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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://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://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

https://www.stanleygenomics.org/

The Stanley Online Genomics Database uses samples from the Stanley Medical Research Institute (SMRI) Brain Bank. These samples were processed and run on gene expression arrays by a variety of researchers in collaboration with the SMRI. These researchers have performed analyses on their respective studies using a range of analytic approaches. All of the genomic data have been aggregated in this online database, and a consistent set of analyses have been applied to each study. Additionally, a comprehensive set of cross-study analyses have been performed. A thorough collection of gene expression summaries are provided, inclusive of patient demographics, disease subclasses, regulated biological pathways, and functional classifications. Raw data is also available to download. The database is derived from two sets of brain samples, the Stanley Array collection and the Stanley Consortium collection. The Stanley Array collection contains 105 patients, and the Stanley Consortium collection contains 60 patients. Multiple genomic studies have been conducted using these brain samples. From these studies, twelve were selected for inclusion in the database on the basis of number of patients studied, genomic platform used, and data quality. The Consortium collection studies have fewer patients but more diversity in brain regions and array platforms, while the Array collection studies are more homogenous. There are tradeoffs, the Consortium results will be more variable, but findings may be more broadly representative. The collections contain brain samples from subjects in four main groups: Bipolar Schizophrenia, Depression, and Controls Brain regions used in the studies include: Broadman Area 6, Broadman Area 8/9, Broadman Area 10, Broadman Area 46, Cerebellum The 12 studies encompass a range of microarray platforms: Affymetrix HG-U95Av2, Affymetrix HG-U133A, Affymetrix HG-U133 2.0+, Codelink Human 20K, Agilent Human I, Custom cDNA Publications based on any of the clinical or genomic data should credit the Stanley Medical Research Institute, as well as any individual SMRI collaborators whose data is being used. Publications which make use of analytic results/methods in the database should additionally cite Dr. Michael Elashoff. Registration is required to access the data.

Proper citation: Stanley Medical Research Institute Online Genomics Database (RRID:SCR_004859) Copy   

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http://www.psychologytoday.com/blog/the-compass-pleasure

A blog written by David J. Linden, Ph.D., professor of Neuroscience at the Johns Hopkins University School of Medicine, focusing on the brain''s pleasure circuits. Topics covered include exercise, pleasure and the brain; and understanding the biology of runners high. The Compass of Pleasure: How Our Brains Make Fatty Foods, Orgasm, Exercise, Marijuana, Generosity, Vodka, Learning, and Gambling Feel So Good is also a book and available for purchase. David J. Linden, Ph.D., is a professor in the Department of Neuroscience at the Johns Hopkins University School of Medicine. His laboratory has worked for many years on the cellular substrates of memory storage in the brain and a few other topics. He has a longstanding interest in scientific communication and serves as the Chief Editor of the Journal of Neurophysiology. He has written two books for a general audience about the biological basis of mental function: The Compass of Pleasure (Viking Press, 2011) and The Accidental Mind (Harvard/Belknap, 2007).

Proper citation: Compass of Pleasure (RRID:SCR_004756) Copy   

•   Source: SciCrunch Registry

http://mindblog.dericbownds.net/

Deric Bownds'' Mindblog reports new ideas and work on mind, brain, and behavior - as well as random curious stuff. Deric Bownds, retired Univ. Wisc. Professor, studies brain and mind. My laboratory research of ~35 years contributed to our understanding of how vision works. This work was gradually phased out in the 1990''s as I devoted increasing time to studying the evolution, development, and function of humans brains.

Proper citation: Deric Bownds Mindblog (RRID:SCR_005492) Copy   

•   Source: SciCrunch Registry

http://wiringthebrain.blogspot.com/

This blog highlights and comments on current research and hypotheses relating to how the brain wires itself up during development, how the end result can vary in different people and what happens when it goes wrong. It includes discussions of the genetic and neurodevelopmental bases of traits such as intelligence and personality characteristics, as well as of conditions such as schizophrenia, autism, dyslexia, epilepsy, synaesthesia and others.

Proper citation: Wiring the Brain (RRID:SCR_005528) 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://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

http://neurobureau.projects.nitrc.org/ADHD200/Introduction.html

Preprocessed versions of the ADHD-200 Global Competition data including both preprocessed versions of structural and functional datasets previously made available by the ADHD-200 consortium, as well as initial standard subject-level analyses. The ADHD-200 Sample is pleased to announce the unrestricted public release of 776 resting-state fMRI and anatomical datasets aggregated across 8 independent imaging sites, 491 of which were obtained from typically developing individuals and 285 in children and adolescents with ADHD (ages: 7-21 years old). Accompanying phenotypic information includes: diagnostic status, dimensional ADHD symptom measures, age, sex, intelligence quotient (IQ) and lifetime medication status. Preliminary quality control assessments (usable vs. questionable) based upon visual timeseries inspection are included for all resting state fMRI scans. In accordance with HIPAA guidelines and 1000 Functional Connectomes Project protocols, all datasets are anonymous, with no protected health information included. They hope this release will open collaborative possibilities and contributions from researchers not traditionally addressing brain data so for those whose specialties lay outside of MRI and fMRI data processing, the competition is now one step easier to join. The preprocessed data is being made freely available through efforts of The Neuro Bureau as well as the ADHD-200 consortium. They ask that you acknowledge both of these organizations in any publications (conference, journal, etc.) that make use of this data. None of the preprocessing would be possible without the freely available imaging analysis packages, so please also acknowledge the relevant packages and resources as well as any other specific release related acknowledgements. You must be logged into NITRC to download the ADHD-200 datasets, http://www.nitrc.org/projects/neurobureau

Proper citation: ADHD-200 Preprocessed Data (RRID:SCR_000576) Copy   

•   Source: SciCrunch Registry

https://scicrunch.org/resources/Tools/record/nlx_144509-1/6b508d2a-fd5f-56f2-93cf-462fcd52548e/search?q=*&l=&facet%5B%5D=Parent%20Organization:University%20of%20Michigan;%20Michigan;%20USA&sort=added

THIS RESOURCE IS NO LONGER IN SERVICE. Documented September 12, 2017.

Dataset in Bilingual exposure optimizes left-hemisphere dominance for selective attention processes in the developing brain by Arredondo, Su, Satterfield, & Kovelman (XX) Does early bilingual exposure alter the representations of cognitive processes in the developing brain? Theories of bilingual development have suggested that bilingual language switching might improve children''s executive function and foster the maturation of prefrontal brain regions that support higher cognition. To test this hypothesis, we used functional Near Infrared Spectroscopy to measure brain activity in Spanish-English bilingual and English-monolingual children during a visuo-spatial executive function task of attentional control (N=27, ages 7-13). Prior findings suggest that while young children start with bilateral activation for the task, it becomes right-lateralized with age (Konrad et al., 2005). Indeed monolinguals showed bilateral frontal activation, however young bilinguals showed greater activation in left language areas relative to right hemisphere and relative to monolinguals. The findings suggest that bilingual experience optimizes attention mechanisms in the language hemisphere, and highlight the importance of early experiences for neurodevelopmental plasticity of higher cognition. These data are made available from Ioulia Kovelman''s Language and Literacy Lab at University of Michigan and may be exported through the NIF Data Federation. To cite these data please use this text Data were published by Arredondo et al. (XX) and made available via the NIF at XX

Proper citation: Arredondo ANT fNIRS dataset1 (RRID:SCR_002653) Copy   

•   Source: SciCrunch Registry

http://www.internationalbrainbee.com

A world-wide neuroscience competition for high school students that aims to motivate them to learn about the brain and to pursue neuroscience careers. Brain Bee tests knowledge of the human brain, including topics like intelligence, emotions, memory, sleep, vision, hearing, sensations, Alzheimer's disease, Parkinson's disease, stroke, schizophrenia, epilepsy, depression, addictions and brain research.

Proper citation: Brain Bee (RRID:SCR_002248) Copy   

•   Source: SciCrunch Registry

http://fcon_1000.projects.nitrc.org/indi/retro/BeijingEOEC.html

Data set of 48 healthy controls from a community (student) sample from Beijing Normal University in China with 3 resting state fMRI scans each. During the first scan participants were instructed to rest with their eyes closed. The second and third resting state scan were randomized between resting with eyes open versus eyes closed. In addition this dataset contains a 64-direction DTI scan for every participant. The following data are released for every participant: * 6-minute resting state fMRI scan (R-fMRI) * MPRAGE anatomical scan, defaced to protect patient confidentiality * 64-direction diffusion tensor imaging scan (2mm isotropic) * Demographic information and information on the counterbalancing of eyes open versus eyes closed.

Proper citation: Beijing: Eyes Open Eyes Closed Study (RRID:SCR_001507) Copy   

•   Source: SciCrunch Registry