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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://mindboggle.info

Mindboggle (http://mindboggle.info) is open source software for analyzing the shapes of brain structures from human MRI data. The following publication in PLoS Computational Biology documents and evaluates the software: Klein A, Ghosh SS, Bao FS, Giard J, Hame Y, Stavsky E, Lee N, Rossa B, Reuter M, Neto EC, Keshavan A. (2017) Mindboggling morphometry of human brains. PLoS Computational Biology 13(3): e1005350. doi:10.1371/journal.pcbi.1005350

Proper citation: Mindboggle (RRID:SCR_002438) Copy   

•   Source: SciCrunch Registry

http://neuromab.ucdavis.edu/

A national mouse monoclonal antibody generating resource for biochemical and immunohistochemical applications in mammalian brain. NeuroMabs are generated from mice immunized with synthetic and recombinant immunogens corresponding to components of the neuronal proteome as predicted from genomic and other large-scale cloning efforts. Comprehensive biochemical and immunohistochemical analyses of human, primate and non-primate mammalian brain are incorporated into the initial NeuroMab screening procedure. This yields a subset of mouse mAbs that are optimized for use in brain (i.e. NeuroMabs): for immunocytochemical-based imaging studies of protein localization in adult, developing and pathological brain samples, for biochemical analyses of subunit composition and post-translational modifications of native brain proteins, and for proteomic analyses of native brain protein networks. The NeuroMab facility was initially funded with a five-year U24 cooperative grant from NINDS and NIMH. The initial goal of the facility for this funding period is to generate a library of novel NeuroMabs against neuronal proteins, initially focusing on membrane proteins (receptors/channels/transporters), synaptic proteins, other neuronal signaling molecules, and proteins with established links to disease states. The scope of the facility was expanded with supplements from the NIH Blueprint for Neuroscience Research to include neurodevelopmental targets, the NIH Roadmap for Medical Research to include epigenetics targets, and NIH Office of Rare Diseases Research to include rare disease targets. These NeuroMabs will then be produced on a large scale and made available to the neuroscience research community on an inexpensive basis as tissue culture supernatants or purified immunoglobulin by Antibodies Inc. The UC Davis/NIH NeuroMab Facility makes NeuroMabs available directly to end users and is unable to accommodate sales to distributors for third party distribution. Note, NeuroMab antibodies are now offered through antibodiesinc.

Proper citation: NeuroMab (RRID:SCR_003086) Copy   

•   Source: SciCrunch Registry

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

This resource was created to host descriptions of protocols, definitions and rules for the reliable identification and localization of human brain anatomy and discussions of best practices in brain labeling. Project for manual anatomical labeling of human brain MRI data, and the visual presentation of labeled brain images.

Proper citation: BrainColor: Collaborative Open Labeling Online Resource (RRID:SCR_006377) Copy   

•   Source: SciCrunch Registry

http://nimhstemcells.org/

Induced Pluripotent Stem Cell (iPSC) and Source Cells available for distribution for postnatal-to-adult human control and patient-derived cells and their reprogrammed derivatives in support of stem cell research relevant to mental disorders. This includes but is not limited to anxiety disorders, attention deficit hyperactivity disorder, autism spectrum disorders, bipolar disorder, borderline personality disorder, depression, eating disorders, obsessive-compulsive disorder, panic disorder, post-traumatic stress disorder, and schizophrenia. The capabilities of the repository range from derivation and banking of primary source cells from postnatal through adult human subject tissue to more comprehensive banking and validation of induced pluripotent stem cells (iPSCs) or similar reprogrammed / de-differentiated cells. Please send a message with the Contact page if you wish to contribute source cells or iPSC.

Proper citation: NIMH Stem Cell Center (RRID:SCR_006682) Copy   

•   Source: SciCrunch Registry

http://nimh-repository.rti.org/

A program that synthesizes, purifies, and distributes otherwise unavailable essential compounds to stimulate basic and clinical research in psychopharmacology relevant to mental health in areas such as the molecular pharmacology and signaling of CNS receptors, longitudinal studies to evaluate the molecular, biochemical, and behavioral actions of psychoactive compounds, and functional brain imaging in both primates and humans. WHAT IS AVAILABLE: * Ligands for CNS receptors, radiolabeled compounds for autoradiography and neuroimaging, biochemical markers, drug analogs and metabolites, and reference standards * Synthesis (including GMP) of promising compounds for mental health research, including preclinical toxicology and safety studies, especially compounds for PET neuroimaging * A listing of currently available NIMH CSDSP compounds is available online at www.nimh-repository.rti.org. RTI International scientists can provide investigators with technical assistance and additional information about the compounds on request. Data sheets containing purity, storage, and handling information are supplied with all NIMH CSDSP compounds. WHO IS ELIGIBLE: Investigators involved in basic or clinical research relevant to mental health are eligible to submit requests. To learn more about current NIMH research areas, please visit the NIMH website at www.nimh.nih.gov. NIMH CSDSP compounds are free to qualified academic investigators, but payment may be required from nonacademic requestors. Investigators interested in obtaining radiolabeled compounds but uncertain about what type of label or specific activity would work best for them may obtain help by communicating with the technical contacts listed on the website.

Proper citation: NIMH Chemical Synthesis and Drug Supply Program (RRID:SCR_004921) Copy   

•   Source: SciCrunch Registry

http://senselab.med.yale.edu

The SenseLab Project is a long-term effort to build integrated, multidisciplinary models of neurons and neural systems. It was founded in 1993 as part of the original Human Brain Project, which began the development of neuroinformatics tools in support of neuroscience research. It is now part of the Neuroscience Information Framework (NIF) and the International Neuroinformatics Coordinating Facility (INCF). The SenseLab project involves novel informatics approaches to constructing databases and database tools for collecting and analyzing neuroscience information, using the olfactory system as a model, with extension to other brain systems. SenseLab contains seven related databases that support experimental and theoretical research on the membrane properties: CellPropDB, NeuronDB, ModelDB, ORDB, OdorDB, OdorMapDB, BrainPharmA pilot Web portal that successfully integrates multidisciplinary neurocience data.

Proper citation: SenseLab (RRID:SCR_007276) 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://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

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

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://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

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

A long-term outpatient study designed to find out which treatments, or combinations of treatments, are most effective for treating episodes of depression and mania and for preventing recurrent episodes in people with bipolar disorder. This study has been completed. (2005) STEP-BD is evaluating all the best-practice treatment options used for bipolar disorder: mood-stabilizing medications, antidepressants, atypical antipsychotics, and psychosocial interventions - or talk therapies - including Cognitive Behavioral Therapy, Family-focused Therapy, Interpersonal and Social Rhythm Therapy, and Collaborative Care (psychoeducation). There are two kinds of treatment pathways in STEP-BD, and participants may have the opportunity to take part in both. The medications and psychosocial interventions provided in these pathways are considered among the best choices of treatment for bipolar disorder in everyday clinical practice. In the Best Practice Pathway, participants are followed by a STEP-BD certified doctor and all treatment choices are individualized. Everyone enrolled in STEP-BD may participate in this pathway. Participants and their doctors work together to decide on the best treatment plans and to change these plans if needed. Also, anyone who wishes to stay on his or her current treatment upon entering STEP-BD may do so in this pathway. Adolescents and adults age 15 years and older may participate in the Best Practice Pathway. For adults age 18 and older, another way to participate is in the STEP-BD Randomized Care Pathways. Depending on their symptoms, participants may be offered treatment in one or more of these pathways during the course of the study. The participants remain on mood-stabilizing medication. However, because doctors are uncertain which of several treatment strategies work best for bipolar disorder, another medication and/or talk therapy may be added. Each Randomized Care Pathway involves a different set of these additional treatments. Unlike in the Best Practice Pathway, the participants in the Randomized Care Pathways are randomly assigned to treatments. Also, in some cases, neither the participant nor the doctor will be told which of the different medications is being added. This is called a double-blind study and is done so that the medication effects can be evaluated objectively, without any unintended bias that may come from knowing what has been assigned. Participants will not be assigned medications that they have had bad reactions to in the past, that they are strongly opposed to, or that the doctor feels are unsuitable for them. The medication(s) participants may be randomly assigned to in the Randomized Care Pathways are free of charge. There are other treatment options for participants if they do not respond well to the treatment assigned to them. Also, participants may return to the Best Practice Pathway at any time. About 1,500 individuals will be enrolled in at least one Randomized Care Pathway during their period of participation in STEP-BD. It is important to note that STEP-BD provides continuity of care. For example, if a participant starts out in the Best Practice Pathway and later chooses to enter one of the Randomized Care Pathways, he or she continues with the same STEP-BD doctor and treatment team. Then, after completing the Randomized Care Pathway, the participant may return to the Best Practice Pathway for ongoing, individually-tailored treatment. Follow the link to view study info at Clinicaltrials.gov, http://www.clinicaltrials.gov/ct/show/NCT00012558?order=1

Proper citation: Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) (RRID:SCR_008844) Copy   

•   Source: SciCrunch Registry

http://research.mssm.edu/cnic/

Center to advance research and training in mathematical, computational and modern imaging approaches to understanding the brain and its functions. Software tools and associated reconstruction data produced in the center are available. Researchers study the relationships between neural function and structure at levels ranging from the molecular and cellular, through network organization of the brain. This involves the development of new computational and analytic tools for imaging and visualization of 3-D neural morphology, from the gross topologic characteristics of the dendritic arbor to the fine structure of spines and their synapses. Numerical simulations of neural mechanisms based on these structural data are compared with in-vivo and in-vitro electrophysiological recordings. The group also develops new theoretical and analytic approaches to exploring the function of neural models of working memory. The goal of this analytic work is to combine biophysically realistic models and simulations with reduced mathematical models that capture essential dynamical behaviors while reproducing the functionally important features of experimental data. Research areas include: Imaging Studies, Volume Integration, Visualization Techniques, Medial Axis Extraction, Spine Detection and Classification, Applications of Rayburst, Analysis of Spatially Complex Structures, Computational Modeling, Mathematical and Analytic Studies

Proper citation: Computational Neurobiology and Imaging Center (RRID:SCR_013317) Copy   

•   Source: SciCrunch Registry

http://interactome.baderlab.org/

Project portal for the Human Reference Protein Interactome Project, which aims generate a first reference map of the human protein-protein interactome network by identifying binary protein-protein interactions (PPIs). It achieves this by systematically interrogating all pairwise combinations of predicted human protein-coding genes using proteome-scale technologies.

Proper citation: Human Reference Protein Interactome Project (RRID:SCR_015670) Copy   

•   Source: SciCrunch Registry

https://github.com/davidaknowles/leafcutter/

Software tool for identifying and quantifying RNA splicing variation. Used to study sample and population variation in intron splicing. Identifies variable intron splicing events from short read RNA-seq data and finds alternative splicing events of high complexity. Used for detecting differential splicing between sample groups, and for mapping splicing quantitative trait loci (sQTLs).

Proper citation: LeafCutter (RRID:SCR_017639) Copy   

•   Source: SciCrunch Registry

https://github.com/zburkett/VoICE

Software that groups vocal elements of birdsong by creating a high dimensionality dataset through scoring spectral similarity between vocalizations.

Proper citation: Vocal Inventory Clustering Engine (VoICE) (RRID:SCR_016004) Copy   

•   Source: SciCrunch Registry