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http://www.brain-connectivity-toolbox.net

A large selection of complex network measures in Matlab that are increasingly used to characterize structural and functional brain connectivity datasets. Several people have contributed to the toolbox, and if you wish to contribute with a new function or set of functions, please contact Olaf Sporns. All efforts have been made to avoid errors, but users are strongly urged to independently verify the accuracy and suitability of toolbox functions for the chosen application. Please report bugs or substantial improvements.

Proper citation: Brain Connectivity Toolbox (RRID:SCR_004841) Copy   

•   Source: SciCrunch Registry

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

A software toolkit that performs multiple imputation for group level, single sample t-tests. Whole brain group level statistic maps from fMRI rarely cover the entire brain as a result of missing data. Missingness between subjects in fMRI datasets can result from susceptibility artifacts, bounding box (acquisition parameters), and small differences in post-normalized morphology. The toolkit consists of several interactive command line scripts that guide the user to map the spatial distribution of missing data across contrast images, calculate spatial neighborhood averages that help impute values, perform conventional and multiple imputed t-statistics, save the results to brain maps, and create result tables. The toolkit contains an instruction manual (pdf), two Matlab scripts and one R-Statistics script, which depend on functions defined in the popular SPM toolbox and functions defined in the MICE package for (R).

Proper citation: Group Level Imputation of Statistic Maps (RRID:SCR_002397) Copy   

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http://www.rogue-research.com

Neuronavigation system for use in human cognitive neuroscience (TMS, EEG, NIRS) and for non-human neurosurgical applications.

Proper citation: Brainsight (RRID:SCR_009539) Copy   

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http://www.cns.atr.jp/dni/en/downloads/tools-for-brain-behavior-data-sharing/

This is MATLAB library to create Neuroshare data format. You can convert your own data into Neuroshare format file.

Proper citation: Matlab Neuroshare Library (RRID:SCR_006957) Copy   

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http://www.neuroconstruct.org/

Software for simulating complex networks of biologically realistic neurons, i.e. models incorporating dendritic morphologies and realistic cell membrane conductance, implemented in Java and generates script files for the NEURON and GENESIS simulators, with support for other simulation platforms (including PSICS and PyNN) in development. neuroConstruct is being developed in the Silver Lab in the Department of Neuroscience, Physiology and Pharmacology at UCL and uses the latest NeuroML specifications, including MorphML, ChannelML and NetworkML. Some of the key features of neuroConstruct are: Creation of networks of biologically realistic neurons, positioned in 3D space. Complex connectivity patterns between cell groups can be specified for the networks. Can import morphology files in GENESIS, NEURON, Neurolucida, SWC and MorphML format for inclusion in network models. Simulations can be run on the NEURON or GENESIS platforms. Cellular processes (synapses/channel mechanisms) can be imported from native script files or created in ChannelML. Recording of simulation data generated by the simulation and visualization/analysis of data. Stored simulation runs can be viewed and managed through the Simulation Browser interface.

Proper citation: neuroConstruct (RRID:SCR_007197) Copy   

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

A program which creates anatomically realistic virtual neurons using the formalism of the Lyndenmayer systems to implement sets of neuroanatomical rules discovered by several research groups. The program algorithms read in experimental data - in the form of statistical distributions - to generate virtual structures. L-Neuron samples the values of the parameters within these statistical distributions in a stochastic (random) fashion during dendritic growth.

Proper citation: L-Neuron (RRID:SCR_014132) Copy   

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

A Matlab tool for simulating extracellular potential recordings in spiking neural network (SNN) models. VERTEX is designed to facilitate the simulation of extracellular potentials generated by activity in SNNs; in particular, spatially-organised networks containing thousands or hundreds of thousands of neurons. It has a limited scope but has a simpler user interface so that a simulation can be specified simply by setting some parameters and run using a few function calls.

Proper citation: Virtual Electrode Recording Tool for EXtracellular potentials (VERTEX) (RRID:SCR_014178) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/ruby-nifti/

A library for handling NIfTI data in the Ruby programming language. Ruby NIfTI supports basic read and write access to NIfTI files, including basic and extended header information and image information. It doesn't attempt to touch the image data but it does provide access to qform and sform orientation matrices. It also provides a nice interface to get at NIfTI info from within Ruby.

Proper citation: Ruby NIfTI (RRID:SCR_014164) Copy   

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

A collection of methods for comparing the performance of different image algorithms. These methods generate quantitative scores that measure divergences to a standard.

Proper citation: SCORE (RRID:SCR_014165) Copy   

•   Source: SciCrunch Registry

http://www.thevirtualbrain.org/

Simulation software for modeling the entire human brain by combining structural and functional data from empirical neuroimaging data. It can generate local field potentials, EEG, MEG and fMRI BOLD data based on neural mass models. The user can also modify the model parameters to match clinical conditions from focal lesions or degenerative disorders.

Proper citation: Virtual brain (RRID:SCR_002249) Copy   

•   Source: SciCrunch Registry

http://omlc.ogi.edu/software/mc/

MCML is a Monte Carlo simulation program for Multi-layered Turbid Media with an infinitely narrow photon beam as the light source. The simulation is specified by an input text file called, for example, sample.mci, which can be modified by any simple text editor. The output is another text file called, for example, sample.mco. (The names are arbitrary.) CONV is a convolution program which uses the MCML output file to convolve for photon beams of any size in a Gaussian or flat field shape. CONV can provide a variety of output formats (reflectance, transmission, iso-fluence contours, etc.), which are compatible with standard graphics applications.

Proper citation: MCML and CONV (RRID:SCR_002419) Copy   

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http://code.google.com/p/panda-tool/

Software matlab toolbox for pipeline processing of diffusion MRI images. For each subject, PANDA can provide outputs in 2 types: i) diffusion parameter data that is ready for statistical analysis; ii) brain anatomical networks constructed by using diffusion tractography. Particularly, there are 3 types of resultant diffusion parameter data: WM atlas-level, voxel-level and TBSS-level. The brain network generated by PANDA has various edge definitions, e.g. fiber number, length, or FA-weighted. The key advantages of PANDA are as follows: # fully-automatic processing from raw DICOM/NIFTI to final outputs; # Supporting both sequential and parallel computation. The parallel environment can be a single desktop with multiple-cores or a computing cluster with a SGE system; # A very friendly GUI (graphical user interface).

Proper citation: PANDA (RRID:SCR_002511) Copy   

•   Source: SciCrunch Registry

http://www.dartmouth.edu/~nir/nirfast/

Software package for modeling Near-Infrared light transport in tissue and image reconstruction. This includes: Standard single wavelength absorption and reduced scatter, Multi-wavelength spectrally constrained models and Fluorescence models.

Proper citation: Nirfast (RRID:SCR_002503) Copy   

•   Source: SciCrunch Registry

http://www.fmrib.ox.ac.uk/fsl/

Software library of image analysis and statistical tools for fMRI, MRI and DTI brain imaging data. Include registration, atlases, diffusion MRI tools for parameter reconstruction and probabilistic taractography, and viewer. Several brain atlases, integrated into FSLView and Featquery, allow viewing of structural and cytoarchitectonic standard space labels and probability maps for cortical and subcortical structures and white matter tracts. Includes Harvard-Oxford cortical and subcortical structural atlases, Julich histological atlas, JHU DTI-based white-matter atlases, Oxford thalamic connectivity atlas, Talairach atlas, MNI structural atlas, and Cerebellum atlas.

Proper citation: FSL (RRID:SCR_002823) Copy   

•   Source: SciCrunch Registry

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

An I/O library for Matlab/Octave Matlab and Octave library for reading and writing Nifti-1 files. cbiNifti is intended to be a small, self-contained library that makes minimal assumptions about what Nifti files should look like and allow users easy access to the raw data. cbiNifti handles compressed file formats for reading and writing, using Unix pipes for compression and decompression. More information and code examples at: http://www.pc.rhul.ac.uk/staff/J.Larsson/software.html

Proper citation: cbiNifti: Matlab/Octave Nifti library (RRID:SCR_000860) Copy   

•   Source: SciCrunch Registry

http://briansimulator.org/

Software Python package for simulating spiking neural networks. Useful for neuroscientific modelling at systems level, and for teaching computational neuroscience. Intuitive and efficient neural simulator.

Proper citation: Brian Simulator (RRID:SCR_002998) Copy   

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http://sccn.ucsd.edu/wiki/MPT

This toolbox is an EEGLAB plugin for performing Measure Projection Analysis. Measure Projection Analysis (MPA) is a novel probabilistic multi-subject inference method that overcomes EEG Independent Component (IC) clustering issues by abandoning the notion of distinct IC clusters. Instead, it searches voxel by voxel for brain regions having event-related IC process dynamics that exhibit statistically significant consistency across subjects and/or sessions as quantified by the values of various EEG measures. Local-mean EEG measure values are then assigned to all such locations based on a probabilistic model of IC localization error and inter-subject anatomical and functional differences.

Proper citation: Measure Projection Toolbox (RRID:SCR_002429) Copy   

•   Source: SciCrunch Registry

https://pydicom.github.io/

Software Python package for working with DICOM files, made for inspecting and modifying DICOM data in an easy pythonic way. The modifications can be written again to a new file. As a pure python package, it should run anywhere python runs without any other requirements.

Proper citation: pydicom (RRID:SCR_002573) Copy   

•   Source: SciCrunch Registry

http://www.lead-dbs.org/

MATLAB toolbox for deep-brain-stimulation (DBS) electrode reconstructions and visualizations based on postoperative MRI and computed tomography (CT) imaging. The toolbox also facilitates visualization of localization results in 2D/3D, analysis of DBS-electrode placement's effects on clinical results, simulation of DBS stimulations, diffusion tensor imaging (DTI) based connectivity estimates, and fiber-tracking from the VAT to other brain regions (connectomic surgery).

Proper citation: LEAD-DBS (RRID:SCR_002915) Copy   

•   Source: SciCrunch Registry

https://www.nitrc.org/projects/gmac_2012/

Open-source software toolbox implemented multivariate spectral Granger Causality Analysis for studying brain connectivity using fMRI data. Available features are: fMRI data importing, network nodes definition, time series preprocessing, multivariate autoregressive modeling, spectral Granger causality indexes estimation, statistical significance assessment using surrogate data, network analysis and visualization of connectivity results. All functions are integrated into a graphical user interface developed in Matlab environment. Dependencies: Matlab, BIOSIG, SPM, MarsBar.

Proper citation: GMAC: A Matlab toolbox for spectral Granger causality analysis of fMRI data (RRID:SCR_009581) Copy   

•   Source: SciCrunch Registry