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On page 12 showing 221 ~ 240 out of 291 results
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  • RRID:SCR_002244

    This resource has 100+ mentions.

http://www.nimh.nih.gov/research-priorities/rdoc/index.shtml

NIMH Strategic Plan developing, for research purposes, new ways of classifying psychopathology based on dimensions of observable behavior and neurobiological measures. In brief, the effort is to define basic dimensions of functioning (such as fear circuitry or working memory) to be studied across multiple units of analysis, from genes to neural circuits to behaviors, cutting across disorders as traditionally defined. The intent is to translate rapid progress in basic neurobiological and behavioral research to an improved integrative understanding of psychopathology and the development of new and/or optimally matched treatments for mental disorders. The various domains of functioning, and their constituent elements, are being defined by an ongoing series of consensus workshops; input from the research community and other interested stakeholders is encouraged.

Proper citation: RDoC (RRID:SCR_002244) Copy   


  • RRID:SCR_002235

    This resource has 1+ mentions.

http://cogpo.org

Ontology used to describe the experimental conditions within cognitive and behavioral experiments, primarily in humans for application and use in the functional neuroimaging community. CogPO has been developed through the integration of the Functional Imaging Biomedical Informatics Research Network (FBIRN) Human Imaging Database (HID) and the BrainMap Database. The design of CogPO concentrates on what can be observed directly: categorization of each paradigm in terms of (1) the stimulus presented to the subjects, (2) the requested instructions, and (3) the returned response.

Proper citation: Cognitive Paradigm Ontology (RRID:SCR_002235) Copy   


http://www.schizophreniaforum.org/

The mission of the SRF is to help in the search for causes, treatments, and understanding of the devastating disease of schizophrenia. Our goal is to foster collaboration among researchers by providing an international online forum where ideas, research news, and data can be presented and discussed. The website is intended to bring together scientists working specifically on schizophrenia, scientists researching related diseases, and basic scientists whose work can shed light on these diseases. In this way, we hope that the Schizophrenia Research Forum will be a catalyst for creative thinking in the quest to understand a deeply complex disease. It is our goal to create and maintain up-to-date content of the highest quality. The website is free of charge to users, independent of industry sponsorship, and open to the public. Though geared toward researchers, we welcome other visitorspeople with mental illnesses, families, the media, and others who need accurate information on research into schizophrenia. We do, however, require that users who wish to post comments and other materials be registered members. All such materials are subject to approval by the editorial team. As a forum, we encourage participation and welcome feedback from the community.

Proper citation: Schizophrenia Research Forum (RRID:SCR_002899) Copy   


  • RRID:SCR_003073

    This resource has 1000+ mentions.

http://rsb.info.nih.gov/nih-image/index.html

Public image processing and analysis program for Macintosh.

Proper citation: NIH Image (RRID:SCR_003073) Copy   


  • RRID:SCR_003131

    This resource has 100+ mentions.

https://neurobiobank.nih.gov/

National resource for investigators utilizing human post-mortem brain tissue and related biospecimens for their research to understand conditions of the nervous system. Federated network of brain and tissue repositories in the United States that collects, evaluates, stores, and makes available to researchers, brain and other tissues in a way that is consistent with the highest ethical and research standards. The NeuroBioBank ensures protection of the privacy and wishes of donors. Provides information to the public about the need for tissue donation and how to register as a donor.

Proper citation: NIH NeuroBioBank (RRID:SCR_003131) Copy   


  • RRID:SCR_002973

    This resource has 1+ mentions.

http://trans.nih.gov/bmap/resources/resources.htm

As part of BMAP gene discovery efforts, mouse brain cDNA libraries and Expressed Sequence Tags (ESTs) have been generated. Through this project a BMAP mouse brain UniGene set consisting of over 24,000 non-redundant members of unique clusters has been developed from EST sequencing of more than 50,000 cDNA clones from 10 regions of adult mouse brain, spinal cord, and retina (http://brainEST.eng.uiowa.edu/). In 2001, NIMH along with NICHD, NIDDK, and NIDA, awarded a contract to the University of Iowa ( M.B. Soares, PI) to isolate full-length cDNA clones corresponding to genes expressed in the developing mouse nervous system and determine their full-coding sequences. The BMAP mouse brain EST sequences can be accessed at NCBI's dbEST database (http://www.ncbi.nlm.nih.gov/dbEST/). Arrayed sets of BMAP mouse brain UniGenes and cDNA libraries, and individual BMAP cDNA clones can be purchased from Open Biosystems, Huntsville, AL (http://www.openbiosystems.com

Proper citation: BMAP cDNA Resources (RRID:SCR_002973) Copy   


  • RRID:SCR_002986

    This resource has 50+ mentions.

https://bioimagesuiteweb.github.io/webapp/index.html

Web applications for analysis of multimodal/multispecies neuroimaging data. Image analysis software package. Has facilities for DTI and fMRI processing. Capabilities for both neuro/cardiac and abdominal image analysis and visualization. Many packages are extensible, and provide functionality for image visualization and registration, surface editing, cardiac 4D multi-slice editing, diffusion tensor image processing, mouse segmentation and registration, and much more. Can be intergrated with other biomedical image processing software, such as FSL, AFNI, and SPM.

Proper citation: BioImage Suite (RRID:SCR_002986) Copy   


  • RRID:SCR_005547

    This resource has 500+ mentions.

http://chronux.org

Open-source software package for the analysis of neural data. Chronux routines may be employed in the analysis of both point process and continuous data, ranging from preprocessing, exploratory and confirmatory analysis. The current release is implemented as a MATLAB library. Chronux offers several routines for computing spectra and coherences for both point and continuous processes. In addition, it also offers several general purpose routines that were found useful such as a routine for extracting specified segments from data, or binning spike time data with bins of a specified size. Since the data can be continuous valued, point process times, or point processes that are binned, methods that apply to all these data types are given in routines whose names end with ''''c'''' for continuous, ''''pb'''' for binned point processes, and ''''pt'''' for point process times. Thus, mtspectrumc computes the spectrum of continuous data, mtspectrumpb computes a spectrum for binned point processes, and mtspectrumpt compute spectra for data consisting of point process times. Hybrid routines are also available and similarly named - for instance coherencycpb computes the coherency between continuous and binned point process data.

Proper citation: Chronux (RRID:SCR_005547) Copy   


http://www.nimh.nih.gov/labs-at-nimh/research-areas/research-support-services/hbcc/index.shtml

A collection of brain tissue from individuals suffering from schizophrenia, bipolar disorder, depression, anxiety disorders, and substance abuse, as well as healthy individuals. The research mission of the NIMH Brain Bank is to better understand the underlying biological mechanisms and pathways that contribute to schizophrenia and other neuropsychiatric disorders, as well as to study normal human brain development.

Proper citation: NIMH Brain Tissue Collection (RRID:SCR_008726) Copy   


http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Atlases

Probabilistic atlases covering 48 cortical and 21 subcortical structural areas, derived from structural data and segmentations kindly provided by the Harvard Center for Morphometric Analysis. T1-weighted images of 21 healthy male and 16 healthy female subjects (ages 18-50) were individually segmented by the CMA using semi-automated tools developed in-house. The T1-weighted images were affine-registered to MNI152 space using FLIRT (FSL), and the transforms then applied to the individual labels. Finally, these were combined across subjects to form population probability maps for each label. Segmentations used to create these atlases were provided by: David Kennedy and Christian Haselgrove, Centre for Morphometric Analysis, Harvard; Bruce Fischl, the Martinos Center for Biomedical Imaging, MGH; Janis Breeze and Jean Frazier from the Child and Adolescent Neuropsychiatric Research Program, Cambridge Health Alliance; Larry Seidman and Jill Goldstein from the Department of Psychiatry of Harvard Medical School.

Proper citation: Harvard - Oxford Cortical Structural Atlas (RRID:SCR_001476) Copy   


http://database.hudsen.eu/

Interactive digital atlas and movies comprising 3-D reconstructions at all stages of human development from Carnegie Stage 12 (CS12; ~26 days post conception (dpc)) to CS23 (~ 56 dpc) and anatomical annotations of the 3-D models linked to an anatomical database. The 3D models are generated using Optical Projection Tomography (OPT; Sharpe et al 2002). The digital atlas is also linked to a gene expression database that has been developed from the Edinburgh Mouse Atlas Project gene expression database (EMAGE). In the future, the HUDSEN EADHB aims to provide the wider scientific and medical communities with a dynamic tool for documenting and analyzing gene expression patterns and morphological changes in the developing human brain.

Proper citation: HUDSEN Electronic Atlas of the Developing Human Brain (RRID:SCR_002056) Copy   


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

Software for the analysis of multiple diffusion properties along fiber bundle as functions in an infinite dimensional space and their association with a set of covariates of interest, such as age, diagnostic status and gender, in real applications. The resulting analysis pipeline can be used for understanding normal brain development, the neural bases of neuropsychiatric disorders, and the joint effects of environmental and genetic factors on white matter fiber bundles.

Proper citation: Functional Regression Analysis of DTI Tract Statistics (RRID:SCR_002293) Copy   


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

A population-specific DTI template for young adolescent Rhesus Macaque (Macaca mulatta) monkeys using 271 high-quality scans. Using such a large number of animals in generating a template allows it to account for variability in the species. Their DTI template is based on the largest number of animals ever used in generating a computational brain template. It is anticipated that their DTI template will help facilitate voxel-based and tract specific WM analyses in non-human primate species, which in turn may increase our understanding of brain function, development, and evolution.

Proper citation: DTI-TEMPLATE-RHESUS-MACAQUES (RRID:SCR_002482) Copy   


  • RRID:SCR_005164

    This resource has 1+ mentions.

http://sccn.ucsd.edu/fmrlab/index.html

A Matlab toolbox for fMRI data analysis using Independent Component Analysis (ICA). It provides an integrated environment to manage, process and analyze fMRI data in a single framework so that users can complete the analysis without switching between software. In addition, it provides an interactive Matlab graphic user interface (GUI). All the necessary processes to apply ICA to fMRI data and review its results can be run from the graphic interface. The FMRLAB processing flow is straightforward. Custom analyses can be performed with Matlab scripts using the FMRLAB functions and data structure. Since fMRI data analysis is a complex enterprise, including digital image processing, statistical analysis and data visualization, an integrated framework combining processing elements is desired eagerly by users in the neuroimaging community. Recently, large number of software tools for data analysis and visualization have been developed for this purpose. However, most of these tools use model-based statistical methods which assume that the users know the hemodynamic response (HR) for their paradigm in advance and can specify a reasonable HR model. Often, however, accurate or reasonable response HR models are unavailable. An alternative data-driven method, infomax ICA (McKeown et al., 1998), does not require that an a priori HR model, instead deriving HRs of spatially independent components of the entire data set from the higher-order statistics of the data themselves. FMRLAB is a toolbox running under Matlab containing necessary components for data-driven fMRI data analysis using the highly reliable infomax ICA algorithm (Bell & Sejnowski, 1995), normalized (Amari, 1999), extended (Lee, Girolami and Sejnowski, 1999) and automated by Makeig et al. FMRLAB has been developed under Matlab 6.1 running on Red Hat Linux. FMRLAB Features * Graphic user interface * Flexible data importing * Interactive data plotting * Computationally efficient * Defined FMRI data structure * Independent component browser * Smooth, transparent component exporting and spatial normalization process * Interface with other software for further analysis or visualization. * SPM-style component plots (MIP, 2-D slice overlay and 3-D)

Proper citation: FMRLAB (RRID:SCR_005164) Copy   


  • RRID:SCR_006798

    This resource has 1000+ mentions.

http://neurosynth.org

Platform for large-scale, automated synthesis of functional magnetic resonance imaging (fMRI) data extracted from published articles. It''s a website wrapped around a set of open-source Python and JavaScript packages. Neurosynth lets you run crude but useful analyses of fMRI data on a very large scale. You can: * Interactively visualize the results of over 3,000 term-based meta-analyses * Select specific locations in the human brain and view associated terms * Browse through the nearly 10,000 studies in the database Their ultimate goal is to enable dynamic real-time analysis, so that you''ll be able to select foci, tables, or entire studies for analysis and run a full-blown meta-analysis without leaving your browser. You''ll also be able to do things like upload entirely new images and obtain probabilistic estimates of the cognitive states most likely to be associated with the image.

Proper citation: NeuroSynth (RRID:SCR_006798) Copy   


  • RRID:SCR_000238

    This resource has 1+ mentions.

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   


  • RRID:SCR_000500

    This resource has 1+ mentions.

http://www.brainscanr.com/

A database of neuroscience-related concepts that utilizes visualization tools for the purpose of research, education and knowledge discovery. The data comes from PubMed abstracts and an algorithm that assumes related terms will appear together. The topics can include computational modeling, behavioral functions and neurological degeneration.

Proper citation: brainSCANr (RRID:SCR_000500) Copy   


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   


  • RRID:SCR_001407

    This resource has 1+ mentions.

http://cng.gmu.edu/brava

A database of digital reconstructions of the human brain arterial arborizations from 61 healthy adult subjects along with extracted morphological measurements. The arterial arborizations include the six major trees stemming from the circle of Willis, namely: the left and right Anterior Cerebral Arteries (ACAs), Middle Cerebral Arteries (MCAs), and Posterior Cerebral Arteries (PCAs).

Proper citation: BraVa (RRID:SCR_001407) Copy   


  • RRID:SCR_001635

    This resource has 1+ mentions.

http://mus.well.ox.ac.uk/gscandb/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Database / display tool of genome scans, with a web interface that lets the user view the data. It does not perform any analyses - these must be done by other software, and the results uploaded into it. The basic features of GSCANDB are: * Parallel viewing of scans for multiple phenotypes. * Parallel analyses of the same scan data. * Genome-wide views of genome scans * Chromosomal region views, with zooming * Gene and SNP Annotation is shown at high zoom levels * Haplotype block structure viewing * The positions of known Trait Loci can be overlayed and queried. * Links to Ensembl, MGI, NCBI, UCSC and other genome data browsers. In GSCANDB, a genome scan has a wide definition, including not only the usual statistical genetic measures of association between genetic variation at a series of loci and variation in a phenotype, but any quantitative measure that varies along the genome. This includes for example competitive genome hybridization data and some kinds of gene expression measurements.

Proper citation: WTCHG Genome Scan Viewer (RRID:SCR_001635) Copy   



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