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http://www.matrics.ucla.edu/index.html

Cognitive deficits -- including impairments in areas such as memory, attention, and executive function -- are a major determinant and predictor of long-term disability in schizophrenia. Unfortunately, available antipsychotic medications are relatively ineffective in improving cognition. Scientific discoveries during the past decade suggest that there may be opportunities for developing medications that will be effective for improving cognition in schizophrenia. The NIMH has identified obstacles that are likely to interfere with the development of pharmacological agents for treating cognition in schizophrenia. These include: (1) a lack of a consensus as to how cognition in schizophrenia should be measured; (2) differing opinions as to the pharmacological approaches that are most promising; (3) challenges in clinical trial design; (4) concerns in the pharmaceutical industry regarding the US Food and Drug Administration''s (FDA) approaches to drug approval for this indication; and (5) issues in developing a research infrastructure that can carry out clinical trials of promising drugs. The MATRICS program will bring together representatives of academia, industry, and government in a consensus process for addressing all of these obstacles. Specific goals of the NIMH MATRICS are: * To catalyze regulatory acceptance of cognition in schizophrenia as a target for drug registration. * To promote development of novel compounds to enhance cognition in schizophrenia. * Leverage economic research power of industry to focus on important but neglected clinical targets. * Identify lead compounds and if deemed feasible, support human proof of concept trials for cognition in schizophrenia.

Proper citation: MATRICS - Measurement And Treatment Research to Improve Cognition in Schizophrenia (RRID:SCR_005644) Copy   

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http://www.open-ephys.org/pulsepal

Open source pulse train generator that allows users to create and trigger software defined trains of voltage pulses with high temporal precision. Generates precisely timed pulse sequences for use in research involving electrophysiology or psychophysics.

Proper citation: Open Ephys: Pulse Pal (RRID:SCR_017203) Copy   

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

A free software tool for Copy Number Variation (CNV) detection from SNP genotyping arrays. Currently it can handle signal intensity data from Illumina and Affymetrix arrays. With appropriate preparation of file format, it can also handle other types of SNP arrays and oligonucleotide arrays. PennCNV implements a hidden Markov model (HMM) that integrates multiple sources of information to infer CNV calls for individual genotyped samples. It differs form segmentation-based algorithm in that it considered SNP allelic ratio distribution as well as other factors, in addition to signal intensity alone. In addition, PennCNV can optionally utilize family information to generate family-based CNV calls by several different algorithms. Furthermore, PennCNV can generate CNV calls given a specific set of candidate CNV regions, through a validation-calling algorithm.

Proper citation: PennCNV (RRID:SCR_002518) Copy   

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http://www.patternlabforproteomics.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented July 5, 2018. Gene Ontology Explorer (GOEx) combines data from protein fold changes with GO over-representation statistics to help draw conclusions in proteomic experiments. It is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. A recent hack included in GOEx is to load the sparse matrix index file directly into GOEx, instead of going through the report generation using the AC/T-fold methods. This makes it easy for GOEx to analyze any list of proteins as long as the list follows the index file format (described in manuscript) . Please note that if using this alternative strategy, there will be no protein fold information. Platform: Windows compatible

Proper citation: GOEx - Gene Ontology Explorer (RRID:SCR_005779) Copy   

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http://www.agre.org/index.cfm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. A private repository of clinical and genetic information on families with autism. Genetic and clinical data are obtained from families that have more than one family member diagnosed with an Autism Spectrum Disorder. The biological samples, along with the accompanying clinical data, are made available to AGRE-approved researchers worldwide. As they become available, additional family pedigrees will be posted in the online catalog. Cell lines have been established for the majority of families in this collection and serum/plasma is available on a subset of the subjects until stocks are depleted. The diagnosis of autism has been made using the standard Autism Diagnostic Interview-Revised (ADI-R) algorithm and the Autism Diagnostic Observation Scale (ADOS-G). Detailed birth and medical histories (including basic dysmorphology assessments) on children as well as family and medical information for parents and unaffected siblings, are available for nearly all families. DNA, cell lines, serum, plasma and clinical information are made available to AGRE-approved researchers for analysis.

Proper citation: Autism Genetic Resource Exchange (RRID:SCR_004403) Copy   

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https://yeatmanlab.github.io/pyAFQ/

Software package focused on automated delineation of major fiber tracts in individual human brains, and quantification of tissue properties within the tracts.Software for automated processing and analysis of diffusion MRI data. Automates tractometry.

Proper citation: Automated Fiber Quantification in Python (RRID:SCR_023366) Copy   

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http://jaxmice.jax.org/list/ra1642.html

Produce new neurological mouse models that could serve as experimental models for the exploration of basic neurobiological mechanisms and diseases. The impetus for the program resulted from the recognition that: * The value of genomic data would remain limited unless more information about the functionality of its individual components became available. * The task of linking genes to specific behavior would best be accomplished by employing a combination of different approaches. In an effort to complement already existing programs, the Neuroscience Mutagenesis Facility decided to use: a random, genome-wide approach to mutagenesis, i.e.N-ethyl-N-nitrosourea (ENU) as the mutagen; a three-generation back-cross breeding scheme to focus on the detection of recessive mutations; behavioral screens selective for the detection of phenotypes deemed useful for the program goals. The resulting mutant mouse lines have been available to the scientific community for the last five years and over 700 NMF mice have been sent to interested investigators for research; these mutant mouse lines will remain available as frozen embryos (which can be re-derived on request) and can be ordered through the JAX customer service at 1-800-422-6423 (or 207-288-5845). The results of the work of the Neuroscience Mutagenesis Facility and that of two other neurogenesis centers, i.e. The Neurogenomics Project at Northwestern University, and the Neuromutagenesis Project of the Tennessee Mouse Genome Consortium, can also be seen at Neuromice.org, a common web site of these three research centers; in addition, information about all mutants produced by these groups has been recorded in MGI.

Proper citation: JAX Neuroscience Mutagenesis Facility (RRID:SCR_007437) Copy   

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http://dx.doi.org/10.5281/zenodo.21157

A graphical source code file used for an automated motion detection and reward system for animal training (see comment for full paper title). It was designed on the LabVIEW programming system. Running the program requires the appropriate LabVIEW runtime software from National Instruments Corporation.

Proper citation: Monkey Motion (RRID:SCR_014285) Copy   

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https://www.nitrc.org/projects/fmridatacenter/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 25, 2013 Public curated repository of peer reviewed fMRI studies and their underlying data. This Web-accessible database has data mining capabilities and the means to deliver requested data to the user (via Web, CD, or digital tape). Datasets available: 107 NOTE: The fMRIDC is down temporarily while it moves to a new home at UCLA. Check back again in late Jan 2013! The goal of the Center is to help speed the progress and the understanding of cognitive processes and the neural substrates that underlie them by: * Providing a publicly accessible repository of peer-reviewed fMRI studies. * Providing all data necessary to interpret, analyze, and replicate these fMRI studies. * Provide training for both the academic and professional communities. The Center will accept data from those researchers who are publishing fMRI imaging articles in peer-reviewed journals. The goal is to serve the entire fMRI community.

Proper citation: fMRI Data Center (RRID:SCR_007278) Copy   

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http://hendrix.imm.dtu.dk/software/lyngby/

Matlab toolbox for the analysis of functional neuroimages (PET, fMRI). The toolbox contains a number of models: FIR-filter, Lange-Zeger, K-means clustering among others, visualizations and reading of neuroimaging files.

Proper citation: Lyngby (RRID:SCR_007143) Copy   

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http://www.bmu.psychiatry.cam.ac.uk/software/

Suite of programs developed for fMRI analysis in a Virtual Pipeline Laboratory facilitates combining program modules from different software packages into processing pipelines to create analysis solutions which are not possible with a single software package alone. Current pipelines include fMRI analysis, statistical testing based on randomization methods and fractal spectral analysis. Pipelines are continually being added. The software is mostly written in C. This fMRI analysis package supports batch processing and comprises the following general functions at the first level of individual image analysis: movement correction (interpolation and regression), time series modeling, data resampling in the wavelet domain, hypothesis testing at voxel and cluster levels. Additionally, there is code for second level analysis - group and factorial or ANOVA mapping - after co-registration of voxel statistic maps from individual images in a standard space. The main point of difference from other fMRI analysis packages is the emphasis throughout on the use of data resampling (permutation or randomization) as a basis for inference on individual, group and factorial test statistics at voxel and cluster levels of resolution.

Proper citation: Cambridge Brain Activation (RRID:SCR_007109) Copy   

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https://bams1.org/

Knowledge management system designed to handle neurobiological information at different levels of organization of vertebrate nervous system. Database and repository for information about neural circuitry, storing and analyzing data concerned with nomenclature, taxonomy, axonal connections, and neuronal cell types. Handles data and metadata collated from original literature, or inserted by scientists that is associated to four levels of organization of vertebrate nervous system. Data about expressed molecules, neuron types and classes, brain regions, and networks of brain regions.

Proper citation: Brain Architecture Management System (RRID:SCR_007251) Copy   

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http://www.cidr.jhmi.edu/

Next generation sequencing and genotyping services provided to investigators working to discover genes that contribute to disease. On-site statistical geneticists provide insight into analysis issues as they relate to study design, data production and quality control. In addition, CIDR has a consulting agreement with the University of Washington Genetics Coordinating Center (GCC) to provide statistical and analytical support, most predominantly in the areas of GWAS data cleaning and methods development. Completed studies encompass over 175 phenotypes across 530 projects and 620,000 samples. The impact is evidenced by over 380 peer-reviewed papers published in 100 journals. Three pathways exist to access the CIDR genotyping facility: * NIH CIDR Program: The CIDR contract is funded by 14 NIH Institutes and provides genotyping and statistical genetic services to investigators approved for access through competitive peer review. An application is required for projects supported by the NIH CIDR Program. * The HTS Facility: The High Throughput Sequencing Facility, part of the Johns Hopkins Genetic Resources Core Facility, provides next generation sequencing services to internal JHU investigators and external scientists on a fee-for-service basis. * The JHU SNP Center: The SNP Center, part of the Johns Hopkins Genetic Resources Core Facility, provides genotyping to internal JHU investigators and external scientists on a fee-for-service basis. Data computation service is included to cover the statistical genetics services provided for investigators seeking to identify genes that contribute to human disease. Human Genotyping Services include SNP Genome Wide Association Studies, SNP Linkage Scans, Custom SNP Studies, Cancer Panel, MHC Panels, and Methylation Profiling. Mouse Genotyping Services include SNP Scans and Custom SNP Studies.

Proper citation: Center for Inherited Disease Research (RRID:SCR_007339) Copy   

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http://www.nimh.nih.gov/funding/clinical-trials-for-researchers/practical/stard/index.shtml

A nationwide public health clinical trial conducted to determine the effectiveness of different treatments for people with major depression, in both primary and specialty care settings, who have not responded to initial treatment with an antidepressant. This is the largest and longest study ever done to evaluate depression treatment. The study is completed and no longer recruiting participants. Each of the four levels of the study tested a different medication or medication combination. The primary goal of each level was to determine if the treatment used during that level could adequately treat participants����?? major depressive disorder (MDD). Those who did not become symptom-free could proceed to the next level of treatment. The design of the STAR*D study reflects what is done in clinical practice because it allowed study participants to choose certain treatment strategies most acceptable to them and limited the randomization of each participant only to his/her range of acceptable treatment strategies. No prior studies have evaluated the different treatment strategies in broadly defined participant groups treated in diverse care settings. Over a seven-year period, the study enrolled 4,041 outpatients, ages 18-75 years, from 41 clinical sites around the country, which included both specialty care settings and primary medical care settings. Participants represented a broad range of ethnic and socioeconomic groups. All participants were diagnosed with MDD, were already seeking care at one of these sites, and were referred to the trial by their doctors. * STAR*D Study Medications: Citalopram (Celexa), Sertraline (Zoloft), Bupropion SR (Wellbutrin SR), Venlafaxine XR (Effexor XR), Buspirone (BuSpar), Mirtazapine (Remeron), Triiodothyronine (T3) (Cytomel), Nortriptyline (Pamelor, Aventyl), Tranylcypromine (Parnate), Lithium (Eskalith, Lithobid) *STAR*D Talk Therapy:Cognitive Therapy

Proper citation: Sequenced Treatment Alternatives to Relieve Depression Study (RRID:SCR_008051) Copy   

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http://www.jneurosci.org/supplemental/18/12/4570/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on January 29, 2013. Supplemental data for the paper Changes in mitochondrial function resulting from synaptic activity in the rat hippocampal slice, by Vytautas P. Bindokas, Chong C. Lee, William F. Colmers, and Richard J. Miller that appears in the Journal of Neuroscience June 15, 1998. You can view digital movies of changes in fluorescence intensity by clicking on the title of interest.

Proper citation: Hippocampal Slice Wave Animations (RRID:SCR_008372) Copy   

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http://grey.colorado.edu/emergent

emergent is a comprehensive, full-featured neural network simulator that allows for the creation and analysis of complex, sophisticated models of the brain in the world. With an emphasis on qualitative analysis and teaching, it also supports the workflow of professional neural network researchers. Its high level drag-and-drop programming interface, built on top of a scripting language that has full introspective access to all aspects of networks and the software itself, allows one to write programs that seamlessly weave together the training of a network and evolution of its environment without ever typing out a line of code. Networks and all of their state variables are visually inspected in 3d, allowing for a quick visual regression of network dynamics and robot behavior. This same 3d world sports a highly accurate Newtonian physics simulation, allowing you to create rich robotics simulations (for example, a car). As a direct descendant of PDP (1986) and PDP (1999), emergent has been in development for decades. In the most recent versions available strive to distill it down to its essential elements. Those that take the time to learn the best practices will be rewarded with the ability to create and understand the most complicated neural models ever published.

Proper citation: Emergent (RRID:SCR_008500) Copy   

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http://www.cognitiveatlas.org/

Knowledge base (or ontology) that characterizes the state of current thought in cognitive science that captures knowledge from users with expertise in psychology, cognitive science, and neuroscience. There are two basic kinds of knowledge in the knowledge base. Terms provide definitions and properties for individual concepts and tasks. Assertions describe relations between terms in the same way that a sentence describes relations between parts of speech. The goal is to develop a knowledge base that will support annotation of data in databases, as well as supporting improved discourse in the community. It is open to all interested researchers. A fundamental feature of the knowledge base is the desire and ability to capture not just agreement but also disagreement regarding definitions and assertions. Thus, if you see a definition or assertion that you disagree with, then you can assert and describe your disagreement. The project is led by Russell Poldrack, Professor of Psychology and Neurobiology at the University of Texas at Austin in collaboration with the UCLA Center for Computational Biology (A. Toga, PI) and UCLA Consortium for Neuropsychiatric Phenomics (R. Bilder, PI). Most tasks used in cognitive psychology research are not identical across different laboratories or even within the same laboratory over time. A major advantage of anchoring cognitive ontologies to the measurement level is that the strategy for determining changes in task properties is easier than tracking changes in concept definitions and usage. The process is easier because task parameters are usually (if not always) operationalized objectively, offering a clear basis to judge divergence in methods. The process is also easier because most tasks are based on prior tasks, and thus can more readily be considered descendants in a phylogenetic sense.

Proper citation: Cognitive Atlas (RRID:SCR_002793) Copy   

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http://sumsdb.wustl.edu/sums/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on May 11, 2016. Repository of brain-mapping data (surfaces and volumes; structural and functional data) derived from studies including fMRI and MRI from many laboratories, providing convenient access to a growing body of neuroimaging and related data. WebCaret is an online visualization tool for viewing SumsDB datasets. SumsDB includes: * data on cerebral cortex and cerebellar cortex * individual subject data and population data mapped to atlases * data from FreeSurfer and other brainmapping software besides Caret SumsDB provides multiple levels of data access and security: * Free (public) access (e.g., for data associated with published studies) * Data access restricted to collaborators in different laboratories * Owner-only access for work in progress Data can be downloaded from SumsDB as individual files or as bundles archived for offline visualization and analysis in Caret WebCaret provides online Caret-style visualization while circumventing software and data downloads. It is a server-side application running on a linux cluster at Washington University. WebCaret "scenes" facilitate rapid visualization of complex combinations of data Bi-directional links between online publications and WebCaret/SumsDB provide: * Links from figures in online journal article to corresponding scenes in WebCaret * Links from metadata in WebCaret directly to relevant online publications and figures

Proper citation: SumsDB (RRID:SCR_002759) Copy   

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http://brainmap.org/

A community database of published functional and structural neuroimaging experiments with both metadata descriptions of experimental design and activation locations in the form of stereotactic coordinates (x,y,z) in Talairach or MNI space. BrainMap provides not only data for meta-analyses and data mining, but also distributes software and concepts for quantitative integration of neuroimaging data. The goal of BrainMap is to develop software and tools to share neuroimaging results and enable meta-analysis of studies of human brain function and structure in healthy and diseased subjects. It is a tool to rapidly retrieve and understand studies in specific research domains, such as language, memory, attention, reasoning, emotion, and perception, and to perform meta-analyses of like studies. Brainmap contains the following software: # Sleuth: database searches and Talairach coordinate plotting (this application requires a username and password) # GingerALE: performs meta-analyses via the activation likelihood estimation (ALE) method; also converts coordinates between MNI and Talairach spaces using icbm2tal # Scribe: database entry of published functional neuroimaging papers with coordinate results

Proper citation: brainmap.org (RRID:SCR_003069) Copy   

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http://braininfo.rprc.washington.edu

Portal to neuroanatomical information on the Web that helps you identify structures in the brain and provides a variety of information about each structure by porting you to the best of 1500 web pages at 100 other neuroscience sites. BrainInfo consists of three basic components: NeuroNames, a developing database of definitions of neuroanatomic structures in four species, their most common acronyms and their names in eight languages; NeuroMaps, a digital atlas system based on 3-D canonical stereotaxic atlases of rhesus macaque and mouse brains and programs that enable one to map data to standard surface and cross-sectional views of the brains for presentation and publication; and the NeuroMaps precursor: Template Atlas of the Primate Brain, a 2-D stereotaxic atlas of the longtailed (fascicularis) macaque brain that shows the locations of some 250 architectonic areas of macaque cortex. The NeuroMaps atlases will soon include a number of overlays showing the locations of cortical areas and other neuroscientific data in the standard frameworks of the macaque and mouse atlases. Viewers are encouraged to use NeuroNames as a stable source of unique standard terms and acronyms for brain structures in publications, illustrations and indexing systems; to use templates extracted from the NeuroMaps macaque and mouse brain atlases for presenting neuroscientific information in image format; and to use the Template Atlas for warping to MRIs or PET scans of the macaque brain to estimate the stereotaxic locations of structures.

Proper citation: BrainInfo (RRID:SCR_003142) Copy   

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