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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://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://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.chimpanzeebrain.org/

Collection and distribution of chimpanzee neuroimaging data and postmortem brain tissue. Portal to access chimpanzee brain atlas tools, data repository, bibliography of publications, educational information, and links to other chimpanzee brain resources and datasets on the Internet. Serves as repository for in vivo structural MRI scans of chimpanzee brains, in vivo and postmortem diffusion tensor images (DTI), as well as postmortem fixed and frozen brain specimens.

Proper citation: National Chimpanzee Brain Resource (RRID:SCR_019183) 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://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://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://bodymap.genes.nig.ac.jp/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. A taxonomical and anatomical database of latest cross species animal EST data, clustered by UniGene and inter connected by Inparanoid. Users can search by Unigene, RefSeq, or Entrez Gene ID, or search for Gene Name or Tissue type. Data is also sortable and viewable based on qualities of normal, Neoplastic, or other. The last data import appears to be from 2008

Proper citation: BodyMap-Xs (RRID:SCR_001147) Copy   

•   Source: SciCrunch Registry

http://netbio.bgu.ac.il/tissuenet/

Database of human tissue protein-protein interactions (PPIs) that associates each interaction with human tissues that express both pair mates. This was achieved by integrating current data of experimentally detected PPIs with extensive data of gene and protein expression across 16 main human tissues. Users can query TissueNet using a protein and retrieve its PPI partners per tissue, or using a PPI and retrieve the tissues expressing both pair mates. The graphical representation of the output highlights tissue-specific and tissue-wide PPIs. Thus, TissueNet provides a unique platform for assessing the roles of human proteins and their interactions across tissues.

Proper citation: TissueNet - The Database of Human Tissue Protein-Protein Interactions (RRID:SCR_002052) Copy   

•   Source: SciCrunch Registry

http://www.neuroanatomy.wisc.edu/

Training materials including Web edition modules of the neuroanatomy coursebooks used by first-year medical students at the University of Wisconsin Medical School (UWMS), videos, and images. Topics include spinal cord, brain stem, Cerebellum, Thalamus, Cranial Nerves and National Board Review practice questions.

Proper citation: UW-Madison Neuroscience Resources (RRID:SCR_001649) Copy   

•   Source: SciCrunch Registry

http://www.med.unc.edu/bric/ideagroup/free-softwares/abeat-a-toolbox-for-consistent-analysis-of-longitudinal-adult-brain-mri

A 4D adult brain extraction and analysis toolbox with graphical user interfaces to consistently analyze 4D adult brain MR images. Single-time-point images can also be analyzed. Main functions of the software include image preprocessing, 4D brain extraction, 4D tissue segmentation, 4D brain labeling, ROI analysis. Linux operating system (64 bit) is required. A computer with 8G memory (or more) is recommended for processing many images simultaneously. The graphical user interfaces and overall framework of the software are implemented in MATLAB. The image processing functions are implemented with the combination of C/C++, MATLAB, Perl and Shell languages. Parallelization technologies are used in the software to speed up image processing.

Proper citation: aBEAT (RRID:SCR_002238) Copy   

•   Source: SciCrunch Registry

http://www.utdallas.edu/bbs/

Mission of the School of Behavioral and Brain Sciences is to understand the intersection of mind, brain and behavior; enhance the health, education, and quality of life of children and families; and create and implement technologies and therapies that repair and strengthen human abilities. The School is housed in Green Hall on the main UT Dallas campus in Richardson. It also has satellite research centers and facilities in downtown Dallas.

Proper citation: University of Texas at Dallas School of Behavioral and Brain Sciences (RRID:SCR_004645) Copy   

•   Source: SciCrunch Registry

https://www.bminds.brain.riken.jp/

Web-accessible digital brain atlas of the common marmoset (Callithrix jacchus), prepared from histological sections of the marmoset brain using various staining techniques.

Proper citation: Digital Brain Atlas of the Common Marmoset (RRID:SCR_005069) Copy   

•   Source: SciCrunch Registry

http://connectir.projects.nitrc.org

An R-based package to conduct brain connectivity analyses with a focus on a novel approach to conducting Connectome-Wide Association Studies (CWAS) using functional connectivity.

Proper citation: Connectir (RRID:SCR_000863) Copy   

•   Source: SciCrunch Registry

http://www.tbi-impact.org/

Project focused on advancing knowledge of prognosis, trial design and treatment in Traumatic Brain Injury. IMPACT has developed and validated prognostic models for classification and characterization of TBI series, and participated in development of standardization of data collection in TBI studies.

Proper citation: IMPACT: International Mission for Prognosis and Analysis of Clinical Trials in TBI (RRID:SCR_000539) Copy   

•   Source: SciCrunch Registry

http://www.semel.ucla.edu/creativity/

The purpose of this center is to study the molecular, cellular, systems and cognitive mechanisms that result in cognitive enhancements and explain unusual levels of performance in gifted individuals, including extraordinary creativity. Additionally, by understating the mechanisms responsible for enhancements in performance we may be better suited to intervene and reverse disease states that result in cognitive deficits. One of the key topics addressed by the Center is the biological basis of cognitive enhancements, a topic that can be studied in human subjects and animal models. In the past much of the focus in the brain sciences has been on the study of brain mechanisms that degrade cognitive performance (for example, on mutations or other lesions that cause cognitive deficits). The Tennenbaum Center for the Biology of Creativity at UCLA enables an interdisciplinary team of leading scientists to advance knowledge about the biological bases of creativity. Starting with a pilot project program, a series of investigations was launched, spanning disciplines from basic molecular biology to cognitive neuroscience. Because the concept of creativity is multifaceted, initial efforts targeted refinement of the component processes necessary to generate novel, useful cognitive products. The identified core cognitive processes: 1.) Novelty Generation the ability to flexibly and adaptively generate products that are unique; 2.) Working Memory and Declarative Memory the ability to maintain, and then use relevant information to guide goal-directed performance, along with the capacity to store and retrieve this information; and 3.) Response Inhibition the ability to suppress habitual plans and substitute alternate actions in line with changing problem-solving demands. To study the basic mechanisms underlying these complex brain functions we use translational strategies. Starting from foundational studies in basic neuroscience, we forged an interdisciplinary strategy that permits the most advanced techniques for genetic manipulation and basic neurobiological research to be applied in close collaboration with human studies that converge on the same core cognitive processes. Our integrated research program aims to reveal the genetic architecture and fundamental brain mechanisms underlying creative cognition. The work holds enormous promise for both enhancing healthy cognitive performance and designing new treatments for diverse cognitive disorders. Sponsors: The Tennenbaum Center for the Biology of Creativity was inspired by the vision and generosity of Michael Tennenbaum.

Proper citation: Tennenbaum Center for the Biology of Creativity (RRID:SCR_000668) Copy   

•   Source: SciCrunch Registry

http://ccb.loni.usc.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 31, 2022. Center focused on the development of computational biological atlases of different populations, subjects, modalities, and spatio-temporal scales with 3 types of resources: (1) Stand-alone computational software tools (image and volume processing, analysis, visualization, graphical workflow environments). (2) Infrastructure Resources (Databases, computational Grid, services). (3) Web-services (web-accessible resources for processing, validation and exploration of multimodal/multichannel data including clinical data, imaging data, genetics data and phenotypic data). The CCB develops novel mathematical, computational, and engineering approaches to map biological form and function in health and disease. CCB computational tools integrate neuroimaging, genetic, clinical, and other relevant data to enable the detailed exploration of distinct spatial and temporal biological characteristics. Generalizable mathematical approaches are developed and deployed using Grid computing to create practical biological atlases that describe spatiotemporal change in biological systems. The efforts of CCB make possible discovery-oriented science and the accumulation of new biological knowledge. The Center has been divided into cores organized as follows: - Core 1 is focused on mathematical and computational research. Core 2 is involved in the development of tools to be used by Core 3. Core 3 is composed of the driving biological projects; Mapping Genomic Function, Mapping Biological Structure, and Mapping Brain Phenotype. - Cores 4 - 7 provide the infrastructure for joint structure within the Center as well as the development of new approaches and procedures to augment the research and development of Cores 1-3. These cores are: (4)Infrastructure and Resources, (5) Education and Training, (6) Dissemination, and (7) Administration and Management. The main focus of the CCB is on the brain, and specifically on neuroimaging. This area has a long tradition of sophisticated mathematical and computational techniques. Nevertheless, new developments in related areas of mathematics and computational science have emerged in recent years, some from related application areas such as Computer Graphics, Computer Vision, and Image Processing, as well as from Computational Mathematics and the Computational Sciences. We are confident that many of these ideas can be applied beneficially to neuroimaging.

Proper citation: Center for Computational Biology at UCLA (RRID:SCR_000334) Copy   

•   Source: SciCrunch Registry