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http://www.connectomeviewer.org/viewer/

A free, open source, cross-platform Python-based software application for visualization and analysis in connectome research. Features of the software include: Connectome File Format including metadata, networks, surfaces, volumes, track files; complex network analysis toolboxes; modular plugin architecture for extensibility; Mayavi2 for 3D Scientific Visualization and Plotting; interactive data manipulation and scripting capabilities; and Neuroimaging and Diffusion in Python libraries.

Proper citation: Connectome Viewer (RRID:SCR_009552) Copy   

•   Source: SciCrunch Registry

https://www.conn-toolbox.org

Matlab based cross platform software package for computation, display, and analysis of functional connectivity in fMRI (fcMRI). Used for resting state data (rsfMRI) as well as task related designs. Covers pipeline from raw fMRI data to hypothesis testing.

Proper citation: CONN (RRID:SCR_009550) Copy   

•   Source: SciCrunch Registry

http://cbfbirn.ucsd.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented August 23, 2017.

A web based central repository for individual and group analysis of Arterial Spin Labeling (ASL) data sets and ASL pulse sequences developed at CMFRI UCSD for MRI researchers. This resource currently hosts more 1300 ASL data sets from 22 projects and consists of mainly two main tools 1) The Cerebral Blood Flow Database and Analysis Pipeline (CBFDAP) is a web enabled data and workflow management system extended from the HID codebase on NITRC specialized for Arterial Spin Labeling data management and analysis (including group analysis) in a centralized manner. 2) Pulse Sequence Distribution System (PSDS) for managing dissamination of ASL pulse sequences developed at the UCSD CFMRI. This resource also includes web and video tutorials for end users.

Proper citation: CBFBIRN (RRID:SCR_009543) Copy   

•   Source: SciCrunch Registry

http://www.ant-neuro.com/products/asa

A highly flexible EEG/ERP and MEG analysis package with a variety of source reconstruction, signal analysis and MRI processing features. ASA combines functional brain imaging with the visualization and incorporation of morphological information obtained from MRI or CT. ASA is a highly interactive and flexible software tool that can be applied to neuro-physiological and clinical brain research. ASA gives a realistic impression of your experimental configuration together with topographical mapping of EEG and MEG and the results of your analysis. ASA is developed for and by people dedicated to brain research. The concept of flexibility and openness covers even most complex analysis demands. The ASA environment is particularly attractive for those that wish to develop their own methods in third party packages like Matlab and use ASA for pre-processing and visualization purposes.

Proper citation: ASA - Advanced Source Analysis (RRID:SCR_012867) Copy   

•   Source: SciCrunch Registry

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

Graphical user interface that has been implemented as a 3D Slicer plugin (scripted module). It serves to display a corresponding set of cortical regions from functional connectivity matrix in an explorable 3D scene that represents brain anatomical environment. In addition to grey matter regions, MultiXplore automatically finds and extracts deterministic fiber bundles which exist between selected region(s) and adds them to the 3D environment. This feature helps in generating region-based fiber bundles given a desired whole-brain tractography data.

Proper citation: MultiXplore (RRID:SCR_014814) Copy   

•   Source: SciCrunch Registry

https://www.nitrc.org/projects/atpp

Integrated pipeline for tractography-based brain parcellation with automatic processing and massive parallel computing. ATPP offers a CLI version for parcellating multiple brain regions and a GUI version for parcellating a specific brain region. " ATPP completely follows the scientific cultural shift to open science, which aims at making scientific research including journal papers, lab notes, data, and, of course, workflow tools, accessible and transparent to all levels of society. ATPP is publicly accessible in Neuroimaging Informatics Tools and Resources Clearinghouse8 (NITRC) (https://www.nitrc.org/projects/atpp). Its source codes are hosted in GitHub9 (https://github.com/haililihai/ATPP_CLI; https://github.com/haililihai/ATPP_GUI), under the GNU generic purpose license version 310 (GPLv3), and are welcome to download and fork. The Digital Object Identifiers (DOIs) providing a persistent way to make digital data easily and uniquely citable was created from Zenodo11 platform with those GitHub repositories (ATPP CLI v2.0.0, doi: https://doi.org/10.5281/zenodo.239702; ATPP GUI v2.0.0, doi: https://doi.org/10.5281/zenodo.239705). "

Proper citation: Automatic Tractography-based Parcellation Pipeline (RRID:SCR_014815) Copy   

•   Source: SciCrunch Registry

http://fcon_1000.projects.nitrc.org/indi/CoRR/html/

Consortium that has aggregated resting state fMRI (R-fMRI) and diffusion imaging data from laboratories around the world, creating an open science resource for the imaging community, that facilitates the assessment of test-retest reliability and reproducibility for functional and structural connectomics. Given that this was a retrospective data collection, they have focused on basic phenotypic measures that are relatively standard in the neuroimaging field, as well as fundamental for analyses and sample characterization. Their phenotypic key is organized to reflect three classifications of variables: 1) core (i.e., minimal variables required to characterize any dataset), 2) preferred (i.e., variables that were strongly suggested for inclusion due to their relative import and/or likelihood of being collected by most sites), and 3) optional (variables that are data-set specific or only shared by a few sites). CoRR includes 33 datasets consisting of: * 1629 Subjects * 3357 Anatomical Scans * 5093 Resting Functional Scans * 1302 Diffusion Scans * 300 CBF and ASL Scans

Proper citation: Consortium for Reliability and Reproducibility (RRID:SCR_003774) Copy   

•   Source: SciCrunch Registry

http://www.humanconnectomeproject.org/

A multi-center project comprising two distinct consortia (Mass. Gen. Hosp. and USC; and Wash. U. and the U. of Minn.) seeking to map white matter fiber pathways in the human brain using leading edge neuroimaging methods, genomics, architectonics, mathematical approaches, informatics, and interactive visualization. The mapping of the complete structural and functional neural connections in vivo within and across individuals provides unparalleled compilation of neural data, an interface to graphically navigate this data and the opportunity to achieve conclusions about the living human brain. The HCP is being developed to employ advanced neuroimaging methods, and to construct an extensive informatics infrastructure to link these data and connectivity models to detailed phenomic and genomic data, building upon existing multidisciplinary and collaborative efforts currently underway. Working with other HCP partners based at Washington University in St. Louis they will provide rich data, essential imaging protocols, and sophisticated connectivity analysis tools for the neuroscience community. This project is working to achieve the following: 1) develop sophisticated tools to process high-angular diffusion (HARDI) and diffusion spectrum imaging (DSI) from normal individuals to provide the foundation for the detailed mapping of the human connectome; 2) optimize advanced high-field imaging technologies and neurocognitive tests to map the human connectome; 3) collect connectomic, behavioral, and genotype data using optimized methods in a representative sample of normal subjects; 4) design and deploy a robust, web-based informatics infrastructure, 5) develop and disseminate data acquisition and analysis, educational, and training outreach materials.

Proper citation: MGH-USC Human Connectome Project (RRID:SCR_003490) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/ir/

Data repository for neuroimaging data in DlCOM and NIFTI formats. It allows users to search for and freely download publicly available data sets relating to normal subjects and those with diagnoses such as: schizophrenia, ADHD, autism, and Parkinson's disease.XNAT-based image registry that supports both NIfTI and DICOM images to promote re-use and integration of NIH funded data.

Proper citation: NITRC-IR (RRID:SCR_004162) Copy   

•   Source: SciCrunch Registry

https://nda.nih.gov/

The National Institute of Mental Health Data Archive (NDA) makes available human subjects data collected from hundreds of research projects across many scientific domains. Research data repository for data sharing and collaboration among investigators. Used to accelerate scientific discovery through data sharing across all of mental health and other research communities, data harmonization and reporting of research results. Infrastructure created by National Database for Autism Research (NDAR), Research Domain Criteria Database (RDoCdb), National Database for Clinical Trials related to Mental Illness (NDCT), and NIH Pediatric MRI Repository (PedsMRI).

Proper citation: NIMH Data Archive (RRID:SCR_004434) Copy   

•   Source: SciCrunch Registry

https://www.fieldtriptoolbox.org

Software toolbox for analysis of MEG, EEG, and other electrophysiological data. Used by experimental neuroscientists.

Proper citation: FieldTrip (RRID:SCR_004849) Copy   

•   Source: SciCrunch Registry

http://trackvis.org/

TrackVis is software tool that can visualize and analyze fiber track data from diffusion MR imaging (DTI/DSI/HARDI/Q-Ball) tractography. It does NOT perform actual fiber tracking. Diffusion Toolkit is a set of tools that reconstruct diffusion imaging data and generate fiber track data for TrackVis to visualize. Because these two sets of tools were developed and maintained separately and each has distinguished funtionalities, they decided to distribute them as two separate programs for the ease of maintenance and upgrade. You do need both of them to perform complete diffusion data processing and analysis. Features of TrackVis include: * Cross-platform. Works on Windows, Mac OS X and Linux with native look and feel. * A variety of track filters (track selecting methods) allowing users to explore and locate specific bundles with ease. * Multiple rendering modes with customizable scalar-driven color codes. * Real-time parameter adjustment and 3D render. * Open format of the track data file allowing users to integrate customized scalar data into the track file and visualize and analyze it. Save and restore scenes in XML style scene file. * Statistical scalar analysis of tracks and ROIs. * Synchronized real-time multiple dataset analysis and display allowing time-point and/or subject comparison. Synchronized analysis and display on same dataset can also be performed in real-time remotely over the network. * Upfront in-line parameter adjustment in real-time. No tedious pop-up dialogs. TrackVis works with Track File created by Diffusion Toolkit. Diffusion Toolkit processes raw DICOM, Nifti format and ANALYZE images. TrackVis and Diffusion Toolkit are cross-platform software. They can run on Windows XP, Mac OS X as well as Linux.

Proper citation: TrackVis (RRID:SCR_004817) Copy   

•   Source: SciCrunch Registry

http://neuromorphometrics.com

Neuromorphometrics provides brain labeling and measurement services. Given raw MRI brain scans, we make precise quantitative measurements of the volume, shape, and location of specific neuroanatomical structures. Web tool for brain measurement services. Used for modeling living human brain and make quantitative measurements of volume, shape, and location of specific neuroanatomical structures using given MRI brain scans. Automated analyses are manually guided, inspected and certified by a neuroanatomical expert. Resource of neuroanatomically labeled MRI brain scans database. Resource for neuroanatomical localization and identification: NeuAtlas.

Proper citation: Neuromorphometrics (RRID:SCR_005656) Copy   

•   Source: SciCrunch Registry

http://enigma.ini.usc.edu/

Network that brings together researchers in imaging genomics, to understand brain structure and function, based on MRI, DTI, fMRI and genomewide association scan (GWAS) data. The ENIGMA Network has several goals: * to create a network of like-minded individuals, interested in pushing forward the field of imaging genetics * to ensure promising findings are replicated via member collaborations, in order to satisfy the mandates of most journals * to share ideas, algorithms, data, and information on promising findings or methods * to facilitate training, including workshops and conferences on key methods and emerging directions in imaging genetics. Data sharing with other members of the ENIGMA Network is optional and by no means a requirement of joining the network. Genetics and Imaging Protocols are available.

Proper citation: ENIGMA: Enhancing Neuro Imaging Genetics Through Meta-Analysis (RRID:SCR_005515) Copy   

•   Source: SciCrunch Registry

http://pubbrain.org/

A literature search and visualization tool that allows end users to enter any PubMed query and see that query rendered as a heatmap illustrating which regions of interest are most commonly mentioned within the search results. To use PubBrain, simply enter any valid PubMed search in the search box.

Proper citation: PubBrain (RRID:SCR_005387) Copy   

•   Source: SciCrunch Registry

http://www.neurobureau.org/

A neuroscience collaboratory that supports open neuroscience, which basically encompasses the unrestricted sharing of: analytic tools, computational resources, data, and knowledge. Its goal is to establish a spirit and forum for open neuroscience, and to facilitate the translation of that ethos into action by conducting successful large open interdisciplinary collaborative efforts such as releasing the preprocessed version of the ADHD-200 competition dataset. The Brain-Art Competition is likewise an effort to bring attention to the more aesthetically-oriented aspects of their field, and to publicize and encourage creative developments taking place at the nexus of art and neuroimaging.

Proper citation: Neuro Bureau (RRID:SCR_005357) Copy   

•   Source: SciCrunch Registry

http://afni.nimh.nih.gov/afni/

Set of (mostly) C programs that run on X11+Unix-based platforms (Linux, Mac OS X, Solaris, etc.) for processing, analyzing, and displaying functional MRI (FMRI) data defined over 3D volumes and over 2D cortical surface meshes. AFNI is freely distributed as source code plus some precompiled binaries.

Proper citation: Analysis of Functional NeuroImages (RRID:SCR_005927) Copy   

•   Source: SciCrunch Registry

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

EPI-images of 25 participants gathered during rest as well as anonymized anatomical images of the same participants. The resting-state fMRI images were collected on several occasions: # the first resting-state scan in a scan session # 5-11 months after the first resting-state scan # about 30 (< 45) minutes after 2. Each scan occasion is released as a new version release of the resource. ---Caution: Participants here are part of the NewYork_a contribution to the 1000 Functional Connectomes Project. DO NOT combine datasets.

Proper citation: NYU CSC TestRetest (RRID:SCR_005975) Copy   

•   Source: SciCrunch Registry

http://martinos.org/mne/

Software suite for processing magnetoencephalography and electroencephalography data. Open source Python software for exploring, visualizing, and analyzing human neurophysiological data including MEG, EEG, sEEG, ECoG . Implements all functionality of MNE Matlab tools in Python and extends capabilities of MNE Matlab tools to, e.g., frequency-domain and time-frequency analyses and non-parametric statistics.

Proper citation: MNE software (RRID:SCR_005972) Copy   

•   Source: SciCrunch Registry

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

ART ''''acpcdetect'''' program for automatic detection of the AC and PC landmarks and the mid-sagittal plane on 3D structural MRI scans. ART ''''brainwash'''' program for automatic multi-atlas skull-stripping of 3D structural MRI scans. ART ''''3dwarper'''' program of non-linear inter-subject registration of 3D structural MRI scans. Software (art2) for linear rigid-body intra-subject inter-modality (MRI-PET) image registration. Data resource: The ART projects makes available corpus callosum segmentations of 316 normal subjects from the OASIS cross-sectional database. ART ''''yuki'''' program for fast, robust, and fully automatic segmentation of the corpus callosum on 3D structural MRI scans.

Proper citation: Automatic Registration Toolbox (RRID:SCR_005993) Copy   

•   Source: SciCrunch Registry