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Ratings or validation data are available for this resource

http://cbrain.mcgill.ca/loris

A modular and extensible web-based data management system that integrates all aspects of a multi-center study, from heterogeneous data acquisition to storage, processing and ultimately dissemination, within a streamlined platform. Through a standard web browser, users are able to perform a wide variety of tasks, such as data entry, 3D image visualization and data querying. LORIS also stores data independently from any image processing pipeline, such that data can be processed by external image analysis software tools. LORIS provides a secure web-based and database-driven infrastructure to automate the flow of clinical data for complex multi-site neuroimaging trials and studies providing researchers with the ability to easily store, link, and access significant quantities of both scalar (clinical, psychological, genomic) and multi-dimensional (imaging) data. LORIS can collect behavioral, neurological, and imaging data, including anatomical and functional 3D/4D MRI models, atlases and maps. LORIS also functions as a project monitoring and auditing platform to oversee data acquisition across multiple study sites. Confidentiality during multi-site data sharing is provided by the Subject Profile Management System, which can perform automatic removal of confidential personal information and multiple real-time quality control checks. Additionally, web interactions with the LORIS portal take place over an encrypted channel via SSL, ensuring data security. Additional features such as Double Data Entry and Statistics and Data Query GUI are included.

Proper citation: LORIS - Longitudinal Online Research and Imaging System (RRID:SCR_000590) Copy   

•   Source: SciCrunch Registry

http://becs.aalto.fi/en/research/bayes/drifter/

Model based Bayesian method for eliminating physiological noise from fMRI data. This algorithm uses image voxel analysis to isolate the cardiac and respiratory noise from the relevant data.

Proper citation: DRIFTER (RRID:SCR_014937) 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://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.fmridc.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 25, 2013 Public curated repository of peer reviewed fMRI studies and their underlying data. This Web-accessible database has data mining capabilities and the means to deliver requested data to the user (via Web, CD, or digital tape). Datasets available: 107 NOTE: The fMRIDC is down temporarily while it moves to a new home at UCLA. Check back again in late Jan 2013! The goal of the Center is to help speed the progress and the understanding of cognitive processes and the neural substrates that underlie them by: * Providing a publicly accessible repository of peer-reviewed fMRI studies. * Providing all data necessary to interpret, analyze, and replicate these fMRI studies. * Provide training for both the academic and professional communities. The Center will accept data from those researchers who are publishing fMRI imaging articles in peer-reviewed journals. The goal is to serve the entire fMRI community.

Proper citation: fMRI Data Center (RRID:SCR_007278) Copy   

•   Source: SciCrunch Registry

http://hendrix.imm.dtu.dk/software/lyngby/

Matlab toolbox for the analysis of functional neuroimages (PET, fMRI). The toolbox contains a number of models: FIR-filter, Lange-Zeger, K-means clustering among others, visualizations and reading of neuroimaging files.

Proper citation: Lyngby (RRID:SCR_007143) Copy   

•   Source: SciCrunch Registry

http://www.bmu.psychiatry.cam.ac.uk/software/

Suite of programs developed for fMRI analysis in a Virtual Pipeline Laboratory facilitates combining program modules from different software packages into processing pipelines to create analysis solutions which are not possible with a single software package alone. Current pipelines include fMRI analysis, statistical testing based on randomization methods and fractal spectral analysis. Pipelines are continually being added. The software is mostly written in C. This fMRI analysis package supports batch processing and comprises the following general functions at the first level of individual image analysis: movement correction (interpolation and regression), time series modeling, data resampling in the wavelet domain, hypothesis testing at voxel and cluster levels. Additionally, there is code for second level analysis - group and factorial or ANOVA mapping - after co-registration of voxel statistic maps from individual images in a standard space. The main point of difference from other fMRI analysis packages is the emphasis throughout on the use of data resampling (permutation or randomization) as a basis for inference on individual, group and factorial test statistics at voxel and cluster levels of resolution.

Proper citation: Cambridge Brain Activation (RRID:SCR_007109) Copy   

•   Source: SciCrunch Registry

http://sumsdb.wustl.edu/sums/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on May 11, 2016. Repository of brain-mapping data (surfaces and volumes; structural and functional data) derived from studies including fMRI and MRI from many laboratories, providing convenient access to a growing body of neuroimaging and related data. WebCaret is an online visualization tool for viewing SumsDB datasets. SumsDB includes: * data on cerebral cortex and cerebellar cortex * individual subject data and population data mapped to atlases * data from FreeSurfer and other brainmapping software besides Caret SumsDB provides multiple levels of data access and security: * Free (public) access (e.g., for data associated with published studies) * Data access restricted to collaborators in different laboratories * Owner-only access for work in progress Data can be downloaded from SumsDB as individual files or as bundles archived for offline visualization and analysis in Caret WebCaret provides online Caret-style visualization while circumventing software and data downloads. It is a server-side application running on a linux cluster at Washington University. WebCaret "scenes" facilitate rapid visualization of complex combinations of data Bi-directional links between online publications and WebCaret/SumsDB provide: * Links from figures in online journal article to corresponding scenes in WebCaret * Links from metadata in WebCaret directly to relevant online publications and figures

Proper citation: SumsDB (RRID:SCR_002759) Copy   

•   Source: SciCrunch Registry

Ratings or validation data are available for this resource

http://brainmap.org/

A community database of published functional and structural neuroimaging experiments with both metadata descriptions of experimental design and activation locations in the form of stereotactic coordinates (x,y,z) in Talairach or MNI space. BrainMap provides not only data for meta-analyses and data mining, but also distributes software and concepts for quantitative integration of neuroimaging data. The goal of BrainMap is to develop software and tools to share neuroimaging results and enable meta-analysis of studies of human brain function and structure in healthy and diseased subjects. It is a tool to rapidly retrieve and understand studies in specific research domains, such as language, memory, attention, reasoning, emotion, and perception, and to perform meta-analyses of like studies. Brainmap contains the following software: # Sleuth: database searches and Talairach coordinate plotting (this application requires a username and password) # GingerALE: performs meta-analyses via the activation likelihood estimation (ALE) method; also converts coordinates between MNI and Talairach spaces using icbm2tal # Scribe: database entry of published functional neuroimaging papers with coordinate results

Proper citation: brainmap.org (RRID:SCR_003069) 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

http://nipy.org

Community site to make brain imaging research easier that aims to build software that is clearly written, clearly explained, a good fit for the underlying ideas, and a natural home for collaboration.

Proper citation: Neuroimaging in Python (RRID:SCR_013141) Copy   

•   Source: SciCrunch Registry

http://brainandsociety.org/the-brain-observatory

Formerly a topical portal studying the brain which collected and imaged 1000 human brains, the Brain Observatory has partnered with the Institute for Brain and Society to build virtual laboratories that will feed directly into the database of images and knowledge created in the context of the Human Brain Library. The Brain Observatory will also host exhibits, conferences, and events aimed at promoting a heightened awareness of brain research and how its results can benefit personal brain fitness and mental health.

Proper citation: Brain Observatory (RRID:SCR_010641) Copy   

•   Source: SciCrunch Registry

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

A repository of schizophrenia neuroimaging data collected from over 450 individuals with schizophrenia, healthy controls and their respective siblings, most with 2-year longitudinal follow-up. The data include neuroimaging data, cognitive data, clinical data, and genetic data.

Proper citation: Northwestern University Schizophrenia Data and Software Tool (NUSDAST) (RRID:SCR_014153) 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://humanconnectome.org/connectome/connectomeDB.html

Data management platform that houses all data generated by the Human Connectome Project - image data, clinical evaluations, behavioral data and more. ConnectomeDB stores raw image data, as well as results of analysis and processing pipelines. Using the ConnectomeDB infrastructure, research centers will be also able to manage Connectome-like projects, including data upload and entry, quality control, processing pipelines, and data distribution. ConnectomeDB is designed to be a data-mining tool, that allows users to generate and test hypotheses based on groups of subjects. Using the ConnectomeDB interface, users can easily search, browse and filter large amounts of subject data, and download necessary files for many kinds of analysis. ConnectomeDB is designed to work seamlessly with Connectome Workbench, an interactive, multidimensional visualization platform designed specifically for handling connectivity data. De-identified data within ConnectomeDB is publicly accessible. Access to additional data may be available to qualified research investigators. ConnectomeDB is being hosted on a BlueArc storage platform housed at Washington University through the year 2020. This data platform is based on XNAT, an open-source image informatics software toolkit developed by the NRG at Washington University. ConnectomeDB itself is fully open source.

Proper citation: ConnectomeDB (RRID:SCR_004830) 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/odormapdb

OdorMapDB is designed to be a database to support the experimental analysis of the molecular and functional organization of the olfactory bulb and its basis for the perception of smell. It is primarily concerned with archiving, searching and analyzing maps of the olfactory bulb generated by different methods. The first aim is to facilitate comparison of activity patterns elicited by odor stimulation in the glomerular layer obtained by different methods in different species. It is further aimed at facilitating comparison of these maps with molecular maps of the projections of olfactory receptor neuron subsets to different glomeruli, especially for gene targeted animals and for antibody staining. The main maps archived here are based on original studies using 2-deoxyglucose and on current studies using high resolution fMRI in mouse and rat. Links are also provided to sites containing maps by other laboratories. OdorMapDB thus serves as a nodal point in a multilaboratory effort to construct consensus maps integrating data from different methodological approaches. OdorMapDB is integrated with two other databases in SenseLab: ORDB, a database of olfactory receptor genes and proteins, and OdorDB, a database of odor molecules that serve as ligands for the olfactory receptor proteins. The combined use of the three integrated databases allows the user to identify odor ligands that activate olfactory receptors that project to specific glomeruli that are involved in generating the odor activity maps.

Proper citation: Olfactory Bulb Odor Map DataBase (OdorMapDB) (RRID:SCR_007287) Copy   

•   Source: SciCrunch Registry

http://www.fz-juelich.de/ime/spm_anatomy_toolbox

A MATLAB toolbox which uses three dimensional probabilistic cytoarchitechtonic maps to correlate microscopic, anatomic and functional data of the cerebral cortex. Correlating the activation foci identified in functional imaging studies of the human brain with structural (e.g., cytoarchitectonic) information on the activated areas is a major methodological challenge for neuroscience research. We here present a new approach to make use of three-dimensional probabilistic cytoarchitectonic maps, as obtained from the analysis of human post-mortem brains, for correlating microscopical, anatomical and functional imaging data of the cerebral cortex. We introduce a new, MATLAB based toolbox for the SPM2 software package which enables the integration of probabilistic cytoarchitectonic maps and results of functional imaging studies. The toolbox includes the functionality for the construction of summary maps combining probability of several cortical areas by finding the most probable assignment of each voxel to one of these areas. Its main feature is to provide several measures defining the degree of correspondence between architectonic areas and functional foci. The software, together with the presently available probability maps, is available as open source software to the neuroimaging community. This new toolbox provides an easy-to-use tool for the integrated analysis of functional and anatomical data in a common reference space.

Proper citation: SPM Anatomy Toolbox (RRID:SCR_013273) Copy   

•   Source: SciCrunch Registry

http://tela.biostr.washington.edu/cgi-bin/repos/bmap_repo/main-menu.pl

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. An experiment management system for researchers studying language organization in the brain. Data from thirteen patients are available as a public demo. Language Map EMS

Proper citation: Language Map Experiment Management System (RRID:SCR_004562) 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