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http://www.bri.ucla.edu/research/resources

Brain bank resources which include postmortem human frozen brain tissue and matched cerebrospinal fluid (CSF) and blood available for scientists to search for etiopathogeneses of human disease. The National Neurological Research Specimen Bank and the Multiple Sclerosis Human Neurospecimen Bank maintains a collection of quick frozen and formalin fixed postmortem human brain tissue and frozen cerebrospinal fluid from patients with neurological diseases, including Alzheimer's Disease, amyotrophic lateral sclerosis, depressive disorder/suicide, and epilepsy, among others. Diagnoses are documented by clinical medical records and gross/microscopic neuropathology. The Neuropathology Laboratory at the UCLA Medical Center maintains a bank of frozen, formalin and paraformaldehyde-fixed and paraffin-embedded postmortem human brain tissues and frozen cerebrospinal fluid (CSF) from patients who die with Alzheimer's disease and other dementing and degenerative illnesses, as well as control materials removed in a similar fashion from patients who are neurologically normal.

Proper citation: Brain Research Institute Biobank Resources (RRID:SCR_008756) Copy   

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https://www.humanconnectome.org/software/connectome-workbench

Software brain visualization, analysis and discovery tool for fMRI and dMRI brain imaging data, including functional and structural connectivity data generated by the Human Connectome Project. Used to map brain imaging data. Allows for visualization of outputs from HCP pipelines from single subject, or average data from group of subjects and register that data onto standard brain atlas.

Proper citation: Connectome Workbench (RRID:SCR_008750) Copy   

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http://humanconnectome.org/

Consortium to comprehensively map long-distance brain connections and their variability. It is acquiring data and developing analysis pipelines for several modalities of neuroimaging data plus behavioral and genetic data from healthy adults.

Proper citation: Human Connectome Coordination Facility (RRID:SCR_008749) Copy   

•   Source: SciCrunch Registry

http://www.nimh.nih.gov/educational-resources/neuroscience-and-psychiatry/neuroscience-and-psychiatry-module-2-fear-safety-anxiety-and-anxiety-disorders.shtml

This is the second in a series of modules on neuroscience and psychiatry. This module describes neuroscience research on animal models of fear that informed human studies of fear/safety, anxiety and anxiety disorders. This model helps shed light on the symptoms of PTSD and lead to the development of a novel treatment that has been successful in research studies for several anxiety disorders.

Proper citation: Neuroscience and Psychiatry Module 2: Fear/Safety Anxiety and Anxiety Disorders (RRID:SCR_008843) Copy   

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http://www.nimh.nih.gov/funding/clinical-trials-for-researchers/practical/tordia/treatment-of-ssri-resistant-depression-in-adolescents-tordia.shtml

A multi-site, clinical research study examining treatment options for teens whose depression has not improved after one adequate trial of a selective serotonin reuptake inhibitor (SSRI), a type of antidepressant. The purpose of the study is to determine how best to treat adolescents with depression that is resistant to the first SSRI antidepressant they have tried. Participants receive one of three other antidepressant medications, either alone or in combination with cognitive behavioral therapy. The TORDIA study aims to develop useful clinical guidelines for the care and management of adolescent depression. Adolescents ages 12 to 18, currently taking a prescribed selective serotonin reuptake inhibitor (SSRI) and still experiencing depression, participate in a 12-week randomized treatment study that includes one of four conditions: (1) switching to an alternative SSRI, (2) switching to a different non-SSRI antidepressant, (3) switching to an alternative SSRI and receiving cognitive behavioral therapy (CBT), or (4) switching to a different non-SSRI antidepressant and receiving CBT. This is a double-blind study, which means that neither the participant nor the clinical staff will know which of the three possible medications has been assigned. Participants who respond to the assigned treatment will receive 12 additional weeks of the same treatment. Those who do not appear to be getting better will be offered 12 weeks of an alternative, individualized treatment plan based on each participant''s particular needs. All participants will receive follow-up psychiatric evaluations for 12 months after the 12-week continuation phase of the study, regardless of treatment adherence. For more information visit, http://www.clinicaltrials.gov/ct2/show/NCT00018902?term=clinical+trial+AND+treatment+of+ssri-resistant+AND+depression+AND+TORDIA+AND+study&rank=1

Proper citation: Treatment of SSRI-resistant Depression in Adolescents (TORDIA) (RRID:SCR_008831) Copy   

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

The Brain Molecular Anatomy Project is a trans-NIH project aimed at understanding gene expression and function in the nervous system. BMAP has two major scientific goals: # Gene discovery: to catalog of all the genes expressed in the nervous system, under both normal and abnormal conditions. # Gene expression analysis: to monitor gene expression patterns in the nervous system as a function of cell type, anatomical location, developmental stage, and physiological state, and thus gain insight into gene function. In pursuit of these goals, BMAP has launched several initiatives to provide resources and funding opportunities for the scientific community. These include several Requests for Applications and Requests for Proposals, descriptions of which can be found in this Web site. BMAP is also in the process of establishing physical and electronic resources for the community, including repositories of cDNA clones for nervous system genes, and databases of gene expression information for the nervous system. Most of the BMAP initiatives so far have focused on the mouse as a model species because of the ease of experimental and genetic manipulation of this organism, and because many models of human disease are available in the mouse. However, research in humans, other mammalian species, non-mammalian vertebrates, and invertebrates is also being funded through BMAP. For the convenience of interested investigators, we have established this Web site as a central information resource, focusing on major NIH-sponsored funding opportunities, initiatives, genomic resources available to the research community, courses and scientific meetings related to BMAP initiatives, and selected reports and publications. When appropriate, we will also post initiatives not directly sponsored by BMAP, but which are deemed relevant to its goals. Posting decisions are made by the Trans-NIH BMAP Committee

Proper citation: BMAP - Brain Molecular Anatomy Project (RRID:SCR_008852) Copy   

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http://erpinfo.org/erplab

A set of open source, freely available Matlab routines for analyzing Event Related Potential (ERP) data. It is tightly integrated with the EEGLAB Toolbox. ERPLAB routines can be accessed from the Matlab command window and from Matlab scripts in addition to being accessed from the EEGLAB GUI. Consequently, ERPLAB provides the ease of learning of a GUI-based system but also provides the power and flexibility of a scripted system.The development of ERPLAB Toolbox is being coordinated by Steve Luck and Javier Lopez-Calderon at the UC-Davis Center for Mind & Brain, with financial support from NIMH.

Proper citation: ERPLAB (RRID:SCR_009574) Copy   

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https://github.com/BRAINSia/BRAINSTools/tree/master/BRAINSDemonWarp

A command line program for image registration by using different methods including Thirion and diffeomorphic demons algorithms. The function takes in a template image and a target image along with other optional parameters and registers the template image onto the target image. The resultant deformation fields and metric values can be written to a file. The program uses the Insight Toolkit (www.ITK.org) for all the computations, and can operate on any of the image types supported by that library. This a an ITK based implementation of various forms of Thirion Demons based registration (including diffeomorphic demons registration originating from Tom Vercauteren at INRIA ).

Proper citation: BRAINSDemonWarp (RRID:SCR_009524) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

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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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://portal.brain-map.org/explore/classes/nomenclature

Framework for creating brain cell type nomenclature, and include examples using published datasets. System allows designation of cell types with or without hierarchical organization. Nomenclature convention initially applied to brain cells and types, is intended to encompass existing naming strategies used in publications across diverse research teams. Allows tracking of many different taxonomies, including those from different organ systems or across diverse areas of bioscience.

Proper citation: Common Cell Type Nomenclature (RRID:SCR_021124) Copy   

•   Source: SciCrunch Registry

https://palamaralab.github.io/software/argon/

Software tool as fast simulator of genetic data that samples from Discrete Time Wright Fisher process backwards in time. Used to simulate long chromosomes and large samples under DTWF, with computational time comparable to recent coalescent simulators.

Proper citation: ARGON (RRID:SCR_021635) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://CRAN.R-project.org/package=TrumpetPlots

Software R package to visualize relationship between allele frequency and effect size in genetic association studies.

Proper citation: TrumpetPlots (RRID:SCR_023742) Copy   

•   Source: SciCrunch Registry