirchler M, Iwanir R, Mumford JA, Adcock RA, Avesani P, Baczkowski BM, Bajracharya A, Bakst L, Ball S, Barilari M, Bault N, Beaton D, Beitner J, Benoit RG, Berkers RMWJ, Bhanji JP, Biswal BB, Bobadilla-Suarez S, Bortolini T, Bottenhorn KL, Bowring A, Braem S, Brooks HR, Brudner EG, Calderon CB, Camilleri JA, Castrellon JJ, Cecchetti L, Cieslik EC, Cole ZJ, Collignon O, Cox RW, Cunningham WA, Czoschke S, Dadi K, Davis CP, Luca A, Delgado MR, Demetriou L, Dennison JB, Di X, Dickie EW, Dobryakova E, Donnat CL, Dukart J, Duncan NW, Durnez J, Eed A, Eickhoff SB, Erhart A, Fontanesi L, Fricke GM, Fu S, Galvan A, Gau R, Genon S, Glatard T, Glerean E, Goeman JJ, Golowin SAE, Gonzalez-Garcia C, Gorgolewski KJ, Grady CL, Green MA, Guassi Moreira JF, Guest O, Hakimi S, Hamilton JP, Hancock R, Handjaras G, Harry BB, Hawco C, Herholz P, Herman G, Heunis S, Hoffstaedter F, Hogeveen J, Holmes S, Hu CP, Huettel SA, Hughes ME, Iacovella V, Iordan AD, Isager PM, Isik AI, Jahn A, Johnson MR, Johnstone T, Joseph MJE, Juliano AC, Kable JW, Kassinopoulos M, Koba C, Kong XZ, Koscik TR, Kucukboyaci NE, Kuhl BA, Kupek S, Laird AR, Lamm C, Langner R, Lauharatanahirun N, Lee H, Lee S, Leemans A, Leo A, Lesage E, Li F, Li MYC, Lim PC, Lintz EN, Liphardt SW, Losecaat Vermeer AB, Love BC, Mack ML, Malpica N, Marins T, Maumet C, McDonald K, McGuire JT, Melero H, Mendez Leal AS, Meyer B, Meyer KN, Mihai G, Mitsis GD, Moll J, Nielson DM, Nilsonne G, Notter MP, Olivetti E, Onicas AI, Papale P, Patil KR, Peelle JE, Perez A, Pischedda D, Poline JB, Prystauka Y, Ray S, Reuter-Lorenz PA, Reynolds RC, Ricciardi E, Rieck JR, Rodriguez-Thompson AM, Romyn A, Salo T, Samanez-Larkin GR, Sanz-Morales E, Schlichting ML, Schultz DH, Shen Q, Sheridan MA, Silvers JA, Skagerlund K, Smith A, Smith DV, Sokol-Hessner P, Steinkamp SR, Tashjian SM, Thirion B, Thorp JN, Tinghog G, Tisdall L, Tompson SH, Toro-Serey C, Torre Tresols JJ, Tozzi L, Truong V, Turella L, van 't Veer AE, Verguts T, Vettel JM, Vijayarajah S, Vo K, Wall MB, Weeda WD, Weis S, White DJ, Wisniewski D, Xifra-Porxas A, Yearling EA, Yoon S, Yuan R, Yuen KSL, Zhang L, Zhang X, Zosky JE, Nichols TE, Poldrack RA, Schonberg T" +year: "2020" +journal: "Nature" +volume: 582 +issue: 7810 +pages: 84-88 +is_published: true +image: /assets/images/papers/nature.png +projects: [nimare] +tags: [preprint] + +# Text +fulltext: https://orbi.uliege.be/handle/2268/247997 +pdf: +pdflink: +pmcid: +preprint: https://www.biorxiv.org/content/10.1101/843193v1 +supplement: + +# Links +doi: "10.1038/s41586-020-2314-9" +pmid: 32483374 + +# Data and code +github: ["https://github.com/poldrack/narps"] +neurovault: ["6047", "6048", "6051"] +openneuro: ["ds001734"] +figshare: +figshare_names: +osf: +--- +{% include JB/setup %} + +# Abstract + +Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses(1). The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset(2-5). Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed. diff --git a/team/_posts/2017-05-13-perez-aleymi.md b/team/_posts/2017-05-13-perez-aleymi.md index ad0064fc..eaf1fc7e 100644 --- a/team/_posts/2017-05-13-perez-aleymi.md +++ b/team/_posts/2017-05-13-perez-aleymi.md @@ -5,7 +5,7 @@ position: Research Assistant department: handle: aperez nickname: Aleymi -science_names: [Perez A] +science_names: [Perez AJ] image: /assets/images/team/aleymi-perez.jpg alumni: false