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http://vox.pharmacology.ucla.edu/home.html

Two-dimensional images of gene expression for 20,000 genes in a coronal slice of the mouse brain at the level of the striatum by using microarrays in combination with voxelation at a resolution of 1 cubic mm gene expression patterns in the brain obtained through voxelation. Voxelation employs high-throughput analysis of spatially registered voxels (cubes) to produce multiple volumetric maps of gene expression analogous to the images reconstructed in biomedical imaging systems.

Proper citation: Voxelation Map of Gene Expression in a Coronal Section of the Mouse Brain (RRID:SCR_008065) Copy   

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https://github.com/mne-tools/mne-bids/

Software Python package to link Brain Imaging Data Structure and MNE-Python software for analyzing neurophysiology data with goal to make analyses faster to code, more robust to errors, and easily shareable with colleagues. Provides programmable interface for BIDS datasets in electrophysiology with MNE-Python. Used for organizing electrophysiological data into BIDS format and facilitating their analysis.

Proper citation: MNE-BIDS (RRID:SCR_018766) Copy   

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

A native Java-based imaging processing environment similar to the ITK/VTK paradigm. Initially developed as an extension to MIPAV (CIT, NIH, Bethesda, MD), the JIST processing infrastructure provides automated GUI generation for application plug-ins, graphical layout tools, and command line interfaces. This repository maintains the current multi-institutional JIST development tree and is recommended for public use and extension. JIST was originally developed at IACL and MedIC (Johns Hopkins University) and is now also supported by MASI (Vanderbilt University).

Proper citation: JIST: Java Image Science Toolkit (RRID:SCR_008887) Copy   

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

Interactive Matlab toolbox for processing continuous and event-related EEG, MEG and other electrophysiological data incorporating independent component analysis (ICA), time/frequency analysis, artifact rejection, event-related statistics, and several useful modes of visualization of the averaged and single-trial data. First developed on Matlab 5.3 under Linux, EEGLAB runs on Matlab v5 and higher under Linux, Unix, Windows, and Mac OS X (Matlab 7+ recommended). EEGLAB provides an interactive graphic user interface (GUI) allowing users to flexibly and interactively process their high-density EEG and other dynamic brain data using independent component analysis (ICA) and/or time/frequency analysis (TFA), as well as standard averaging methods. EEGLAB also incorporates extensive tutorial and help windows, plus a command history function that eases users'' transition from GUI-based data exploration to building and running batch or custom data analysis scripts. EEGLAB offers a wealth of methods for visualizing and modeling event-related brain dynamics, both at the level of individual EEGLAB ''datasets'' and/or across a collection of datasets brought together in an EEGLAB ''studyset.'' For experienced Matlab users, EEGLAB offers a structured programming environment for storing, accessing, measuring, manipulating and visualizing event-related EEG data. For creative research programmers and methods developers, EEGLAB offers an extensible, open-source platform through which they can share new methods with the world research community by publishing EEGLAB ''plug-in'' functions that appear automatically in the EEGLAB menu of users who download them. For example, novel EEGLAB plug-ins might be built and released to ''pick peaks'' in ERP or time/frequency results, or to perform specialized import/export, data visualization, or inverse source modeling of EEG, MEG, and/or ECOG data. EEGLAB Features * Graphic user interface * Multiformat data importing * High-density data scrolling * Defined EEG data structure * Open source plug-in facility * Interactive plotting functions * Semi-automated artifact removal * ICA & time/frequency transforms * Many advanced plug-in toolboxes * Event & channel location handling * Forward/inverse head/source modeling

Proper citation: EEGLAB (RRID:SCR_007292) Copy   

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

3D DTI anatomical rat brain atlases have been created by the UNC- Chapel Hill Department of Psychiatry and the CAMID research collaboration. There are three age groups, postnatal day 5, postnatal day 14, and postnatal day 72. The subjects were Sprague-Dawley rats that were controls in a study on cocaine abuse and development. The P5 and P14 templates were made from scans of twenty rats each (ten female, ten male); the P72, from six females. The individual cases have been resampled to isotropic resolution, manually skull-stripped, and deformably registered via an unbiased atlas building method to create a template for each age group. Each template was then manually segmented using itk-SNAP software. Each atlas is made up of 3 files, a template image, a segmentation, and a label file.

Proper citation: 3D DTI Atlas of the Rat Brain In Postnatal Day 5 14 and Adulthood (RRID:SCR_009437) Copy   

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https://imagej.net/

Open source Java based image processing software program designed for scientific multidimensional images. ImageJ has been transformed to ImageJ2 application to improve data engine to be sufficient to analyze modern datasets.

Proper citation: ImageJ (RRID:SCR_003070) Copy   

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https://rmats.sourceforge.io

Software tool to detect differential alternative splicing events from RNA-Seq data. Calculates P-value and false discovery rate that difference in isoform ratio of gene between two conditions exceeds given user-defined threshold. From RNA-Seq data can automatically detect and analyze alternative splicing events corresponding to all major types of alternative splicing patterns. Handles replicate RNA-Seq data from both paired and unpaired study design.

Proper citation: rMATS (RRID:SCR_023485) Copy   

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http://www.nitrc.org/projects/mni2orfromxyz/

Input either normalized MNI coordinates from a 3D image, or input real world XYZ matrix coordinates, and this code will convert coordinates of one type to the other.

Proper citation: Convert MNI coordinates to or from XYZ (RRID:SCR_000406) Copy   

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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   

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http://www.tbi-impact.org/

Project focused on advancing knowledge of prognosis, trial design and treatment in Traumatic Brain Injury. IMPACT has developed and validated prognostic models for classification and characterization of TBI series, and participated in development of standardization of data collection in TBI studies.

Proper citation: IMPACT: International Mission for Prognosis and Analysis of Clinical Trials in TBI (RRID:SCR_000539) Copy   

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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   

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http://rsb.info.nih.gov/

Portal for NIH, NIMH, and NINDS scientific and computer resources including Mac sites, PC sites, Linux sites, intramural programs, intranet and the NIH JumpStart and Directory.

Proper citation: Research Services Branch National Institutes of Mental Health (RRID:SCR_001633) Copy   

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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   

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

Atlas of segmented and normalized high-resolution postmortem MRI of the human hippocampus. Additional data (raw images) is available through the SCM link. It requires knowing how to use CVS.

Proper citation: Penn Hippocampus Atlas (RRID:SCR_000421) Copy   

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http://neurosurgery.ucsf.edu/index.php/research_tissue_bank.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 4th,2023. Brain Tumor Research Center Tissue Bank began collecting tissue in 1978 and has established an organized repository of characterized tissues--frozen, paraffin-embedded, blood and cultures--that are maintained in a manner useful for a wide range of studies. Samples are collected only from patients who have agreed to have their tissues banked and used for future research. Consent documents are maintained in a secure area and associated clinical data are held in a double-password protected computer database. Each sample received into the Tissue Bank is non-identifying number. No protected health information (PHI) is released. To obtain samples, investigators submit a request form to the Manager. The request form requires an explanation of the tissue requested (type, number of samples, justification), description of the study, CHR approval (see new policy regarding human vs. non-human research) and Project Leader authorization. The Manager reviews each request for feasibility before presentation to the Scientific Core Committee. The UCSF Neurosurgery Tissue Bank makes its inventory of stock cell lines available to all investigators. Requested cells are grown in T-25 flasks and shipped FedEx Priority Overnight at the receipient's expense. However, if you prefer, we can ship the frozen cells, packed in dry ice. (Note: some countries restrict dry ice shipments.)

Proper citation: UCSF Brain Tumor Tissue Bank (RRID:SCR_000647) Copy   

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http://med.emory.edu/ADRC/research/tissue_biospecimen_banking_facility.html

The Alzheimer's Disease Research Center at Emery University maintains an active brain bank to facilitate the acquisition, storage, handling and distribution of well-characterized autopsy brain tissue and other materials to investigators. It contains frozen tissue and brain specimens, formalin fixed tissue, paraformaldehyde fixed tissue, and cryopreserved tissue. The ADRC also has access to tissues and samples related to other neurodegenerative diseases. It contains plasma samples, serum samples, lymphoblast cell lines, and cerebrospinal fluid.

Proper citation: Emory ADRC Tissue and Biospecimen Banking Facility (RRID:SCR_000551) Copy   

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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   

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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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https://bwhbioinfo.shinyapps.io/powerEQTL/

Software R package and shiny application for sample size and power calculation of bulk tissue and single-cell eQTL analysis.

Proper citation: powereQTL (RRID:SCR_021653) Copy   

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https://github.com/denisecailab/minian

Software miniscope analysis pipeline that requires low memory and computational demand so it can be run without specialized hardware. Offers interactive visualization that allows users to see how parameters in each step of pipeline affect output.

Proper citation: Minian (RRID:SCR_022601) Copy   

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