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http://www.ccnmd.pitt.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 16,2023. Conte Center for the Neuroscience of Mental Disorders (CCNMD) at the University of Pittsburgh offers a highly interactive scientific environment for the study of the neurobiology of schizophrenia. Integrates the laboratory and clinical research activities of investigators from the University of Pittsburgh Schools of Medicine and Arts and Sciences and the adjacent Carnegie Mellon University.

Proper citation: University of Pittsburgh Conte Center for the Neuroscience of Mental Disorders (RRID:SCR_000014) Copy   

•   Source: SciCrunch Registry

http://autopatcher.org/

Software tool for neuronal recording in intact brain.

Proper citation: Autopatcher (RRID:SCR_017464) Copy   

•   Source: SciCrunch Registry

https://github.com/vlchaplin/pyRayleighCuda

Python Rayleigh-Sommerfeld integral for acoustics with optional CUDA graphics processing unit (GPU) implementation.

Proper citation: pyRayleighCuda (RRID:SCR_017453) Copy   

•   Source: SciCrunch Registry

http://HIVBrainSeqDB.org

The HIV Brain Sequence Database (HIVBrainSeqDB) is a public database of HIV envelope sequences, directly sequenced from brain and other tissues from the same patients. For inclusion in the database, sequences must: (i) be deposited in Genbank; (ii) include some portion of the HIV env region; (iii) be clonal, amplified directly from tissue; and (iv) be sampled from the brain, or sampled from a patient for which the database already contains brain sequence. Sequences are annotated with clinical data including viral load, CD4 count, antiretroviral status, neurocognitive impairment, and neuropathological diagnosis, all curated from the original publication. Tissue source is coded using an anatomical ontology, the Foundational Model of Anatomy, to capture the maximum level of detail available, while maintaining ontological relationships between tissues and their subparts. 44 tissue types are represented within the database, grouped into 4 categories: (i) brain, brainstem, and spinal cord; (ii) meninges, choroid plexus, and CSF; (iii) blood and lymphoid; and (iv) other (bone marrow, colon, lung, liver, etc). Currently, the database contains 2517 envelope sequences from 90 patients, obtained from 22 published studies. 1272 sequences are from brain; the remaining 1245 are from blood, lymph node, spleen, bone marrow, colon, lung and other non-brain tissues. The database interface utilizes a faceted interface, allowing real-time combination of multiple search parameters to assemble a meta-dataset, which can be downloaded for further analysis. This online resource will greatly facilitate analysis of the genetic aspects of HIV macrophage tropism, HIV compartmentalization and evolution within the brain and other tissue reservoirs, and the relationship of these findings to HIV-associated neurological disorders and other clinical consequences of HIV infection.

Proper citation: HIV Brain Sequence Database (RRID:SCR_008819) Copy   

•   Source: SciCrunch Registry

http://neuromorphometrics.com/?page_id=23

Collection of neuroanatomically labeled MRI brain scans, created by neuroanatomical experts. Regions of interest include the sub-cortical structures (thalamus, caudate, putamen, hippocampus, etc), along with ventricles, brain stem, cerebellum, and gray and white matter and sub-divided cortex into parcellation units that are defined by gyral and sulcal landmarks.

Proper citation: Manually Labeled MRI Brain Scan Database (RRID:SCR_009604) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://fcon_1000.projects.nitrc.org/indi/pro/nyu.html

Datasets including a collection of scans from 49 psychiatrically evaluated neurotypical adults, ranging in age from 6 to 55 years old, with age, gender and intelligence quotient (IQ) information provided. Future releases will include more comprehensive phenotypic information, and child and adolescent datasets, as well as individuals from clinical populations. The following data are released for every participant: * At least one 6-minute resting state fMRI scan (R-fMRI) * * One high-resolution T1-weighted mprage, defaced to protect patient confidentiality * Two 64-direction diffusion tensor imaging scans * Demographic information (age, gender) and IQ-measures (Verbal, Performance, and Composite; Weschler Abbreviated Scale of Intelligence - WASI) * Most participants have 2 R-fMRI scans, collected less than 1 hour apart in the same scanning session. Rest_1 is always collected first.

Proper citation: NYU Institute for Pediatric Neuroscience Sample (RRID:SCR_010458) Copy   

•   Source: SciCrunch Registry

http://kimlab.io/brain-map/atlas/

Website to visualize and share anatomical labels. Franklin and Paxinos (FP) based anatomical labels in Allen Common Coordinate Framework (CCF). Cell type specific transgenic mice and MRI atlas were used to adjust and further segment labels. New segmentations were created in dorsal striatum using cortico-striatal connectivity data. Anatomical labels were digitized based on Allen ontology, and web-interface was created for easy visualization. These labels provide resource to isolate and identify mouse brain anatomical structures. Open source data sharing will facilitate further refinement of anatomical labels and integration of data interpretation within single anatomical platform.

Proper citation: Enhanced and Unified Anatomical Labeling for Common Mouse Brain Atlas (RRID:SCR_019267) Copy   

•   Source: SciCrunch Registry

https://cells.ucsc.edu/

Web based tool to visualize gene expression and metadata annotation distribution throughout single cell dataset or multiple datasets. Interactive viewer for single cell expression. You can click on and hover over cells to get meta information, search for genes to color on and click clusters to show cluster specific marker genes.

Proper citation: UCSC Cell Browser (RRID:SCR_023293) Copy   

•   Source: SciCrunch Registry

http://hbatlas.org

A data repository containing transcriptome and associated metadata for the developing and adult human brain. It provides genome-wide, exon-level transcriptome data from both sexes and multiple ethnicities.

Proper citation: Human Brain Transcriptome (RRID:SCR_013742) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://clinicaltrials.gov/ct2/show/NCT00014001

The NIMH-funded Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) Study was a nationwide public health-focused clinical trial that compared the effectiveness of older (first available in the 1950s) and newer (available since the 1990s) antipsychotic medications used to treat schizophrenia. These newer medications, known as atypical antipsychotics, cost roughly 10 times as much as the older medications. CATIE is the largest, longest, and most comprehensive independent trial ever done to examine existing therapies for this disease. Schizophrenia is a brain disorder characterized by hallucinations, delusions, and disordered thinking. The course of schizophrenia is variable, but usually is recurrent and chronic, often causing severe disability. Previous studies have shown that taking antipsychotic medications consistently is far more effective than taking no medicine and that the drugs are necessary to manage the disease. The aim of the CATIE study was to determine which medications provide the best treatment for schizophrenia. Additional information may be found by following the links, http://www.nimh.nih.gov/trials/practical/catie/index.shtml, http://www.clinicaltrials.gov/ct/show/NCT00014001?order=1

Proper citation: CATIE - Clinical Antipsychotic Trials in Intervention Effectiveness (RRID:SCR_005615) Copy   

•   Source: SciCrunch Registry

http://fcon_1000.projects.nitrc.org/indi/abide/

Resting state functional magnetic resonance imaging (R-fMRI) datasets from 539 individuals with autism spectrum disorder (ASD) and 573 typical controls. This initiative involved 16 international sites, sharing 20 samples yielding 1112 datasets composed of both MRI data and an extensive array of phenotypic information common across nearly all sites. This effort is expected to facilitate discovery science and comparisons across samples. All datasets are anonymous, with no protected health information included.

Proper citation: ABIDE (RRID:SCR_003612) Copy   

•   Source: SciCrunch Registry

http://www.nimh.nih.gov/funding/clinical-trials-for-researchers/datasets/nimh-procedures-for-requesting-data-sets.shtml

A listing of data sets from NIMH-supported clinical trials. Limited Access Datasets are available from numerous NIMH studies. NIMH requires all investigators seeking access to data from NIMH-supported trials held by NIMH to execute and submit as their request the appropriate Data Use Certification pertaining to the trial. The datasets distributed by NIMH are referred to as limited access datasets because access is limited to qualified researchers who complete Data Use Certifications.

Proper citation: Limited Access Datasets From NIMH Clinical Trials (RRID:SCR_005614) Copy   

•   Source: SciCrunch Registry

http://mialab.mrn.org/data/index.html

An MRI data set that demonstrates the utility of a mega-analytic approach by identifying the effects of age and gender on the resting-state networks (RSNs) of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12-71 years). Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. RSNs were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described, provide a useful baseline for future investigations of brain networks in health and disease.

Proper citation: MIALAB - Resting State Data (RRID:SCR_008914) Copy   

•   Source: SciCrunch Registry

https://github.com/DeNardoLab/BehaviorDEPOT

Software tool for automated behavioral detection based on markerless pose tracking. Behavioral analysis tool to first compile and clean point-tracking output from DeepLabCut, and then classify behavioral epochs using custom behavior classifiers. Used to detect frame by frame behavior from video time series and can analyze results of common experimental assays, including fear conditioning, decision-making in T-maze, open field, elevated plus maze, and novel object exploration. Calculates kinematic and postural statistics from keypoint tracking data from pose estimation software outputs.

Proper citation: BehaviorDEPOT (RRID:SCR_023602) Copy   

•   Source: SciCrunch Registry

https://github.com/TADA-A/TADA-A/tree/master

Software statistical framework for mapping risk genes from de novo mutations in whole genome sequencing studies.

Proper citation: TADA-A (RRID:SCR_024538) Copy   

•   Source: SciCrunch Registry

https://kimlab.io/brain-map/epDevAtlas/

Suite of open access resources including 3D atlases of early postnatally developing mouse brain and mapped cell type density growth charts, which can be used as standalone resources or to implement data integration. Web platform can be utilized to analyze and visualize the spatiotemporal growth of GABAergic, microglial, and cortical layer-specific cell type densities in 3D. Morphologically averaged symmetric template brains serve as the basis reference space and coordinate system with an isotropic resolution of 20 μm (XYZ in coronal plane). Average transformations were conducted at 20 μm voxel resolution by interpolating high resolution serial two photon tomography images from primarily Vip-IRES-Cre;Ai14 mice at postnatal (P) ages P4, P6, P8, P10, P12, and P14. For all ages, anatomical labels from the P56 Allen Mouse Brain Common Coordinate Framework (Allen CCFv3) were iteratively down registered to each early postnatal time point in a non-linear manner, aided by manual parcellations of landmarks in 3D, consistent with the Allen Mouse Reference Atlas Ontology.

Proper citation: Early Postnatal Developmental Mouse Brain Atlas (RRID:SCR_024725) Copy   

•   Source: SciCrunch Registry

https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/XTRACT

Software command line tool for automated tractography. Standardised protocols for automated tractography in human and macaque brain.

Proper citation: XTRACT (RRID:SCR_024933) Copy   

•   Source: SciCrunch Registry