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http://www.nitrc.org/projects/brainlife_io/

Platform for publishing reproducible code and datasets and providing access to national supercomputers, private clouds, and institutional high-performance computer systems to promote open software and data sharing to advance understanding of the human brain.

Proper citation: brainlife.io (RRID:SCR_016513) Copy   

•   Source: SciCrunch Registry

https://www.med.upenn.edu/sbia/brats2017.html

Organization that provides a conference about the methods for the segmentation of brain tumors in magnetic resonance imaging (MRI) scans. Its conferences utilize multi-institutional pre-operative MRI scans and focus on the segmentation of intrinsically heterogeneous (in appearance, shape, and histology) brain tumors, namely gliomas.

Proper citation: BraTS (RRID:SCR_016214) Copy   

•   Source: SciCrunch Registry

https://cic.ini.usc.edu/

Project to create complete mesoscale connectivity atlas of the C57Black/6 mouse brain and to subsequently generate its global neural networks.

Proper citation: Mouse Connectome Project (RRID:SCR_017313) Copy   

•   Source: SciCrunch Registry

https://www.drugabuse.gov

Portal provides list of genetic resources such as Brain Atlases and genomes for various species provided by National Institute of Drug Abuse.

Proper citation: Compilation of Genetics Resource Databases (RRID:SCR_017501) Copy   

•   Source: SciCrunch Registry

https://github.com/nipy/heudiconv

Software tool as flexible DICOM converter for organizing brain imaging data into structured directory layouts.

Proper citation: HeuDiConv: a heuristic-centric DICOM converter (RRID:SCR_017427) Copy   

•   Source: SciCrunch Registry

http://www.morf-brain.com/

Portal devoted to suite of MORF reporter mice labels of Cre positive neurons and glia distributed stochastically throughout brain and can be imaged with endogenous fluorescence (mNeonGreen in MORF1 and EGFP in TIGRE-MORF) or stained for multivalent immunoreporter (Spaghetti Monster fluorescent protein V5, or smFP-V5, in MORF3). MORF technology used to label and reconstruct thousands genetically defined cells per brain for large scale, unbiased classification and quantitative analyses of CNS cell types brainwide.

Proper citation: Mononucleotide Repeat Frameshift Portal (RRID:SCR_021125) Copy   

•   Source: SciCrunch Registry

http://www.neuromorphometrics.com/2012_MICCAI_Challenge_Data.html

Manually created neuroanatomically labeled MRI brain scans with unique subjects, 5 subjects scanned twice.

Proper citation: 2012 MICCAI Multi-Atlas Labeling Challenge Data (RRID:SCR_017008) Copy   

•   Source: SciCrunch Registry

http://www.uimcimes.es/contenidos/golink?p=1

Software toolbox for Statistical Parametric Mapping (SPM) to fit reference-region kinetic models (SRTM, SRTM2, Patlak Reference and Logan Reference Plot) are currently available in QModeling to dynamic PET studies. Used for the analysis of brain imaging data sequences.

Proper citation: QModeling (RRID:SCR_016358) Copy   

•   Source: SciCrunch Registry

http://caprica.genetics.kcl.ac.uk/BRAINEAC/

Database for the UK Brain Expression Consortium (UKBEC) dataset that comprises of brains from individuals free of neurodegenerative disorders. The aim of Braineac is to release to the scientific community a valid instrument to investigate the genes and SNPs associated with neurological disorders.

Proper citation: Braineac (RRID:SCR_015888) Copy   

•   Source: SciCrunch Registry

http://brainarchitecture.org/allen-atlas-brain-toolbox

Software Matlab toolbox for quantitative analysis of digitized brain wide gene expression data from Allen Atlas of adult mouse brain.

Proper citation: Brain Gene Expression Analysis toolbox (RRID:SCR_017438) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/clsm/

Software package that performs several multivariate and mass univariate lesion symptom mapping analyses. Uses patient imaging lesion masks of brain insults and correlates them in multiple ways with patient behavioral and covariate data. Several permutation based SPMs are computed along with power, variance explained, and lesion coverage maps.

Proper citation: CLIMB Lesion Symptom Mapping Software (RRID:SCR_018298) Copy   

•   Source: SciCrunch Registry

http://spot.colorado.edu/~dubin/talks/agnosia.html

Compilation terms with definitions that describe altered states that are associated with brain injury (e.g., trauma, stroke, tumor) or with developmental deficits. Although the list deals with primarily CNS-associated disorders, in some cases the term does not distinguish between a CNS cause or a peripheral or neuromuscular cause. Terms that are primarily psychiatric diagnoses (e.g., schizophrenia) are not included. AGNOSIA is a general term for a loss of ability to recognize objects, people, sounds, shapes, or smells; that is, the inability to attach appropriate meaning to objective sense-data. It usually is used when the primary sense organ involved is not impaired. APHASIA is a general term relating to a loss of language ability. APRAXIA is a general term for disorders of practice. These conditions are usually caused by brain injury due to trauma, stroke and/or tumor. Many of these terms have two synonymous forms that differ in whether the word starts with a- or with dys- such as alexia and dyslexia. Here the a- form is usually defined and the other is noted as syn:, except when the dys- form is the more common usage. (If you cannot find a term in one of these forms, look for it in the other. All other synonyms are defined in both forms.) Sources: These definitions are paraphrased from definitions in a large number or print and online dictionaries. Thus this list is not meant to be considered my own, but rather is a compilation. Note: When a word appears in italics, that indicates it is defined elsewhere in this list.

Proper citation: AGNOSIA APHASIA APRAXIA and Related Terms for Cognitive Behavioral and Neurological Disorders (RRID:SCR_005336) Copy   

•   Source: SciCrunch Registry

http://www.rad.upenn.edu/sbia/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on June 2, 2023. A section of the Penn department of radiology, it is devoted to the development of computer-based image analysis methods and their application to clinical research studies. Image analysis methodologies include image registration, segmentation, population-based statistical analysis, biophysical modeling of anatomical deformations, and high-dimensional pattern classification. Clinical research studies spans a variety of clinical areas and organs, and they include brain diseases such as Alzheimer's disease and schizophrenia, evaluation of treatment effects in large clinical trials, diagnosis of cardiac diseases, and diagnosis prostate, breast and brain cancer. SBIA also performs small animal imaging research aiming to understand brain development in mouse models. It has multiple resources which can be accessed by researcher.

Proper citation: SBIA (RRID:SCR_013628) Copy   

•   Source: SciCrunch Registry

http://brancusi.usc.edu/bkms/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 7th, 2019. BAMS is an online resource for information about neural circuitry. The BAMS Nested Regions view focuses on the major brain regions and their relationships.

Proper citation: BAMS Nested Regions (RRID:SCR_000238) Copy   

•   Source: SciCrunch Registry

http://brainevolutionnews.blogspot.com/

Brain Evolution in the News pulls in blogs from a variety of resources on topic.

Proper citation: Brain Evolution in the News (RRID:SCR_000592) Copy   

•   Source: SciCrunch Registry

http://www.eideneurolearningblog.blogspot.com/

Weekly articles related to brain-based learning and learning styles, problem-solving and creativity, kids, families, and parenting, gifted and visual learners, dyslexia, attention deficit disorders, autism, and more.

Proper citation: Eide Neurolearning Blog (RRID:SCR_000680) Copy   

•   Source: SciCrunch Registry

http://kymata-atlas.org

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. An online atlas of neural function, maintained by Cambridge University and the MRC Cognition and Brain Sciences Unit (CBSU).

Proper citation: Kymata Atlas (RRID:SCR_000269) Copy   

•   Source: SciCrunch Registry

http://gemma-doc.chibi.ubc.ca/neurocarta/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Neurocarta is a knowledgebase that consolidates information on genes and phenotypes across multiple resources and allows tracking and exploring of the associations. The system enables automatic and manual curation of evidence supporting each association, as well as user-enabled entry of their own annotations. Phenotypes are recorded using controlled vocabularies such as the Disease Ontology to facilitate computational inference and linking to external data sources. The gene-to-phenotype associations are filtered by stringent criteria to focus on the annotations most likely to be relevant. Neurocarta is constantly growing and currently holds more than 30,000 lines of evidence linking over 6,800 genes to 1,800 different phenotypes. Neurocarta is a one-stop shop for researchers looking for candidate genes for any disorder of interest. In Neurocarta, they can review the evidence linking genes to phenotypes and filter out the evidence they're not interested in. In addition, researchers can enter their own annotations from their experiments and analyze them in the context of existing public annotations. Neurocarta's in-depth annotation of neurodevelopmental disorders makes it a unique resource for neuroscientists working on brain development.

Proper citation: Neurocarta (RRID:SCR_000617) Copy   

•   Source: SciCrunch Registry

http://gbrowse.csbio.unc.edu/cgi-bin/gb2/gbrowse/slep/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Database of genetic and gene expression data from the published literature on psychiatric disorders. Users can search the accumulated data to find the evidence in support of the involvement of a particular genomic region with a set of important psychiatric disorders, ADHD, autism, bipolar disorder, eating disorder, major depressive disorder, schizophrenia, and smoking behavior. It contains findings from manual reviews of 144 papers in psychiatric genetics, 136 primary reports and 8 meta-analyses. Disorders covered include schizophrenia (44 papers), autism (24 papers), bipolar disorder (24 papers), smoking behavior (24 papers), major depressive disorder and neuroticism (14 papers), ADHD (8 papers), eating disorders (3 papers), and a combined schizophrenia-bipolar phenotype (3 papers). The unbiased searches integrated into SLEP include genomewide linkage (117 papers), genomewide association (15 papers), copy number variation (9 papers), and gene expression studies of post-mortem brain tissue (3 meta-analyses courtesy of the Stanley Foundation). In total, SLEP captures 3,741 findings from these 144 papers. SLEP also contains over 70,000 SignPosts. These annotations derive from many different sources and are designed to try to capture current state of knowledge about disease associations in the human genome. SignPosts can be searched simultaneously with the psychiatric genetics literature in order to integrate these two bodies of knowledge. The SignPosts include: accumulated GWAS findings from the human genetics literature, the OMIM database, candidate gene association study literature, CNV location and frequency data, SNPs that influence gene expression in brain, genes expressed in brain, genes with evidence of imprinting and random monoalleleic expression, genes mutated in breast or colorectal cancer, and pathway data from BioCyc.

Proper citation: Sullivan Lab Evidence Project (RRID:SCR_000753) Copy   

•   Source: SciCrunch Registry

http://projectreporter.nih.gov/project_info_description.cfm?aid=8662111&icde=19363315&ddparam=&ddvalue=&ddsub=&cr=2&csb=default&cs=ASC

A multi-center and multi-disciplinary study designed to dramatically increase understanding of chronic traumatic encephalopathy (CTE) and other late effects of traumatic brain injury (TBI). Overlapping clinical features, postmortem pathologies and patterns of involvement exist in TBI, CTE, and Alzheimer''s disease pose challenges to accurate diagnosis. Premortem diagnosis of CTE is currently impossible. The neuropathological consequences of single mild or moderate-severe TBI and its relationship with CTE and known dementias are unclear. The proposed project will leverage extensive resources from an ongoing population-based prospective cohort study of brain aging (Adult Changes in Thought; ACT, n=2,305) which includes excellent medical, behavioral, and genetic characterization of a cohort (20% of whom have a history of mild-moderate TBI) in addition to state-of-the-art neuropathology workup upon death. Neuropathological study of TBI effects can begin immediately in the existing ACT autopsy sample (n=489, 20% with TBI exposure). Additional cohorts of TBI- exposed individuals will come from the Brain Injury Research Center at Mount Sinai (n=150 individuals with moderate-severe TBI), the University of Texas Southwestern (n=50 retired boxers with repetitive TBI exposure), and the National Football League (n=76 retired players with repetitive TBI exposure). All participants in the proposed study (ACT and other sites) will undergo uniform harmonized neurobehavioral assessment (chosen to maximize correspondence with existing large-scale TBI and dementia studies), MRI scan, and genomic analysis. Those individuals who expire during the course of the study will undergo ex-vivo neuroimaging and extensive neuropathological exam using state-of-the-art techniques (such as Histelide) designed to quantify tau and A�� in whole brain specimens. Only by examining postmortem pathology in a sample of individuals with varying levels of TBI exposure who are well characterized during life (as proposed herein) can postmortem pathology facilitate identification of in-vivo biomarkers that can act as diagnostic tools. This project represents the most systematic and scientifically rigorous effort to date to develop a more complete understanding of the long-term clinical and neuropathological sequelae of single and multiple TBI.

Proper citation: Neuropathology of CTE and Delayed Effects of TBI: Toward In-Vivo Diagnostics (RRID:SCR_012951) Copy   

•   Source: SciCrunch Registry