From 968ae668e339a6e5483a95fab5c459a96e9a2d17 Mon Sep 17 00:00:00 2001 From: Katie Bottenhorn Date: Fri, 30 Oct 2020 09:55:22 -0400 Subject: [PATCH 1/4] extremely old post and poster --- .../2019-06-12-bottenhorn-physics-poster.md | 33 +++++++++++++++++++ .../_posts/2017-04-06-bottenhorn-katherine.md | 3 +- 2 files changed, 34 insertions(+), 2 deletions(-) create mode 100644 posters/_posts/2019-06-12-bottenhorn-physics-poster.md diff --git a/posters/_posts/2019-06-12-bottenhorn-physics-poster.md b/posters/_posts/2019-06-12-bottenhorn-physics-poster.md new file mode 100644 index 00000000..6a2c0cf8 --- /dev/null +++ b/posters/_posts/2019-06-12-bottenhorn-physics-poster.md @@ -0,0 +1,33 @@ +--- +layout: poster +title: "Large-scale brain networks underlying domain-specific +memory, intelligence, and academic performance" +nickname: 2019-06-12-bottenhorn-physics-poster +authors: "Bottenhorn KL, Salo T, Sutherland MT, Laird AR" +year: "2019" +conference: "HBM" +image: /assets/images/posters/2019-06-12-bottenhorn-physics-poster.png +projects: [athena] +tags: [] + +# Content +fulltext: "https://f1000research.com/posters/7-1222" +pdf: + +# Links +doi: "10.7490/f1000research.1115906.1" + +# Data and code +github: ["https://github.com/62442katieb/idconn-retrieval/tree/master/ohbm2019"] +neurovault: +openneuro: +figshare: +figshare_names: +osf: +f1000: +--- +{% include JB/setup %} + +# Abstract + +Functional decoding is an analytic method that seeks to determine the most consistent brain structure-function relationships; this approach typically relies on a large database of neuroimaging results. Two frameworks, Neurosynth (NS) and BrainMap (BM), offer quantitative functional decoding free of researcher bias, but their implementations differ as NS annotates each study with a bag-of-words approach, while BM relies on a structured vocabulary. To assess these differences, we performed a quantitative comparison by decoding a set of 15 ROIs using both NS and BM. NS terms were coded as “functional” (functional or subject-related) or “non-functional” (non-content or anatomical) and compared to BM terms. We observed that 43% of NS’s terms were functional, with 80% of those not corresponding to a term in BM’s taxonomy. Conversely, of BM’s terms, 44% were not represented in NS’s lexicon. Further analysis revealed that characteristics of decoded ROIs (i.e., size, false positive activation rate) were unrelated to the proportion of noise in NS decoding results or the number of significant terms returned by BM. Average correlation of NS terms analogous to BM terms was 0.09, compared to an average correlation of 0.36 for the top 50 functional NS terms. Overall, we observed that NS’s functional terms provide high specificity, but require filtering through many non-informative terms. In contrast, BM provides broad descriptions that less accurately relate function to brain activations. diff --git a/team/_posts/2017-04-06-bottenhorn-katherine.md b/team/_posts/2017-04-06-bottenhorn-katherine.md index c0b06495..70320a9f 100644 --- a/team/_posts/2017-04-06-bottenhorn-katherine.md +++ b/team/_posts/2017-04-06-bottenhorn-katherine.md @@ -18,9 +18,8 @@ osf: fq7db publons: researchgate: Katherine_Bottenhorn scholar: ZXxr85IAAAAJ -site: katiebottenhorn.com twitter: 62442katieb --- -Katie is a fourth-year graduate student in the Department of Psychology at Florida International University, specializing in Cognitive Neuroscience. She graduated from Auburn University (Auburn, AL) with dual Bachelor of Arts degrees in Chemistry and Psychology. Katie is interested in how individual differences in large-scale brain network topology are related to biological, behavioral, and environmental differences in children and adults. Additionally, she is assisting with the NIH-funded Adolescent Brain and Cognitive Development (ABCD) Study, which will track biological and behavioral development in participants though adolescence. +Katie is a fifth-year graduate student in the Department of Psychology at Florida International University, specializing in Cognitive Neuroscience. She graduated from Auburn University (Auburn, AL) with dual Bachelor of Arts degrees in Chemistry and Psychology. Katie is interested in how individual variability in large-scale brain network topology is related to biological, behavioral, and environmental differences in children and adults. Additionally, she is assisting with the NIH-funded Adolescent Brain and Cognitive Development (ABCD) Study, which will track biological and behavioral development in participants though adolescence. From 84377492006ad6b405d96140995614f61a7e05b1 Mon Sep 17 00:00:00 2001 From: Katie Bottenhorn Date: Fri, 30 Oct 2020 10:33:51 -0400 Subject: [PATCH 2/4] update personal bio --- team/_posts/2017-04-06-bottenhorn-katherine.md | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/team/_posts/2017-04-06-bottenhorn-katherine.md b/team/_posts/2017-04-06-bottenhorn-katherine.md index 70320a9f..d283df2e 100644 --- a/team/_posts/2017-04-06-bottenhorn-katherine.md +++ b/team/_posts/2017-04-06-bottenhorn-katherine.md @@ -15,11 +15,15 @@ email: kbott006@fiu.edu github: 62442katieb orcid: 0000-0002-7796-8795 osf: fq7db -publons: +publons: 2905860 researchgate: Katherine_Bottenhorn scholar: ZXxr85IAAAAJ twitter: 62442katieb --- -Katie is a fifth-year graduate student in the Department of Psychology at Florida International University, specializing in Cognitive Neuroscience. She graduated from Auburn University (Auburn, AL) with dual Bachelor of Arts degrees in Chemistry and Psychology. Katie is interested in how individual variability in large-scale brain network topology is related to biological, behavioral, and environmental differences in children and adults. Additionally, she is assisting with the NIH-funded Adolescent Brain and Cognitive Development (ABCD) Study, which will track biological and behavioral development in participants though adolescence. +Katie is a sixth-year graduate student in the Department of Psychology at Florida International University, specializing in Cognitive Neuroscience. She graduated from Auburn University (Auburn, AL) with dual Bachelor of Arts degrees in Chemistry and Psychology. Katie is interested in how large-scale brain network topology varies both between- and within-individuals over the course of everyday life. She is especially interested in how hormonal fluctuations associated with the menstrual cycle and hormonal contraceptives contribute to this variability, and how this differs with respect to changes in sleep, exerise, and stress. To assess these factors, she and [Taylor Salo](/team/salo-taylor) designed and launched the Dense Investigation of Variaibility in Affect (DIVA) Study, a longitudinal study using neuroimaging, behavioral, and endocrine measures to track fluctuations in sleep, exercise, stress, and mood over the course of three complete menstrual cycles in individuals using different forms of hormonal contraceptives, in February 2020. + +Outside of her graduate work, Katie is the current secretary of the Organization for Human Brain Mapping's Open Science Special Interest Group and an active member of the open (neuro)science community. She has contributed to a number of open source software packages including Nipype, metaCurious, NiMARE, and phys2bids, as well as in-lab pipeline development for a number of meta-analytic and neuroimaging projects (all code available [on GitHub](https://github.com/NBCLab/)). Katie is currently reworking one such pipeline, [IDConn](https://github.com/NBCLab/IDConn), into a configurable Python workflow for other researchers to use in studying individual variability in functional network topology using fMRI data. + +Since 2016, she has been assisting with data collection for the NIH-funded Adolescent Brain and Cognitive Development (ABCD) Study, a multi-site longitudinal study tracking biological and behavioral development in over 10,000 participants though adolescence. Katie has additionally assisted with study design for NBC Lab projects including [DIVA](/projects/diva) and [SEAAS](/projects/seaas), in addition to setting up physiological recording technology and assisting with multi-echo MRI sequence development/testing at FIU's Center for Imaging Science. From 3b82739fffd714868ff3491653a04a49c671819c Mon Sep 17 00:00:00 2001 From: Katie Bottenhorn Date: Fri, 30 Oct 2020 13:00:18 -0400 Subject: [PATCH 3/4] added to DIVA description --- projects/_posts/2018-10-05-diva.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/projects/_posts/2018-10-05-diva.md b/projects/_posts/2018-10-05-diva.md index 5dc16f31..7b3ab2d7 100644 --- a/projects/_posts/2018-10-05-diva.md +++ b/projects/_posts/2018-10-05-diva.md @@ -23,4 +23,5 @@ osf: --- {% include JB/setup %} -DIVA is a new study in which we will acquire a large amount of neuroimaging, neuropsychological, demographic, and physiological data for a small sample of ~3 participants. +DIVA is a 3-month longitudinal study in which we acquired weekly neuroimaging and electrophysiological data, in addition to biweekly endocrine, neuropsychological, and actigraphic data for a small sample of ~3 participants to capture fluctuations in the brain, sleep, exercise, mood, and stress over the course of three complete menstrual cycles. Participants completed twice-weekly self-report questionnaires about their sleep, exercise, mood, stress, contraceptive use, and physical state; weekly 2-hour MRI sessions, including an assortment of cognitive tasks in addition to naturalistic movie-watching, resting, and structural scans, with concurrent electrocardiogram, electrodermal activity, and respiration recordings; twice-weekly vocal recordings; and twice weekly saliva sample collection, for measuring hormones. Additionally, participants wore FitBit activity trackers for the duration of the study, which provide measures of heart rate, sleep, exercise, etc. daily over the course of the study. These data will provide an insight into sources of variability in brain structure and function, across cognitive and behavioral contexts, as well as how they interact over the course of everyday life. + From 8269dbc9474e589999eab44e3adcb77c93aa1cb5 Mon Sep 17 00:00:00 2001 From: Katie Bottenhorn Date: Fri, 30 Oct 2020 13:01:12 -0400 Subject: [PATCH 4/4] added note about covid-halt to DIVA description --- projects/_posts/2018-10-05-diva.md | 1 + 1 file changed, 1 insertion(+) diff --git a/projects/_posts/2018-10-05-diva.md b/projects/_posts/2018-10-05-diva.md index 7b3ab2d7..b6823491 100644 --- a/projects/_posts/2018-10-05-diva.md +++ b/projects/_posts/2018-10-05-diva.md @@ -25,3 +25,4 @@ osf: DIVA is a 3-month longitudinal study in which we acquired weekly neuroimaging and electrophysiological data, in addition to biweekly endocrine, neuropsychological, and actigraphic data for a small sample of ~3 participants to capture fluctuations in the brain, sleep, exercise, mood, and stress over the course of three complete menstrual cycles. Participants completed twice-weekly self-report questionnaires about their sleep, exercise, mood, stress, contraceptive use, and physical state; weekly 2-hour MRI sessions, including an assortment of cognitive tasks in addition to naturalistic movie-watching, resting, and structural scans, with concurrent electrocardiogram, electrodermal activity, and respiration recordings; twice-weekly vocal recordings; and twice weekly saliva sample collection, for measuring hormones. Additionally, participants wore FitBit activity trackers for the duration of the study, which provide measures of heart rate, sleep, exercise, etc. daily over the course of the study. These data will provide an insight into sources of variability in brain structure and function, across cognitive and behavioral contexts, as well as how they interact over the course of everyday life. +DIVA was launched in February 2020 and was unfortunately discontinued in March 2020 due to the COVID-19 pandemic. \ No newline at end of file