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http://www.nitrc.org/projects/cs_schizbull08/

This project hosts data for CANDI Share Schizophrenia Bulletin 2008 (reference below) as part of the CANDI Neuroimaging Access Point. This set includes preprocessed MRI images and segmentation results of all 4 diagnostic groups (Healthy Controls, N=29; Schizophrenia Spectrum, N=20; Bipolar Disorder with Psychosis, N=19; and Bipolar Disorder without Psychosis, N=35). Frazier JA, Hodge SM, Breeze JL, Giuliano AJ, Terry JE, Moore CM, Kennedy DN, Lopez-Larson MP, Caviness VS, Seidman LJ, Zablotsky B, Makris N. Diagnostic and sex effects on limbic volumes in early-onset bipolar disorder and schizophrenia. Schizophr Bull. 2008 Jan;34(1):37-46.

Proper citation: CANDI Share: Schizophrenia Bulletin 2008 (RRID:SCR_009451) Copy   

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http://www.radiologyresearch.org/HippocampusSegmentation.aspx

This dataset contains T1-weighted MR images of 50 subjects, 40 of whom are patients with temporal lobe epilepsy and 10 are nonepileptic subjects. Hippocampus labels are provided for 25 subjects for training. The users may submit their segmentation outcomes for the remaining 25 testing images to get a table of segmentation metrics.

Proper citation: MRI Dataset for Hippocampus Segmentation (RRID:SCR_009597) Copy   

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http://www.nitrc.org/projects/me-icr/

Data set of an AFNI GroupInCorr session for multi-echo independent component regression (ME-ICR) for a cohort of 52 subjects. This dataset provides a high-quality atlas of seed-based functional connectivity with strong statistical conditioning.

Proper citation: Multi-Echo Independent Component Regression Group-Level Connectivity Dataset (RRID:SCR_009508) Copy   

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http://fcon_1000.projects.nitrc.org/indi/pro/nki.html

A phenotypically rich neuroimaging sample, consisting of data obtained from individuals between the ages of 4 and 85 years-old. All individuals included in the sample undergo semi-structured diagnostic psychiatric interviews, and complete a battery of psychiatric, cognitive and behavioral assessments in order to provide comprehensive phenotypic information for the purpose of exploring brain / behavior relationships.

Proper citation: NKI/Rockland Sample (RRID:SCR_009435) Copy   

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http://www.umassmed.edu/psychiatry/candi/

A series of structural brain images, as well as their anatomic segmentations, demographic and behavioral data and a set of related morphometric resources (static and dynamic atlases) made avaialble from the Child and Adolescent NeuroDevelopment Initiative (CANDI) at UMass Medical School. Schiz Bull 2008 data is now available on NITRC-IR. Please register for access: http://www.nitrc.org/project/request.php?group_id=377

Proper citation: CANDI Neuroimaging Access Point (RRID:SCR_009542) Copy   

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

This package is a set of three slicer modules which together are able to compute a DWI Atlas given a set of DWI''s. The modules included are: # A Groupwise Registration module -> compute''s a deformation field for each DWI, using, for example, FA maps as input # Warp DWI module -> used to warp each DWI using the deformation from (1) # DWI Averager -> used to average the set of warped DWI''s producing the final DWI Atlas

Proper citation: Create DWI Atlas (RRID:SCR_009455) Copy   

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http://www.nitrc.org/projects/camino-trackvis/

Software package that allows interoperability between CAMINO and TRACKVIS. CAMINO is a leading software package in DTI processing. The package is from University of College London. TRACKVIS is a tract visualizing utility with capability of visualizing up to and over a million white matter tracts seamlessly. The package is from Massachusetts General Hospital. With increasing efforts on brain connectivity analyses it becomes important to have tools that can allow increased interoperability among different tractography tools. The tools in this package allow conversion of tracts from one format to another in a very effective way with ability to handle over a million tracts.

Proper citation: CAMINO-TRACKVIS (RRID:SCR_009450) Copy   

•   Source: SciCrunch Registry

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

A Matlab toolbox that allows computation of task-related functional connectivity between multiple pairs of regions. Task-related functional connectivity is computed using the correlational psychophysiological interaction (cPPI) methodology described in Fornito et al. (2012) PNAS, 109: 12788-12793. The toolbox assumes that first-level design matrices have been specified and estimated using SPM5 or later. It takes as input these design matrices as well as user-extracted regional time courses and returns a matrix of pair-wise, task-related functional connectivity for each participant. The method is scalable to large networks comprising hundreds of regions and is well-suited to graph theoretic analyses and functional connectomics. One modifiable script, cPPI_master.m, can be used to run the analysis for an entire sample of participants.

Proper citation: cPPI Toolbox for fMRI (RRID:SCR_009518) Copy   

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http://www.montefiore.ulg.ac.be/~phillips/FASST.html

An EEG toolbox developed to help users with 3 specific types of data and problems: simulatenous EEG-fMRI recording, continuous EEG scoring (e.g. sleep) and handling (visualisation, cutting, power spectrum, etc.) multi-channel recording of spontaneous EEG. The toolbox is written in Matlab and is specifically compatible with the BrainAmp family of EEG recorders (from BrainProducts GmbH) Three other data formats are now also supported: the edf "European Data Format", exported raw-EGI data (from Electrical Geodesics, Inc.) and the BCI2000 format.The results are directly compatible with SPM8 and are saved with SPM8 EEG data format.

Proper citation: fMRI Artefact rejection and Sleep Scoring Toolbox (RRID:SCR_009620) Copy   

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http://www.nitrc.org/projects/gig-ica/

Software toolbox for group-information guided Independent Component Analysis (ICA). In GIG-ICA, group information captured by standard Independent Component Analysis (ICA) on the group level is used as guidance to compute individual subject specific Independent Components (ICs) using a multi-objective optimization strategy. For computing subject specific ICs, GIG-ICA is applicable to subjects that are involved or not involved in the computation of the group information. Besides the group ICs, group information captured from other imaging modalities and meta analysis could be used as the guidance in GIG-ICA too.

Proper citation: Group Information Guided ICA (RRID:SCR_009491) Copy   

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http://caid.cs.uga.edu/?name=software

A software toolbox to predict 358 DICCCOL landmarks (Dense Individualized and Common Connectivity-based Cortical landmarks (http://dicccol.cs.uga.edu) ) on a new brain given b0, brain surface data and DTI derived fiber data (vtk format). Each DICCCOL landmark is defined by group-wise consistent white-matter fiber connection patterns derived from diffusion tensor imaging (DTI) data. DICCCOL aims to provide large-scale cortical landmarks with finer granularity, better functional homogeneity, more accurate functional localization, and automatically-established cross-subjects correspondence.

Proper citation: DICCCOL predictor (RRID:SCR_009554) Copy   

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http://www.calatk.org/

An open-source toolkit for cross-sectional and longitudinal atlas building. The CalaTK project develops innovative methods and tools for longitudinal atlases with a focus on neurodevelopment. The computational toolbox is developed with the objective to analyze the neural developmental patterns observed in human and non-human primate structural and diffusion tensor magnetic resonance (MR) images.

Proper citation: CalaTK (RRID:SCR_009547) Copy   

•   Source: SciCrunch Registry

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

An fMRI toolkit which contains a large selection of complex network measures in Matlab GUI. These measures are increasingly used to characterize structural and functional brain connectivity datasets.

Proper citation: Brainnetome fMRI toolkit (RRID:SCR_014092) Copy   

•   Source: SciCrunch Registry

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

A MATLAB toolbox for denoising task-based fMRI data. It derives noise regressors from voxels unrelated to the experimental paradigm and uses these regressors in a general linear model (GLM) analysis of the data. The technique only requires a design matrix indicating the experimental design and an fMRI dataset.

Proper citation: GLMdenoise: a fast, automated technique for denoising task-based fMRI data (RRID:SCR_014116) Copy   

•   Source: SciCrunch Registry

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

A software tool (with GUI) for investigating inter-regional functional connectivity in event-related fMRI data and allows the user to assess the modulation of functional connectivity by an experimental condition.

Proper citation: BetA-Series COrrelation (RRID:SCR_014086) Copy   

•   Source: SciCrunch Registry

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

A DICOM image converter based on the ITK IO mechanism for reading and writing images. The formats currently supported by the converter are DICOM to: Analyze (*.hdr); MetaImage (*.mhd); Nrrd (*.nhdr, *.nrrd).

Proper citation: DICOMConvert (RRID:SCR_014100) Copy   

•   Source: SciCrunch Registry

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

Standalone software designed to be used by radiology researchers for storage and anonymization of research images.

Proper citation: Notion ResearchPACS (RRID:SCR_014154) Copy   

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http://sourceforge.net/projects/cudasphere/

A CUDA C based toolkit which provides a GPU based implementation of the spherical model forward solution for the 306 channel Elekta Neuromag MEG system and the EEG. The 1-Sphere forward solution for the MEG and the 4-Sphere forward solution for the EEG is implemented in CUDA C and an accelerated solution is obtained using the NVIDIA GPU when the solution is calculated for a large number of dipoles (on the order of 15000 and above) and sensor location. Speedup by a factor of 22 and 32 is obtained for the EEG and MEG solution respectively when compared to the fastest CPU implementation available in the public domain. The complete source code and pre-compiled binaries are also made available via an open source license (GPL Version 3). A CUDA enabled NVIDIA graphics card is required to use the software.

Proper citation: CUDA-SPHERE-FWD-MEEG (RRID:SCR_013225) Copy   

•   Source: SciCrunch Registry

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

A comprehensive and open-source library of analysis tools for multi-parametric MRI of the spinal cord. The toolbox includes a template and several atlases, along with state-of-the-art methods to register any data to the template. It also includes useful scripts for data preprocessing: extraction of centerline, automatic segmentation, slice-wise motion correction, etc.

Proper citation: Spinal Cord Toolbox (RRID:SCR_014170) Copy   

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https://github.com/BRAINSia/BRAINSTools

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 23,2023. A suite of tools to generate the cortical surface of the brain. The surface is generated in the middle of grey matter and can be used to measure surface features including cortical depth and curvature.

Proper citation: BRAINSCortex (RRID:SCR_001082) Copy   

•   Source: SciCrunch Registry