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PyMVPA / MultiVariate Pattern Analysis in Python
Applies classifier-based analysis techniques to functional magnetic resonance imaging (fMRI) datasets. PyMVPA makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine-learning packages. It provides a collection of common algorithms and processing steps that can be combined. The software code is tested to be portable across multiple platforms.
FNC / Functional Network Connectivity
Allows users to investigate relationships between brain networks. The FNC Toolbox is a Matlab software that extends the analysis run by the GIFT toolbox. The application is able to compute Granger Causality or the highest correlated lag between components from a GIFT output file. It was tested for the identification of pairs of independent components that are showing changes in temporal correlation between healthy controls and schizophrenic patients.
SCKS / Square-root Cubature Kalman Filter
Evaluates states, input and parameters of stochastic continuous-discrete state-space models. SCKS is a toolbox that consists of two main algorithms: square-root Cubature Kalman Filter and square-root Rauch-Tang-Striebel smoother (SCKF-SCKS). The application can be applied to the inversion of any nonlinear continuous dynamic model that is formulated with stochastic differential equation and is especially designed for the assessment of the underlying neuronal signal.
Nipype / Neuroimaging in Python: Pipelines and Interfaces
Interfaces with existing software for analysis of neuroimaging data and comparative development of algorithms. Nipype is an open-source, community-developed, Python-based software package that consists of three components: (1) interfaces to external tools providing a unified way for setting inputs, executing, and retrieving outputs; (2) a workflow engine for creating analysis pipelines; and (3) plug-ins that execute workflows either locally or in a distributed processing environment.
TDT / The decoding toolbox
Represents a user-friendly, powerful and flexible package for multivariate analysis of functional brain imaging data. TDT allows running fast whole-brain analyses, region-of-interest analyses and searchlight analyses, using machine learning classifiers, pattern correlation analysis, or representational similarity analysis. It offers automatic creation and visualization of diverse cross-validation schemes, feature scaling, nested parameter selection, a variety of feature selection methods, multiclass capabilities, and pattern reconstruction from classifier weights.
IClinfMRI
New
Assists users in functional magnetic resonance imaging (fMRI) research. IclinfMRI consists of a five-modules program able to perform interactive rs-fMRI mapping and visualization of sites with potential NVU in fMRI results. Besides, the application includes utilities to convert DICOM files towards the NIfti format and to lastly export the analyzed images as a series of files. Results can be exploited into a surgical navigation system with application on presurgical fMRI planning.
4D FFT Toolbox
Characterizing the role in overall brain activation of spatially scaled periodic patterns with given temporal recurrence rates. 4D FFT Toolbox is a Matlab software that focuses on the computation of is the spatiotemporal spectral profile (STSP). The application is able to distinguish populations of interest among large balanced multi-site resting functional magnetic resonance imaging (fMRI) dataset. It was tested on a dataset of fMRI data including schizophrenia patients and healthy controls.
DynamicBC
An open-source MATLAB toolbox with user-friendly graphical user interfaces, implementing both dynamic functional and effective connectivity for tracking brain dynamics from functional MRI. We provided two strategies for dynamic analysis: (1) the commonly utilized sliding-window analysis and (2) the flexible least squares based time-varying parameter regression strategy. The toolbox also implements multiple functional measures including seed-to-voxel analysis, region of interest (ROI)-to-ROI analysis, and voxel-to-voxel analysis.
ToolConnect
Infers functional connectivity by analyzing the peak trains of spiking neuronal signals. ToolConnect implements correlation and information theory based core algorithms. It contains several modules in the windows form embodiment and allows the user to easily manipulate and analyze data, while providing computational efficiency and accuracy. This tool is able to return both numerical and graphical results. It has been designed to be adapted, modified and extended by the interested researchers.
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