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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   

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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   

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http://www.nimh.nih.gov/educational-resources/neuroscience-and-psychiatry/neuroscience-and-psychiatry-module-1-translating-neural-circuits-into-novel-therapeutics.shtml

This is the first in a series of modules on neuroscience and psychiatry. This module explores research on cognitive deficits, a core feature of schizophrenia and the single best predictor of functional outcomes in this disorder for which we currently have no treatments. This module is an example of how translational neuroscience can provide clues for the development of promising novel therapeutics.

Proper citation: Neuroscience and Psychiatry Module 1: Translating Neural Circuits into Novel Therapeutics (RRID:SCR_005609) Copy   

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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   

•   Source: SciCrunch Registry

https://zenodo.org/records/11095105

Software label transfer tool for single-cell RNA sequencing analysis. Scalable, Interpretable Modeling for Single-cell RNA-seq data classification.

Proper citation: SIMS (RRID:SCR_025787) Copy   

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http://www.nimh.nih.gov/research-priorities/rdoc/index.shtml

NIMH Strategic Plan developing, for research purposes, new ways of classifying psychopathology based on dimensions of observable behavior and neurobiological measures. In brief, the effort is to define basic dimensions of functioning (such as fear circuitry or working memory) to be studied across multiple units of analysis, from genes to neural circuits to behaviors, cutting across disorders as traditionally defined. The intent is to translate rapid progress in basic neurobiological and behavioral research to an improved integrative understanding of psychopathology and the development of new and/or optimally matched treatments for mental disorders. The various domains of functioning, and their constituent elements, are being defined by an ongoing series of consensus workshops; input from the research community and other interested stakeholders is encouraged.

Proper citation: RDoC (RRID:SCR_002244) Copy   

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http://cogpo.org

Ontology used to describe the experimental conditions within cognitive and behavioral experiments, primarily in humans for application and use in the functional neuroimaging community. CogPO has been developed through the integration of the Functional Imaging Biomedical Informatics Research Network (FBIRN) Human Imaging Database (HID) and the BrainMap Database. The design of CogPO concentrates on what can be observed directly: categorization of each paradigm in terms of (1) the stimulus presented to the subjects, (2) the requested instructions, and (3) the returned response.

Proper citation: Cognitive Paradigm Ontology (RRID:SCR_002235) Copy   

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http://www.schizophreniaforum.org/

The mission of the SRF is to help in the search for causes, treatments, and understanding of the devastating disease of schizophrenia. Our goal is to foster collaboration among researchers by providing an international online forum where ideas, research news, and data can be presented and discussed. The website is intended to bring together scientists working specifically on schizophrenia, scientists researching related diseases, and basic scientists whose work can shed light on these diseases. In this way, we hope that the Schizophrenia Research Forum will be a catalyst for creative thinking in the quest to understand a deeply complex disease. It is our goal to create and maintain up-to-date content of the highest quality. The website is free of charge to users, independent of industry sponsorship, and open to the public. Though geared toward researchers, we welcome other visitorspeople with mental illnesses, families, the media, and others who need accurate information on research into schizophrenia. We do, however, require that users who wish to post comments and other materials be registered members. All such materials are subject to approval by the editorial team. As a forum, we encourage participation and welcome feedback from the community.

Proper citation: Schizophrenia Research Forum (RRID:SCR_002899) Copy   

•   Source: SciCrunch Registry

http://rsb.info.nih.gov/nih-image/index.html

Public image processing and analysis program for Macintosh.

Proper citation: NIH Image (RRID:SCR_003073) Copy   

•   Source: SciCrunch Registry

https://neurobiobank.nih.gov/

National resource for investigators utilizing human post-mortem brain tissue and related biospecimens for their research to understand conditions of the nervous system. Federated network of brain and tissue repositories in the United States that collects, evaluates, stores, and makes available to researchers, brain and other tissues in a way that is consistent with the highest ethical and research standards. The NeuroBioBank ensures protection of the privacy and wishes of donors. Provides information to the public about the need for tissue donation and how to register as a donor.

Proper citation: NIH NeuroBioBank (RRID:SCR_003131) Copy   

•   Source: SciCrunch Registry

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

As part of BMAP gene discovery efforts, mouse brain cDNA libraries and Expressed Sequence Tags (ESTs) have been generated. Through this project a BMAP mouse brain UniGene set consisting of over 24,000 non-redundant members of unique clusters has been developed from EST sequencing of more than 50,000 cDNA clones from 10 regions of adult mouse brain, spinal cord, and retina (http://brainEST.eng.uiowa.edu/). In 2001, NIMH along with NICHD, NIDDK, and NIDA, awarded a contract to the University of Iowa ( M.B. Soares, PI) to isolate full-length cDNA clones corresponding to genes expressed in the developing mouse nervous system and determine their full-coding sequences. The BMAP mouse brain EST sequences can be accessed at NCBI's dbEST database (http://www.ncbi.nlm.nih.gov/dbEST/). Arrayed sets of BMAP mouse brain UniGenes and cDNA libraries, and individual BMAP cDNA clones can be purchased from Open Biosystems, Huntsville, AL (http://www.openbiosystems.com

Proper citation: BMAP cDNA Resources (RRID:SCR_002973) Copy   

•   Source: SciCrunch Registry

https://bioimagesuiteweb.github.io/webapp/index.html

Web applications for analysis of multimodal/multispecies neuroimaging data. Image analysis software package. Has facilities for DTI and fMRI processing. Capabilities for both neuro/cardiac and abdominal image analysis and visualization. Many packages are extensible, and provide functionality for image visualization and registration, surface editing, cardiac 4D multi-slice editing, diffusion tensor image processing, mouse segmentation and registration, and much more. Can be intergrated with other biomedical image processing software, such as FSL, AFNI, and SPM.

Proper citation: BioImage Suite (RRID:SCR_002986) 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://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

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://github.com/YosefLab/FastProject

Software Python tool for low dimensional analysis of single-cell RNA-Seq data. Software package for two dimensional visualization of single cell data. Analyzes gene expression matrix and produces output report in which two-dimensional of data can be explored.

Proper citation: FastProject (RRID:SCR_017462) Copy   

•   Source: SciCrunch Registry

https://github.com/epurdom/clusterExperiment

Software open source R package for executing, evaluating and visualizing different clusterings of experimental data, including data from single cell RNA-Seq studies. Software for running and comparing different clusterings of single cell sequencing data.

Proper citation: clusterExperiment (RRID:SCR_017439) Copy   

•   Source: SciCrunch Registry

http://neuroproteomics.scs.illinois.edu/microMS.htm

Software Python platform for image guided Mass Spectrometry profiling. Provides graphical user interface for automatic cell finding and point based registration from whole slide images. Simplifies single cell analysis with feature rich image processing.

Proper citation: microMS (RRID:SCR_017443) Copy   

•   Source: SciCrunch Registry

https://www.ncbi.nlm.nih.gov/pubmed/28653482

Software tool to facilitate tractography based deep brain stimulation (DBS) electrode targeting within patient specific stereotactic coordinate system used in operating room.

Proper citation: StimVision (RRID:SCR_017457) Copy   

•   Source: SciCrunch Registry