BSMART: A Matlab/C toolbox for analysis of multichannel neural time series

• Published in: Neural networks Vol. 21; no. 8; pp. 1094 - 1104
• Main Authors: Cui, Jie, Xu, Lei, Bressler, Steven L., Ding, Mingzhou, Liang, Hualou
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01-10-2008
• Subjects: Action Potentials - physiology; Animals; Computational Biology; Granger causality spectrum; Multivariate signal analysis; Network analysis; Neural Networks (Computer); Neural time series; Neurons - physiology; Open source toolbox; Signal Processing, Computer-Assisted - instrumentation; Software; Statistics as Topic - instrumentation; Statistics as Topic - methods; Time Factors; Open source toolbox; Multivariate signal analysis; Granger causality spectrum; Neural time series; Network analysis
• ISSN: 0893-6080; 1879-2782
• DOI: 10.1016/j.neunet.2008.05.007

We have developed a Matlab/C toolbox, Brain-SMART (System for Multivariate AutoRegressive Time series, or BSMART), for spectral analysis of continuous neural time series data recorded simultaneously from multiple sensors. Available functions include time series data importing/exporting, preprocessing (normalization and trend removal), AutoRegressive (AR) modeling (multivariate/bivariate model estimation and validation), spectral quantity estimation (auto power, coherence and Granger causality spectra), network analysis (including coherence and causality networks) and visualization (including data, power, coherence and causality views). The tools for investigating causal network structures in respect of frequency bands are unique functions provided by this toolbox. All functionality has been integrated into a simple and user-friendly graphical user interface (GUI) environment designed for easy accessibility. Although we have tested the toolbox only on Windows and Linux operating systems, BSMART itself is system independent. This toolbox is freely available (http://www.brain-smart.org) under the GNU public license for open source development.