https://www.humanconnectome.org/study/hcp-young-adult
The Human Connectome Project (HCP) has tackled key aspects of this challenge by charting the neural pathways that underlie brain function and behavior, including high-quality neuroimaging data in over 1100 healthy young adults.
https://www.humanconnectome.org/study/hcp-lifespan-development
Childhood and adolescence are times of dramatic physical, emotional, social, and intellectual growth and change. Yet there is much we do not know about how normal development and childhood experiences (learning to read, playing a sport, or interacting socially) shape the brain’s wiring.
https://www.humanconnectome.org/study/hcp-lifespan-aging
Changes in brain structure and function are a normal part of the aging process from middle age through older adulthood. In the last decade, an explosion of work has focused on brain structure in disorders that occur as we age. Yet, relatively few studies have focused on healthy aging of brain circuitry and how it varies across people.
https://www.humanconnectome.org/study/lifespan-baby-connectome-project
The LifeSpan Baby Connectome Project (BCP) will explore human brain development from birth through early childhood, focusing on factors that contribute to healthy brain development.
https://www.humanconnectome.org/study/lifespan-developing-human-connectome-project
The Developing Human Connectome Project (dHCP), led by King’s College London, Imperial College London and Oxford University, aims to make major scientific progress by creating the first 4-dimensional connectome of early life. Our goal is to create a dynamic map of human brain connectivity from 20 to 44 weeks post-conceptional age, which will link together imaging, clinical, behavioural, and genetic information. This unique setting, with imaging and collateral data in an expandable open-source informatics structure, will permit wide use by the scientific community, and to undertake pioneer studies into normal and abnormal development by studying well-phenotyped and genotyped group of infants with specific genetic and environmental risks that could lead to Autistic Spectrum Disorder or Cerebral Palsy.
https://www.humanconnectome.org/study/alzheimers-disease-connectome-project
The Alzheimer’s Disease Connectome Project (ADCP) will collect data from participants who range from cognitively healthy to those with dementia due to Alzheimer’s disease. The goal is to develop robust technology to accurately stage Alzheimer’s disease across the full spectrum of its progression on an individual subject basis.
https://www.humanconnectome.org/study/amish-connectome-project
The Amish Connectome Project (ACP) will collect data from extensive, multi-generational Old Order Amish (OOA) families with a high prevalence of mental disorders.
People who have macular degeneration often lose the ability to see in the part of vision normally used for daily tasks such as reading and recognizing faces. This often debilitating loss is expected to afflict 3 million US citizens by 2020. An essential health-related goal is therefore to develop strategies that allow patients with macular degeneration to make better use of their spared peripheral vision. Despite loss of central vision, many patients learn to successfully navigate the world, becoming adept at using peripheral vision for tasks normally done with central vision.
https://www.humanconnectome.org/study/connectomes-related-anxiety-depression
The Connectomes Related to Anxiety and Depression in Adolescents Project is a collaborative effort among researchers at the Massachusetts General Hospital (MGH), Massachusetts Institute of Technology (MIT), McLean Hospital, and Boston University. We will focus on understanding psychiatric disorders in adolescence, in particular those associated with two leading causes of death in adolescents and young adults (suicide and substance-abuse related accidents). Our research is guided by the “Acute Threat/Fear” and the “Reward/Prediction Error” construct.
Frontotemporal Dementia Connectomics (FTDConn) - Neurodegenerative disease is a major public health problem. Frontotemporal degeneration (FTD) is a clinical neurodegenerative condition that affects both gray matter (GM) and white matter (WM) and causes a network disorder.
The HCP consortium is pleased to announce the release of fully reprocessed 7T fMRI data for 184 HCP-Young Adult (HCP-YA) subjects for download on ConnectomeDB. The rerelease corrects the error in the 7T preprocessed fMRI data for all subjects and includes other updates, plus the addition of multirun ICA FIX-cleaned 7T retinotopy data.
The ABCD Data Repository houses all data generated by the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study. The ABCD Study(R) is a prospective longitudinal study starting at the ages of 9-10 and following participants for 10 years. The study includes a diverse sample of nearly 12,000 youth enrolled at 21 research sites across the country.
The ENIGMA Consortium brings together researchers in imaging genomics to understand brain structure, function, and disease, based on brain imaging and genetic data. We welcome brain researchers, imagers, geneticists, methods developers, and others interested in cracking the neuro-genetic code!
https://www.med.upenn.edu/bbl/philadelphianeurodevelopmentalcohort.html
The Philadelphia Neurodevelopmental Cohort (PNC) is a research initiative funded by NIMH through the American Reinvestment and Recovery Act of 2009 (ARRA). The initiative focuses on characterizing brain and behavior interaction with genetics. The PNC includes a population-based sample of over 9500 individuals from the greater Philadelphia area, ages 8-21 years who received medical care at the CHOP network.
https://fcon_1000.projects.nitrc.org/indi/abide/
the Autism Brain Imaging Data Exchange (ABIDE) initiative has aggregated functional and structural brain imaging data collected from laboratories around the world to accelerate our understanding of the neural bases of autism. With the ultimate goal of facilitating discovery science and comparisons across samples, the ABIDE initiative now includes two large-scale collections: ABIDE I and ABIDE II.
The Alzheimer’s Disease Neuroimaging Initiative (ADNI) unites researchers with study data as they work to define the progression of Alzheimer’s disease (AD). ADNI researchers collect, validate and utilize data, including MRI and PET images, genetics, cognitive tests, CSF and blood biomarkers as predictors of the disease. Study resources and data from the North American ADNI study are available through this website, including Alzheimer’s disease patients, mild cognitive impairment subjects, and elderly controls.
The MyConnectome project has characterized how the brain of one person changes over the course of more than one year. It is almost certainly the most ambitious study of a single living person’s brain ever attempted. The data will provide new insights into the dynamics of brain activity and their relationship to bodily metabolism and psychological function. The project is also openly sharing a large amount of biological data for future reuse.
SchizConnect is a search-and-download virtual database for public schizophrenia neuroimaging data. The mediation software underlying SchizConnect integrates schizophrenia neuroimaging and related data from disparate, heterogeneous databases. This gives you access to multi-site, multi-dimensional, multi-modal data all in one place.
http://naturalscenesdataset.org/
The Natural Scenes Dataset (NSD) is a large-scale fMRI dataset conducted at ultra-high-field (7T) strength at the Center of Magnetic Resonance Research (CMRR) at the University of Minnesota.
The human brain processes vast amounts of diverse input that are continuously gathered across the senses. However, most experiments study the brain via simplified stimuli that do little to resemble the complexity of a natural environment — a mismatch that must be addressed if we are to better understand how the brain works.
http://fcon_1000.projects.nitrc.org/fcpClassic/FcpTable.html
On behalf of the ‘1000 Functional Connectomes’ Project, we are pleased to announce the unrestricted public release of 1200+ ‘resting state’ functional MRI (R-fMRI) datasets independently collected at 33 sites.
http://rfmri.org/RuminationfMRIData
This dataset was used to investigate the brain mechanism underlying rumination state (Chen et al., 2020, NeuroImage). The data was shared through the R-fMRI Maps Project (RMP).
https://www.nature.com/articles/s41597-019-0052-3
A free and open platform for validating and sharing BIDS-compliant MRI, PET, MEG, EEG, and iEEG data 23,339 Participants 661 Public Datasets
A place where researchers can publicly store and share unthresholded statistical maps, parcellations, and atlases produced by MRI and PET studies.
https://en.wikipedia.org/wiki/List_of_neuroscience_databases
A number of online neuroscience databases are available which provide information regarding gene expression, neurons, macroscopic brain structure, and neurological or psychiatric disorders. Some databases contain descriptive and numerical data, some to brain function, others offer access to 'raw' imaging data, such as postmortem brain sections or 3D MRI and fMRI images. Some focus on the human brain, others on non-human.
https://github.com/Conxz/multiBrain
A list of brain imaging databases with multiple (e.g., more than 3) scans per subject. Feel free to update the list via 'pull requests'.
https://www.re3data.org/search?query=neuroimaging
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