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

Brainnetome Atlas Viewer shows the anatomical connectivity-based parcellation results, including the maximum probabilistic maps, probabilistic maps and both the anatomical and functional connectivity patterns, which have been developed in Brainnetome Center, CASIA. The atlas is based on the analysis of connectional architecture with in vivo multi-modal MRI data.

Proper citation: Brainnetome Atlas Viewer (RRID:SCR_014091) Copy   

•   Source: SciCrunch Registry

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

A clinical toolbox useful for normalizing data from individuals with brain injury and/or modalities popular in the clinical environment (CT). It supports either enantiomorphic or lesion-masked normalization. It can be either scripted or used with SPM's simple graphical interface.

Proper citation: Clinical Toolbox for SPM (RRID:SCR_014096) Copy   

•   Source: SciCrunch Registry

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

A tool which computes an automatic segmentation of neonatal brain MRI. It uses a registered probabilistic brain atlas to select training samples and to be used as a spatial prior.

Proper citation: Neoseg (RRID:SCR_014144) Copy   

•   Source: SciCrunch Registry

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

This tool allows segmenting neonate brain MRI using a subject-specific atlas. It generates a subject-specific atlas based on an atlas population and some diffusion images of the subject to segment. Then a single atlas method is run with this atlas to obtain results.

Proper citation: NeoSegPipeline (RRID:SCR_014145) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/neuron-c/

A simulation language for modeling biophysically realistic neural circuits (1 to 10,000 neurons) and simulating physiology experiments on it. Programs for plotting and displaying data are included.

Proper citation: Neuron-C (RRID:SCR_014148) Copy   

•   Source: SciCrunch Registry

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

A database which contains longitudinal structural MRIs, spectroscopy, DTI and correlated clinical/behavioral data from approximately 500 healthy, normally developing children, ages newborn to young adult.

Proper citation: NIH Pediatric MRI Data Repository (RRID:SCR_014149) Copy   

•   Source: SciCrunch Registry

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

A practical diffusion MRI simulator for development, testing, and optimisation of novel MR pulse sequences for microstructure imaging. MISST is based on a matrix method approach and simulates the signal for a large variety of pulse sequences and tissue models. It is designed for diffusion MRI researchers who are interested in understanding and developing diffusion pulse sequences for imaging microstructure.

Proper citation: MISST - Microstructure Imaging Sequence Simulation ToolBox (RRID:SCR_014140) Copy   

•   Source: SciCrunch Registry

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

A tool which offers a fast algorithm for computing myelin maps from multiecho T2 relaxation data using parallel computation with multicore CPUs and graphics processing units (GPUs). The tool also provides non-local spatial regularization to produce more accurate and reliable myelin maps for noisy T2 relaxation data.

Proper citation: Fast T2 relaxation data analysis with stimulated echo correction and non-local spatial regularisation (RRID:SCR_014108) Copy   

•   Source: SciCrunch Registry

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

A project which aims to simplify the preparation of accurate electromagnetic head models for EEG forward modeling. It builds off of the seminal SimNIBS tool for electromagnetic field modelling of transcranial magnetic stimulation and transcranial direct current stimulation. Human skin, skull, cerebrospinal fluid, and brain meshing pipelines have been rewritten with Nipype to ease access parallel processing and to allow users to start/stop the workflows. Conductivity tensor mapping from diffusion-weighted imaging is also included.

Proper citation: Forward: Accurate finite element electromagnetic head models (RRID:SCR_014109) Copy   

•   Source: SciCrunch Registry

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

A toolbox developed for multi-channel time-frequency analysis of event related activity of EEG and MEG data. It provides tools for data analysis and visualization of the most commonly used measures of time-frequency transformed event related data as well as data decomposition through non-negative matrix and multi-way (tensor) factorization. The decompositions provided can accommodate additional dimensions like subjects, conditions or repeats and as such they are perfected for group analysis. The toolbox enables tracking of phase locked activity from one channel-time-frequency instance to another as well as tools for artifact rejection in the time-frequency domain.

Proper citation: ERPwavelab (RRID:SCR_014106) Copy   

•   Source: SciCrunch Registry

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

A functional connectivity analysis tool for near-infrared spectroscopy data. Its functions include preprocessing, quality control, FC calculation and network analysis.

Proper citation: Functional Connectivity Analysis Tool for near-infrared spectroscopy data (RRID:SCR_014111) Copy   

•   Source: SciCrunch Registry

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

A toolbox for a point-process derived GLM analysis of eye tracking data in Matlab. Data loading, model specification, fitting and review are organized into a sequence of events, each of which is handled by a separate module in the toolbox. The graphical interface was created using the Matlab graphical user interface development environment.

Proper citation: GazeReader (RRID:SCR_014112) Copy   

•   Source: SciCrunch Registry

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

A software package which contains tools for doing group analysis of FreeSurfer surface data using the general linear model in R (lm). Results can be rendered in FreeSurfer freeview or AFNI SUMA. Plots for selected vertices can be rendered in R with ggplot2.

Proper citation: freesurfR (RRID:SCR_014110) Copy   

•   Source: SciCrunch Registry

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

A multivariate method for fMRI data analysis based on generalized canonical correlation analysis (gCCA) to maximize SPM reproducibility without adopting any model for the hemodynamic response or other temporal brain responses. For multiple subjects, gCCA explores a broad range of temporal responses in fMRI time-series space while maximizing the mean of correlation coefficients between the pair-wise spatial maps of the subjects.

Proper citation: gCCA (RRID:SCR_014113) Copy   

•   Source: SciCrunch Registry

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

A software application that calculates and runs a GLM on graph theory properties derived from brain networks. The GLM accepts continuous and categorical between-participant predictors and categorical within-participant predictors. Significance is determined via non-parametric permutation tests. Both fully connected and thresholded networks are tested. The toolbox also provides a data processing path for resting state and (block design) task fMRI data. Options for partialing nuisance signals include local and total white matter signal and PCA of white matter/ventricular signal. For task fMRI, connectivity matrices are computed for each condition by dividing up the timeseries. To compensate for HDR-related delay, the timeseries is deconvolved, allowing for division at the actual onset/offset times.

Proper citation: Graph Theory GLM (GTG) MATLAB Toolbox (RRID:SCR_014075) Copy   

•   Source: SciCrunch Registry

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

A user-friendly graphical-user-interface (GUI)-based toolbox (MATLAB) for comprehensive graph-theoretical analyses of brain connectivity, including network construction and characterization, statistical analysis on network topological measures, and interactive exploration of results.

Proper citation: GraphVar: A toolbox for comprehensive graph analyses of functional brain connectivity (RRID:SCR_014117) Copy   

•   Source: SciCrunch Registry

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

A software package which performs high-dimensional warping of brain images. Standard voxel-based analysis can be applied to these tissue density maps, in order to examine regional volumetrics, effects of disease, or correlations with clinical measurements.

Proper citation: HAMMER: Deformable Registration (RRID:SCR_014118) Copy   

•   Source: SciCrunch Registry

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

An MRI preprocessing pipeline built with HOF (Heterogeneous Optimization Framework) methodology. MGA prepares neuro-oncology clinical imaging studies for scientific analysis in both longitudinal and cross-sectional studies. It works on DICOM images from a single MRI study and includes perfusion (DSC sequence based) analysis and DTI analysis. MGA spatially co-registers all study images to an atlas template and to a template image within the study.

Proper citation: MGA - Multimodal Glioma Analysis (RRID:SCR_014122) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/bic-mni-models/

Anatomical brain template library which includes models from ICBM 2009 template.Number of unbiased non-linear averages of MNI152 database have been generated that combines attractions of both high-spatial resolution and signal-to-noise while not being subject to vagaries of any single brain. Procedure involved multiple iterations of process where, at each iteration, individual native MRIs were non-linearly fitted to the average template from previous iteration, beginning with MNI152 linear template.

Proper citation: bic-mni-models (RRID:SCR_014087) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/iukf_2013/

A tractography algorithm for HARDI which provides a relatively accurate and efficient fiber tracking mechanism by reconstructing a bi-tensor model for underlying signals and exploiting intrinsic operations on the space of diffusion tensors. Given HARDI data sets, IUKF is capable of tracking in the presence of complex local geometries, such as crossing and kissing fibers. Reconstruction is only performed at the voxels along estimated fibers.

Proper citation: Intrinsic Unscented Kalman Filter (IUKF) Tractography Software v1.0 (RRID:SCR_014127) Copy   

•   Source: SciCrunch Registry