Lionel Barnett and I are pleased to announce the availability of our wholly new MATLAB toolbox for implementing Granger causality analysis. This new free software is a wholesale revision of my previous 'GCCA' toolbox which has been available since 2010 (http://www.ncbi.nlm.nih.gov/pubmed/19961876), and which has enjoyed a wide uptake within the neuroscience community and beyond. Granger causality is a powerful analysis method which can be used to detect directed functional connectivity in stationary time-series data, of the sort often (but not always) found in neuroscience datasets.
The new 'multivariate Granger causality' 'MVGC' toolbox offers a range of enhancements. It easily handles conditional spectral analyses. It requires only estimation of the 'full' regression model, avoiding biases inherent in estimation of both full and reduced models. It is accompanied by a fully functional help system integrated into the online MATLAB documentation. And much else besides.
The toolbox can be downloaded here:
A paper describing the toolbox and the basic concepts and maths underlying Granger causality has been recently published in Journal of Neuroscience Methods:
… which is the appropriate citation for any published work utilizing the software.
Preparation of the toolbox was supported by the Sackler Centre for Consciousness Science, which is funded by the Dr. Mortimer and Dame Theresa Sackler Foundation.
We hope you find it useful!
Best regards
Anil Seth and Lionel Barnett
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Anil K. Seth, D.Phil.
Professor of Cognitive and Computational Neuroscience
Co-Director, Sackler Centre for Consciousness Science
University of Sussex
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