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http://mialab.mrn.org/data/index.html

An MRI data set that demonstrates the utility of a mega-analytic approach by identifying the effects of age and gender on the resting-state networks (RSNs) of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12-71 years). Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. RSNs were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described, provide a useful baseline for future investigations of brain networks in health and disease.

Proper citation: MIALAB - Resting State Data (RRID:SCR_008914) Copy   

•   Source: SciCrunch Registry

http://www.nimh.nih.gov/funding/clinical-trials-for-researchers/datasets/nimh-procedures-for-requesting-data-sets.shtml

A listing of data sets from NIMH-supported clinical trials. Limited Access Datasets are available from numerous NIMH studies. NIMH requires all investigators seeking access to data from NIMH-supported trials held by NIMH to execute and submit as their request the appropriate Data Use Certification pertaining to the trial. The datasets distributed by NIMH are referred to as limited access datasets because access is limited to qualified researchers who complete Data Use Certifications.

Proper citation: Limited Access Datasets From NIMH Clinical Trials (RRID:SCR_005614) Copy   

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https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/eddyqc

Software tool allows to assess dMRI data both at single subject and group levels.Calculates average SNR across all voxels within brain mask to give summary measure of overall quality of dataset. Used to generate single subject and study wise reports and databases.

Proper citation: eddyqc (RRID:SCR_024936) Copy   

•   Source: SciCrunch Registry

https://github.com/xinhe-lab/GSFA

Software R package that performs sparse factor analysis and differential gene expression discovery simultaneously on single cell CRISPR screening data.

Proper citation: Guided Sparse Factor Analysis (RRID:SCR_025023) Copy   

•   Source: SciCrunch Registry

https://beadl.org

Universal framework for describing behavioral tasks. Language to abstract and standardize behavioral task descriptions on two layers. Graphical layer specifies elements to describe behavioral tasks as state machine in formal flow diagram and how task controlling system interacts with subject. This graphical layer has been designed to be easy to understand while retaining all aspects of behavioral task. The second layer is corresponding, XML-based description of task. This layer forms rigid, yet extensible foundation of BEADL and hides hardware implementation related details form graphical representation.BEADL-specific extension for Neurodata Without Borders data standard defines how behavioral outcomes of task are stored in NWB including corresponding BEADL task description.

Proper citation: BEADL:BEhavioral tAsk Description Language (RRID:SCR_025464) Copy   

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http://www.bios.unc.edu/research/genomic_software/Matrix_eQTL/

Software tool for ultra fast eQTL analysis via large matrix operations.

Proper citation: MatrixEQTL (RRID:SCR_025513) Copy   

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https://portal.brain-map.org/genetic-tools/genetic-tools-atlas

Searchable catalog of enhancer-adeno-associated viruses (AAVs) that have been developed and tested at the Allen Institute for Brain Science. We present a suite of enhancer AAVs that can provide access to specific cell types when delivered to the whole brain. Multiple epigenomic and transcriptomic datasets were interrogated to reveal candidate enhancers that are selectively accessible in particular cell populations. Enhancer AAVs were constructed and screened for desirable expression and a sizeable subset of enhancer AAVs were subjected to further characterization by single cell transcriptomics and/or brain-wide expression imaging in mouse. In the GTA, we present a large toolkit for selective gene expression in cell types of interest. Genetic Tools Atlas is part of the growing Brain Knowledge Platform.

Proper citation: Genetic Tools Atlas (RRID:SCR_025643) Copy   

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https://kimlab.io/brain-map/DevATLAS/

Whole brain developmental map of neuronal circuit maturation. Generated by whole brain spatiotemporal mapping of circuit maturation during early postnatal development. Standard reference for normative developmental trajectory of neuronal circuit maturation, as well as high throughput platform to pinpoint when and where circuit maturation is disrupted in mouse models of neurodevelopmental disorders, such as fragile X syndrome.

Proper citation: DevATLAS (RRID:SCR_025718) Copy   

•   Source: SciCrunch Registry

https://github.com/Washington-University/HCPpipelines

Software package as set of tools, primarily shell scripts, for processing multi-modal, high-quality MRI images for the Human Connectome Project. Minimal preprocessing pipelines for structural, functional, and diffusion MRI that were developed by the HCP to accomplish many low level tasks, including spatial artifact/distortion removal, surface generation, cross-modal registration, and alignment to standard space.

Proper citation: HCP Pipelines (RRID:SCR_026575) Copy   

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https://github.com/kaizhang/SnapATAC2

Software Python/Rust package for single-cell epigenomics analysis.

Proper citation: SnapATAC2 (RRID:SCR_026622) Copy   

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https://github.com/ReproBrainChart

Open data resource for mapping brain development and its associations with mental health. Integrates data from 5 large studies of brain development in youth from three continents (N = 6,346). Bifactor models were used to create harmonized psychiatric phenotypes, capturing major dimensions of psychopathology. Neuroimaging data were carefully curated and processed using consistent pipelines in a reproducible manner.

Proper citation: Reproducible Brain Charts (RRID:SCR_027837) Copy   

•   Source: SciCrunch Registry

https://doi.org/10.17605/OSF.IO/WDR78

Open source resource of manually curated and expert reviewed infant brain segmentations hosted on OpenNeuro.org. and OSF.io. Anatomical MRI data was segmented from 71 infant imaging visits across 51 participants, using both T1w and T2w images per visit. Images showed dramatic differences in myelination and intensities across 1–9 months, emphasizing the need for densely sampled gold-standard segmentations across early life. This dataset provides a benchmark for evaluating and improving pipelines dependent upon segmentations in the youngest populations. As such, this dataset provides a vitally needed foundation for early-life large-scale studies such as HBCD.

Proper citation: Baby Open Brains (RRID:SCR_027836) Copy   

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https://github.com/noahbenson/neuropythy

Software neuroscience library for Python, intended to complement the existing nibabel library. Can automatic download data and interpret them into Python data structures.

Proper citation: neuropythy (RRID:SCR_027787) Copy   

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https://weghornlab.org/software.html

Software tool which derives gene-specific probabilistic estimates of the strength of negative and positive selection in cancer.

Proper citation: CBaSE (RRID:SCR_027765) Copy   

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http://nunda.northwestern.edu/nunda/app

A resource for managing study data collected by the Northwestern University neuroimaging community. It includes a secure database, automated pipelines for processing managed data, and tools for exploring and accessing the data. Access to data in the NUNDA is restricted to users authorized by the specific study's investigators. The NUNDA is hosted by the Neuroimaging & Applied Computational Anatomy Lab, and it is modeled after the Washington University's Central Neuroimaging Data Archive (CNDA). The NUNDA is powered by XNAT, an open source software package for managing neuroimaging and related data.

Proper citation: NUNDA (RRID:SCR_013664) Copy   

•   Source: SciCrunch Registry

http://tela.biostr.washington.edu/cgi-bin/repos/bmap_repo/main-menu.pl

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. An experiment management system for researchers studying language organization in the brain. Data from thirteen patients are available as a public demo. Language Map EMS

Proper citation: Language Map Experiment Management System (RRID:SCR_004562) Copy   

•   Source: SciCrunch Registry

http://www.scandb.org/newinterface/about.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17, 2022. A large-scale database of genetics and genomics data associated to a web-interface and a set of methods and algorithms that can be used for mining the data in it. The database contains two categories of single nucleotide polymorphism (SNP) annotations: # Physical-based annotation where SNPs are categorized according to their position relative to genes (intronic, inter-genic, etc.) and according to linkage disequilibrium (LD) patterns (an inter-genic SNP can be annotated to a gene if it is in LD with variation in the gene). # Functional annotation where SNPs are classified according to their effects on expression levels, i.e. whether they are expression quantitative trait loci (eQTLs) for that gene. SCAN can be utilized in several ways including: (i) queries of the SNP and gene databases; (ii) analysis using the attached tools and algorithms; (iii) downloading files with SNP annotation for various GWA platforms. . eQTL files and reported GWAS from NHGRI may be downloaded., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SCAN (RRID:SCR_005185) Copy   

•   Source: SciCrunch Registry

http://www.nimh.nih.gov/news/media/index.shtml

A provider for videos available from the National Institute of Mental Health (NIMH). Visitors may sort by topic and/or subscribe to RSS feeds.

Proper citation: NIMH Video (RRID:SCR_005594) Copy   

•   Source: SciCrunch Registry

http://www.neuroepigenomics.org/methylomedb/

A database containing genome-wide brain DNA methylation profiles for human and mouse brains. The DNA methylation profiles were generated by Methylation Mapping Analysis by Paired-end Sequencing (Methyl-MAPS) method and analyzed by Methyl-Analyzer software package. The methylation profiles cover over 80% CpG dinucleotides in human and mouse brains in single-CpG resolution. The integrated genome browser (modified from UCSC Genome Browser allows users to browse DNA methylation profiles in specific genomic loci, to search specific methylation patterns, and to compare methylation patterns between individual samples. Two species were included in the Brain Methylome Database: human and mouse. Human postmortem brain samples were obtained from three distinct cortical regions, i.e., dorsal lateral prefrontal cortex (dlPFC), ventral prefrontal cortex (vPFC), and auditory cortex (AC). Human samples were selected from our postmortem brain collection with extensive neuropathological and psychopathological data, as well as brain toxicology reports. The Department of Psychiatry of Columbia University and the New York State Psychiatric Institute have assembled this brain collection, where a validated psychological autopsy method is used to generate Axis I and II DSM IV diagnoses and data are obtained on developmental history, history of psychiatric illness and treatment, and family history for each subject. The mouse sample (strain 129S6/SvEv) DNA was collected from the entire left cerebral hemisphere. The three human brain regions were selected because they have been implicated in the neuropathology of depression and schizophrenia. Within each cortical region, both disease and non-psychiatric samples have been profiled (matching subjects by age and sex in each group). Such careful matching of subjects allows one to perform a wide range of queries with the ability to characterize methylation features in non-psychiatric controls, as well as detect differentially methylated domains or features between disease and non-psychiatric samples. A total of 14 non-psychiatric, 9 schizophrenic, and 6 depression methylation profiles are included in the database.

Proper citation: MethylomeDB (RRID:SCR_005583) Copy   

•   Source: SciCrunch Registry

http://www.cpc.unc.edu/projects/addhealth

Longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States during the 1994-95 school year. Public data on about 21,000 people first surveyed in 1994 are available on the first phases of the study, as well as study design specifications. It also includes some parent and biomarker data. The Add Health cohort has been followed into young adulthood with four in-home interviews, the most recent in 2008, when the sample was aged 24-32. Add Health combines longitudinal survey data on respondents social, economic, psychological and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships, providing unique opportunities to study how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. The fourth wave of interviews expanded the collection of biological data in Add Health to understand the social, behavioral, and biological linkages in health trajectories as the Add Health cohort ages through adulthood. The restricted-use contract includes four hours of free consultation with appropriate staff; after that, there''s a fee for help. Researchers can also share information through a listserv devoted to the database.

Proper citation: Add Health (National Longitudinal Study of Adolescent Health) (RRID:SCR_007434) Copy   

•   Source: SciCrunch Registry