blockMVAR –Toolbox for block-based MVAR connectivity analysis

 

Matlab Toolbox based on the papers:

The present study introduces a new framework for the frequency-domain evaluation of directional influences in jointly stationary multivariate vector processes. The framework extends to the study of vector processes the DC/PDC framework, and provides a full multivariate account for the Geweke framework. As such, it is recommended for the evaluation of causal relationships between multiple blocks of time series, with typical application in neurophysiology where multichannel data acquisition technologies allow to monitor many regions of interest with many recordings per region. The proposed framework is exploited to define new frequency domain connectivity measures, which are shown (i) to possess desirable theoretical properties of causality measures; (ii) to be able to reflect either direct causality or total (i.e., direct+indirect) causality from one vector process to another in the multivariate representation; (iii) to reduce to known causality measures derived from the Geweke framework in the case of bivariate vector processes, and from the DC/PDC framework in the case of multivariate scalar processes.

 

DOWNLOAD:

Zip file with all scripts and functions: blockMVAR.zip

 

 

Description of the Toolbox

Functions:

 

Scripts:

 

The toolbox makes also use of functions taken from the eMVAR toolbox: