BSMART: A Matlab/C Toolbox for Analyzing Brain Circuits

BSMART, an acronym of Brain-System for Multivariate AutoRegressive Timeseries, is an open-source software package for analyzing brain circuits. BSMART is a project that was born out of a collaborative research effort between Dr. Hualou Liang at Drexel University, Dr. Steven Bressler at Florida Atlantic University, and Dr. Mingzhou Ding at University of Florida. BSMART can be applied to a wide variety of neuroelectromagnetic phenomena, including EEG, MEG and fMRI data. A unique feature of the BSMART package is Granger causality that can be used to assess causal influences and directions of driving among multiple neural signals.

The backbone of the BSMART project is Multivariate AutoRegressive (MAR) analysis that has been long developed for statistical quantification of brain connectivity on different time scales. Based upon a MAR model, a plethora of spectral quantities such as auto power, partial power, coherence, partial coherence, multiple coherence and Granger causality can be immediately derived.  The approach has been fruitfully used to characterize, with high spatial, temporal, and frequency resolution, functional relations within large scale brain networks.

The BSMART is currently undergoing beta test, freely available under the GNU public license (download BSMART). It is supported by a grant from the National Institute of Neurological Disorders and Stroke (NINDS) through the NIH Neuroinformatics / Human Brain Projects.

The BSMART is described in:

Jie Cui, Lei Xu, Steven L. Bressler, Mingzhou Ding, Hualou Liang, BSMART: a Matlab/C toolbox for analysis of multichannel neural time series, Neural Networks, Special Issue on Neuroinformatics, 21:1094 - 1104, 2008. (download the paper)

 

Please refer to this article when publishing results obtained from the toolbox. For any question or comments please contact Hualou Liang.