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

An international working group dedicated to improving access to neuroimaging results in a free and open-access manner. It seeks to establish a universal coordinate database, including both past papers and future studies. Their current project involves the creation of a comprehensive database of neuroimaging results searchable based on standardized coordinates. Once complete, this will allow anyone to find all of the articles that report a coordinate, or set of coordinates, easily and without cost. Eventually, they hope to expand this database to include not only coordinates, but statistical parametric maps as well. Formation of such a database will increase the likelihood of relevant papers being found and cited, and also be a very useful tool for those interested in meta-analysis, and hopefully clarify structure-function relationships. They are interested in hearing from people who might be willing to contribute to their projects, particularly those with programming experience. The number of published neuroimaging studies is increasing rapidly and it is not feasible to read them all. If a computer database could store key information from published fMRI papers and make that information easier to search or share, this would have substantial benefits for the neuroimaging community. Projects like AMAT, Brainmap, Brede and SumsDB have started to tackle this problem. NIDAG wants to formalize and improve these databases so that they meet the needs of the neuroimaging community. Formal meta-analysis of published data is a valuable way to assess the consistency and reliability of experimental results. A database of neuroimaging results would facilitate meta-analyses, in conjunction with tools like GingerALE and Multi-level Kernel Density Analysis.

Proper citation: NIDAG: Neuroimaging Data Access Group (RRID:SCR_001674) Copy   

•   Source: SciCrunch Registry

http://surfer.nmr.mgh.harvard.edu/

Open source software suite for processing and analyzing human brain MRI images. Used for reconstruction of brain cortical surface from structural MRI data, and overlay of functional MRI data onto reconstructed surface. Contains automatic structural imaging stream for processing cross sectional and longitudinal data. Provides anatomical analysis tools, including: representation of cortical surface between white and gray matter, representation of the pial surface, segmentation of white matter from rest of brain, skull stripping, B1 bias field correction, nonlinear registration of cortical surface of individual with stereotaxic atlas, labeling of regions of cortical surface, statistical analysis of group morphometry differences, and labeling of subcortical brain structures.Operating System: Linux, macOS.

Proper citation: FreeSurfer (RRID:SCR_001847) Copy   

•   Source: SciCrunch Registry

http://www.nesys.uio.no/Atlas3D/

A multi-platform visualization tool which allows import and visualization of 3-D atlas structures in combination with tomographic and histological image data. The tool allows visualization and analysis of the reconstructed atlas framework, surface modeling and rotation of selected structures, user-defined slicing at any chosen angle, and import of data produced by the user for merging with the atlas framework. Tomographic image data in NIfTI (Neuroimaging Informatics Technology Initiative) file format, VRML and PNG files can be imported and visualized within the atlas framework. XYZ coordinate lists are also supported. Atlases that are available with the tool include mouse brain structures (3-D reconstructed from The Mouse Brain in Stereotaxic Coordinates by Paxinos and Franklin (2001)) and rat brain structures (3-D reconstructed from The Rat Brain in Stereotaxic Coordinates by Paxinos and Watson (2005)). Experimental data can be imported in Atlas3D and warped to atlas space, using manual linear registration, with the possibility to scale, rotate, and position the imported data. This facilitates assignment of location and comparative analysis of signal location in tomographic images.

Proper citation: Atlas3D (RRID:SCR_001808) Copy   

•   Source: SciCrunch Registry

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

Software that allows user to do faceted search on an ontology and enables visualization of the search results on the 3D digital atlas. Currently supports faceted search of functional neuroanatomy.

Proper citation: Faceted Search Based Ontology Visualizer (RRID:SCR_000124) Copy   

•   Source: SciCrunch Registry

http://surfer.nmr.mgh.harvard.edu/optseq/

Software tool for automatically scheduling events for rapid-presentation event-related (RPER) fMRI experiments (the schedule is the order and timing of events). Events in RPER are presented closely enough in time that their hemodynamic responses will overlap. This requires that the onset times of the events be jittered in order to remove the overlap from the estimate of the hemodynamic response. RPER is highly resistant to habituation, expectation, and set because the subject does not know when the next stimulus will appear or which stimulus type it will be.

Proper citation: Optseq (RRID:SCR_014363) Copy   

•   Source: SciCrunch Registry

http://enigma.ini.usc.edu/protocols/dti-protocols/

Pipeline which provides tools to extract whole-brain average and regional measurements from DTI images including FA, AD, RD and MD. Protocols for preprocessing, ENIGMA-DTI processing (skeletonization and ROI extraction), and GWAS analysis are available. Software tools used for each process are listed within the protocols.

Proper citation: ENIGMA-DTI Pipeline (RRID:SCR_014649) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/gscca_2013/

Group Sparse Canonical Correlation Analysis is a method designed to study the mutual relationship between two different types of data.

Proper citation: Group Sparse Canonical Correlation Analysis (RRID:SCR_014977) Copy   

•   Source: SciCrunch Registry

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

MATLAB Toolbox which provides a mixed effect model for gene-environment interaction (MixGE) on neuroimaging phenotypes, such as structural volumes and tensor-based morphometry (TBM). This model incorporates both fixed and random effects of genetic-set and environment interaction in order to investigate homogeneous and heterogeneous contributions of sets of genetic variants and their interactions with environmental risks to phenotypes.

Proper citation: Mixed Effect Model of Genetic-Set and Environment Interaction (RRID:SCR_015514) Copy   

•   Source: SciCrunch Registry

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

Software containerized environments for reproducible neuroimaging. Part of ReproNim - Center for Reproducible Neuroimaging Computation. DataLad dataset with collection of popular computational tools provided within ready to use containerized environments.

Proper citation: ReproNim/containers (RRID:SCR_018467) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/vmas_2020/

Software tool to generate whole connected 3D brain ventricular shape model and encode ventricular surface deformation information that is inaccessible by ventricle volume measure. Contains automated segmentation approach and surface based multivariate morphometry statistics.

Proper citation: Ventricular Morphometry Analysis System (RRID:SCR_019007) Copy   

•   Source: SciCrunch Registry

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

Course provides training for reproducible analyses of Adolescent Brain Cognitive Development Study data. Designed to provide comprehensive background to ABCD study while delivering hands on instruction on reproducible ReproNim workflows and outcomes.

Proper citation: ABCD-ReproNim Course (RRID:SCR_018911) Copy   

•   Source: SciCrunch Registry

http://www.angiocalc.com/

Providing quality resources for the management of cerebral aneurysms and features an online calculator that calculates cerebral aneurysm volume and percent packing volume after coil embolization. The site also host an imaging Library with neuroanatomy and neurovascular images.

Proper citation: AngioCalc Cerebral Aneurysm Calculator (RRID:SCR_012805) Copy   

•   Source: SciCrunch Registry

http://umcd.humanconnectomeproject.org

Web-based repository and analysis site for connectivity matrices that have been derived from neuroimaging data including different imaging modalities, subject groups, and studies. Users can analyze connectivity matrices that have been shared publicly and upload their own matrices to share or analyze privately.

Proper citation: USC Multimodal Connectivity Database (RRID:SCR_012809) Copy   

•   Source: SciCrunch Registry

http://www2.hu-berlin.de/eyetracking-eeg

A plugin for the open-source MATLAB toolbox EEGLAB developed with the goal to facilitate integrated analyses of electrophysiological and oculomotor data. The plugin parses, imports, and synchronizes simultaneously recorded eye tracking data and adds it as extra channels to the EEG. Saccades and fixations can be imported from the eye tracking raw data or detected with an adaptive velocity-based algorithm. Eye movements are then added as new time-locking events to EEGLAB's event structure, allowing easy saccade- and fixation-related EEG analysis (e.g., fixation-related potentials, FRPs). Alternatively, EEG data can be aligned to stimulus onsets and analyzed according to oculomotor behavior (e.g. pupil size, microsaccades) in a given trial. Saccade-related ICA components can be objectively identified based on their covariance with the electrically independent eye tracker. All functions can be accessed via EEGLAB's GUI or called from the command line.

Proper citation: EYE-EEG (combined eye-tracking & EEG) (RRID:SCR_012903) Copy   

•   Source: SciCrunch Registry

https://github.com/BRAINSia/BRAINSTools

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 23,2023. A graphical program to trace anatomical features in 3D image volumes. This tools is built upon the NA-MIC toolkit. The tool is fully compatible with Slicer3, and integrates the Slicer3 theme.

Proper citation: BRAINSTracer (RRID:SCR_012894) 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://www.softpedia.com/get/Science-CAD/BrainVisa-Morphology-extensions.shtml

An extension projects providing computational tools for performing regional morphological measurements to assess groupwise differences and track morphological changes during maturation and aging. The extensions include computation of regional GM thickness, 3D gyrification index, sulcal lenght and depth and sulcal span. These tools are distributed in the form of plugins for a popular analysis package BrainVisa

Proper citation: BrainVisa Morphology extensions (RRID:SCR_013248) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/meanmachine/

This software can be used to analyze EEG data either using a graphical interface (GUI) or using Matlab scripts, which make use of the functions provided by the MeanMachine. As compared to other libraries, MeanMachine can handle even very large data sets like, for example, 256 channels recorded at 2KHz.

Proper citation: Mean Machine (RRID:SCR_013103) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/liversegm/

A set of tools for the processing of liver images. These tools consist of a level set based variational approach that incorporates shape priors and appearance models. It uses ITK-SNAP 1.4 as interface. The tools are capable of automatic liver segmentation and semi-automatic injury segmentation.

Proper citation: LiverSegm (RRID:SCR_013108) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/cmind_py_2014/

A python toolbox for analysis of MRI images. It relies on calls to a number of widely tested algorithms from the FMRIB software library (FSL) and the advanced normalization tools (ANTS) to provide analysis of simultaneously acquired ASL/BOLD fMRI data. It was developed for analyzing the datasets collected as part of the Cincinnati MR Imaging of NeuroDevelopment (C-MIND) project.

Proper citation: CMIND PY (RRID:SCR_014097) Copy   

•   Source: SciCrunch Registry