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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

http://www.pymvpa.org

A Python package intended to ease statistical learning analyses of large datasets. It offers an extensible framework with a high-level interface to a broad range of algorithms for classification, regression, feature selection, data import and export. While it is not limited to the neuroimaging domain, it is eminently suited for such datasets. PyMVPA is truly free software (in every respect) and additionally requires nothing but free-software to run. Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. This Python-based, cross-platform, open-source software toolbox software toolbox for the application of classifier-based analysis techniques to fMRI datasets makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine learning packages.

Proper citation: PyMVPA (RRID:SCR_006099) Copy   

•   Source: SciCrunch Registry

https://data.broadinstitute.org/alkesgroup/Eagle/

Software package for statistical estimation of haplotype phase either within a genotyped cohort or using a phased reference panel in large scale sequencing. The package includes Eagle1 (to harness identity-by-descent among distant relatives to rapidly call phase using a fast scoring approach) and Eagle2 (to analyze a full probabilistic model similar to the diploid Li-Stephens model used by previous HMM-based methods.

Proper citation: Eagle (RRID:SCR_015991) Copy   

•   Source: SciCrunch Registry

https://github.com/UMCU-RIBS/ALICE

Software tool for automatic localization of intra-cranial electrodes for clinical and high density grids. Software for coregistering high density ECoG grids to MRI anatomy.

Proper citation: ALICE (RRID:SCR_017463) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/lapdftext/

Software that facilitates accurate extraction of text from PDF files of research articles for use in text mining applications. It is intended for both scientists and natural language processing (NLP) engineers interested in getting access to text within specific sections of research articles. The system extracts text blocks from PDF-formatted full-text research articles and classifies them into logical units based on rules that characterize specific sections. The LA-PDFText system focuses only on the textual content of the research articles. The current version of LA-PDFText is a baseline system that extracts text using a three-stage process: * identification of blocks of contiguous text * classification of these blocks into rhetorical categories * extraction of the text from blocks grouped section-wise.

Proper citation: lapdftext (RRID:SCR_006167) Copy   

•   Source: SciCrunch Registry

http://pdsp.med.unc.edu/

This service provides screening of novel psychoactive compounds for pharmacological and functional activity at cloned human or rodent CNS receptors, channels, and transporters. Bryan Roth MD, PhD (University of North Carolina Chapel Hill) will perform pharmacological and functional screening of novel compounds as a contractor to NIMH. Screening of compounds is provided to qualified academic investigators at no cost. * Assays using for a large number of cloned human or rodent cDNAs for CNS receptors, channels and transporters. For a list of current receptors/transporters go to:clones.html * Ki determinations * Functional assays to determine effects on second messenger systems, channel activity and transporter function * Cloned receptors are also available at no cost to qualified investigators. * Assays are now available for bioavailability predictions (CaCo2, MDR-1) and cardiovascular toxicity predictions (HERG, 5-HT2B) Who is eligible * Academic investigators involved in basic or clinical research relevant to mental health. * Projects from research and development areas in small businesses relevant to mental and behavioral science. * Areas of interest to NIMH include the design and development of new chemical entities and small molecules as research tools, probes, targeted drug delivery systems, and PET ligands for brain imaging. * Research areas of interest are described in the Division of Basic and Clinical Neuroscience Research webpage, http://www.nimh.nih.gov/about/organization/dnbbs/index.shtml.

Proper citation: NIMH Psychoactive Drug Screening Program (RRID:SCR_005630) Copy   

•   Source: SciCrunch Registry

http://www.sri.com/biosciences/nimh/

The purpose of the NIMH Toxicological Evaluation of Novel Ligands Program is to accelerate the discovery, development, and application of novel ligands for PET, SPECT, and MRI imaging in humans by providing toxicology and safety assessment of promising, target-selective compounds. The program will also provide limited assessment of novel psychoactive agents for clinical research and as potential therapeutics. Toxicology and safety data generated by the program will be used to support an Investigational New Drug (IND) application to the Food and Drug Administration (FDA), or for Radioactive Drug Research Committee (RDRC) evaluation of a compound for human studies. The contract will evaluate toxicity and safety of compounds submitted for testing which may include, but are not limited to, novel chemical entities, structural analogs of compounds with an IND, or analogs of FDA-approved drugs. The services available under this program fall under four general phases: (1) analytical, (2) pharmacokinetics, (3) preliminary safety, and (4) IND-directed toxicity including safety pharmacology. What is available A broad range of tasks are available for assessing the safety and/or pharmacokinetics of each ligand. Specific capabilities available to investigators include: * Validation of the analytical methods for quantitating drug concentrations in dosing solutions, biological fluids, and tissues, as required. Determination of plasma drug levels in animals administered the agent under study, and calculation of pharmacokinetic parameters derived from these data. * Determination of bioavailability of the drug after different routes of administration, including oral, intravenous (i.v.), subcutaneous (s.c.), intramuscular (i.m.), or intraperitoneal (i.p.), as needed. Calculation of the pharmacokinetic parameters from the derived data. * In vitro evaluation of hepatotoxicity in human and animal liver cells. * Preclinical acute toxicity evaluations on lead compounds, evaluating clinical observations, body weights, clinical pathology, histopathology, and plasma drug levels in rodents and non-rodent species. Other toxicology endpoints may be selected if needed. * Subacute and subchronic toxicity evaluations in rodents and large animal species, evaluating clinical observations, body weights, clinical pathology, and histopathology. * Genotoxicity assessments using a battery of appropriate assays. Since these preclinical studies are needed to demonstrate to the FDA that a candidate medication or imaging agent is understood well enough for designing appropriate clinical treatment regimens, most of the work to be conducted to achieve these objectives must be performed and the resulting data analyzed and reported in strict compliance with the FDA''s GLP regulations for nonclinical laboratory studies (21 CFR 58). These data must be obtained by carefully planned and skillfully executed methods that are specific, accurate, and precise. The applicable portions of the accumulated safety data will be included in documents submitted to the FDA in support of regulatory applications. Who is eligible Academic investigators involved in basic or clinical research relevant to mental health. Research areas are described on the NIMH website.

Proper citation: NIMH Toxicological Screens of Novel Ligands (RRID:SCR_005631) Copy   

•   Source: SciCrunch Registry

http://www.mbl.org/mbl_main/atlas.html

High-resolution electronic atlases for mouse strains c57bl/6j, a/j, and dba/2j in either coronal or horizontal section. About this Atlas: The anterior-posterior coordinates are taken from an excellent print atlas of a C57BL/6J brain by K. Franklin and G. Paxinos (The Mouse Brain in Stereotaxic Coordinates, Academic Press, San Diego, 1997, ISBN Number 0-12-26607-6; Library of Congress: QL937.F72). The abbreviations we have used to label the sections conform to those in the Franklin-Paxinos atlas. A C57BL/6J mouse brain may contain as many as 75 million neurons, 23 million glial cells, 7 million endothelial cells associated with blood vessels, and 3 to 4 million miscellaneous pial, ependymal, and choroid plexus cells (see data analysis in Williams, 2000). We have not yet counted total cell number in DBA/2J mice, but the counts are probably appreciably lower.The brain and sections were all processed as described in our methods section. The enlarged images have a pixel count of 1865 x 1400 and the resolution is 4.5 microns/pixel for the processed sections.Plans: In the next several years we hope to add several additional atlases of the same sort for other strains of mice. A horizontal C57BL/6J atlas and a DBA/2J coronal atlas were completed by Tony Capra, summer 2000, and additional atlases may be made over the next several years. As describe in the MBL Procedures Section is not hard to make your own strain-specific atlas from the high resolution images in the MBL.

Proper citation: Mouse Brain Atlases (RRID:SCR_007127) Copy   

•   Source: SciCrunch Registry

http://www.nimh.nih.gov/about/director/index.shtml

Blog by the NIMH Director, Thomas R. Insel, M.D. Users may sort posts by topic and/or subsribe to the RSS Feed, http://www.nimh.nih.gov/site-info/feed-directors-blog.atom

Proper citation: NIMH Director's Blog (RRID:SCR_008841) Copy   

•   Source: SciCrunch Registry

https://portal.brain-map.org/atlases-and-data/bkp/abc-atlas

Provides platform for visualizing multimodal single cell data across mammalian brain and aims to empower researchers to explore and analyze multiple whole brain datasets simultaneously. Allen Institute and its collaborators continue to add new modalities, species, and insights to the ABC Atlas. Atlas as part of Brain Knowledge Platform will enable neuroscience community to identify more cell types in brain; Investigate spatial location of cell types; Investigate gene expression and co-expression patterns in cell types; Refine boundaries and knowledge of brain regions defined by gene expression.

Proper citation: Allen Brain Cell Atlas (RRID:SCR_024440) 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   

•   Source: SciCrunch Registry

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://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

http://casestudies.brain-map.org/celltax

Cellular Taxonomy of Mouse Visual Cortex by analyzing gene expression patterns at single cell level. Construction of cellular taxonomy of one cortical region, primary visual cortex, in adult mice done on basis of single cell RNA sequencing.

Proper citation: CellTax vignette (RRID:SCR_017000) Copy   

•   Source: SciCrunch Registry

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

Software tool for registering cortical surfaces. Capable of driving alignment using wide variety of descriptors of brain architecture, function and connectivity.

Proper citation: Multimodal Surface Matching (RRID:SCR_024929) Copy   

•   Source: SciCrunch Registry

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

Software model based segmentation and registration tool. Used for segmentation of sub-cortical structures. Introduces basic segmentation and vertex analysis for detecting group differences.

Proper citation: FMRIB’s Integrated Registration and Segmentation Tool (RRID:SCR_024921) Copy   

•   Source: SciCrunch Registry

https://github.com/calico/borzoi

Software package to access the Borzoi models, which are convolutional neural networks trained to predict RNA-seq coverage at 32bp resolution given 524kb input sequences.

Proper citation: Borzoi (RRID:SCR_026619) Copy   

•   Source: SciCrunch Registry