Comput. Biol. Med. - GMAC: a Matlab toolbox for spectral Granger causality analysis of fMRI data.

Tópicos

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Resumo

Investigation of causal interactions within brain networks using Granger causality analysis (GCA) is a key challenge in studying neural activity on the basis of functional magnetic resonance imaging (fMRI). The article describes an open-source software toolbox GMAC (Granger multivariate autoregressive connectivity) implementing multivariate spectral GCA. Available features are: fMRI data importing/exporting, 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 have been integrated into a user-friendly graphical interface developed in the Matlab environment, easily accessible to both technical and clinical users.

Resumo Limpo

investig causal interact within brain network use granger causal analysi gca key challeng studi neural activ basi function magnet reson imag fmri articl describ opensourc softwar toolbox gmac granger multivari autoregress connect implement multivari spectral gca avail featur fmri data importingexport network node definit time seri preprocess multivari autoregress model spectral granger causal index estim statist signific assess use surrog data network analysi visual connect result function integr userfriend graphic interfac develop matlab environ easili access technic clinic user

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