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

Atlas for studies of older adult brain. Includes T1-weighted template of older adult brain and tissue probability maps. Exhibits high image sharpness, provides higher inter-subject spatial normalization accuracy compared to other standardized templates and similar normalization accuracy to well-constructed study-specific templates.

Proper citation: MIITRA atlas (RRID:SCR_017566) Copy   

•   Source: SciCrunch Registry

http://practicalfmri.blogspot.com/

A blog about functional MRI from a lab at UC Berkeley.

Proper citation: practiCal fMRI: the nuts and bolts (RRID:SCR_005429) Copy   

•   Source: SciCrunch Registry

http://www.brainimmune.com/

BrainImmune is a free web-based reference that provides comprehensive and up-to-date information on the broad spectrum of medical research related to brain-immune interactions and their impact on health and disease. BrainImmune is written collaboratively by experts in the field from all around the world. Here, concise summaries of basic and clinical research describe how the brain and the immune system ''talk'' to each other in order to maintain homeostasis. BrainImmune is continually updated, with articles and opinions on history, the present state of the art, and new ideas and conceptual frameworks for the neurohormonal- and stress-immune interactions and their implications for common human diseases. Our goal in developing BrainImmune is to facilitate and advance neuroendocrine-immunology research, and the communication and collaborations in this vast interdisciplinary area.

Proper citation: BrainImmune (RRID:SCR_005418) Copy   

•   Source: SciCrunch Registry

http://www.youtube.com/user/BCIZaragoza

Videos uploaded to YouTube by the Brain-Computer Interfaces (BCI) research team, University of Zaragoza.

Proper citation: BCIZaragoza - YouTube (RRID:SCR_005445) Copy   

•   Source: SciCrunch Registry

http://centreforstrokerecovery.ca/our-research/research-structure/stroke-patient-recovery-research-database-spred

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 28,2025. The Stroke Patient Recovery Research Database (SPReD) initiative creates the infrastructure needed for the collection of a wide range of data related to stroke risk factors and to stroke recovery. It also promotes the analysis and management of large brain and vessel images. A major goal is to create a comprehensive electronic database Stroke Patient Recovery Research Database or SPReD and populate it with patient data, including demographic, biomarker, genetic and proteomic data and imaging data. SPReD will enable us to combine descriptions of our stroke patients from multiple projects that are geographically distributed. We will do this in a uniform fashion in order to enhance our ability to document rates of recovery; to study the effects of vascular risk factors and inflammatory biomarkers; and to use these data to improve their physical and cognitive recovery through innovative intervention programs. This comprehensive database will provide an integrated repository of data with which our researchers will investigate and test original ideas, ultimately leading to knowledge that can be applied clinically to benefit stroke survivors.

Proper citation: Stroke Patient Recovery Research Database (SPReD) (RRID:SCR_005508) Copy   

•   Source: SciCrunch Registry

http://www.youtube.com/user/BrainBlogger

BrainBlogger - YouTube are videos uploaded to YouTube by Brain Blogger. Brain Blogger covers topics from multidimensional biopsychosocial perspectives. It reviews the latest news and stories related to neuroscience, psychiatry, and neurology. It serves as a focal point for attracting new minds beyond the science of the mind-and-brain and into the biopsychosocial model.

Proper citation: BrainBlogger - YouTube (RRID:SCR_005469) Copy   

•   Source: SciCrunch Registry

http://neuropsychological.blogspot.com/index.html

BrainBlog is news about our knowledge of the brain and behavior from Anthony Risser, Ph.D. Anthony Risser, Ph.D. is a consulting neuropsychologist. My interests include online and distributed applications in medicine, clinical trials, professional training, and undergraduate/graduate education.

Proper citation: BrainBlog (RRID:SCR_005581) 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

https://sites.google.com/site/depressiondatabase/

The Major Depressive Disorder Neuroimaging Database (MaND) contains information of 225 studies which have investigated brain structure (using MRI and CT scans) in patients with major depressive disorder compared to a control group. 143 studies and 63 brain structures are included in the meta-analysis. The database and meta-analysis are contained in an Excel spreadsheet file which may be freely downloaded from this website.

Proper citation: Major depressive disorder neuroimaging database (RRID:SCR_005835) Copy   

•   Source: SciCrunch Registry

http://www.guardian.co.uk/science/neurophilosophy

Blog about molecules, minds and everything in between, written by Mo, a molecular and developmental neurobiologist turned science writer. He aims to produce well-written and easily accessible articles about all aspects of neuroscience, so that he might help to improve public understanding of it. This blog has been featured for two consecutive years in the Open Lab annual anthologies of the best science blogging. AFTER four years at ScienceBlogs.com, Neurophilosophy has moved to a new home. It is now hosted by The Guardian.

Proper citation: Neurophilosophy (RRID:SCR_006514) Copy   

•   Source: SciCrunch Registry

https://github.com/openconnectome/Rambo3D

A web and GPU enabled stand-alone app for viewing volumes at arbitrary cutting planes and zoom levels.

Proper citation: Rambo3D (RRID:SCR_006357) Copy   

•   Source: SciCrunch Registry

http://pepr.cnmcresearch.org/

An experiment in web-database access to large multi-dimensional data sets using a standardized experimental platform to determine if the larger scientific community can be given simple, intuitive, and user-friendly web-based access to large microarray data sets. All data in PEPR is also available via NCBI GEO. The structure and goals of PEPR differ from other mRNA expression profiling databases in a number of important ways. * The experimental platform in PEPR is standardized, and is an Affymetrix - only database. All microarrays available in the PEPR web database should ascribe to quality control and standard operating procedures. A recent publication has described the QC/SOP criteria utilized in PEPR profiles ( The Tumor Analysis Best Practices Working Group 2004 ). * PEPR permits gene-based queries of large Affymetrix array data sets without any specialized software. For example, a number of large time series projects are available within PEPR, containing 40-60 microarrays, yet these can be simply queried via a dynamic web interface with no prior knowledge of microarray data analysis. * Projects in PEPR originate from scientists world-wide, but all data has been generated by the Research Center for Genetic Medicine, Children''''s National Medical Center, Washington DC. Future developments of PEPR will allow remote entry of Affymetrix data ascribing to the same QC/SOP protocols. They have previously described an initial implementation of PEPR, and a dynamic web-queried time series graphical interface ( Chen et al. 2004 ). A publication showing the utility of PEPR for pharmacodynamic data has recently been published ( Almon et al. 2003 ).

Proper citation: Public Expression Profiling Resource (RRID:SCR_007274) 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://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://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://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