Cui Jie, Xu Lei, Bressler Steven L, Ding Mingzhou, Liang Hualou
School of Health Information Science, University of Texas Health Science Center at Houston, 7000 Fannin Street, Suite 600, Houston, TX 77030, USA.
Neural Netw. 2008 Oct;21(8):1094-104. doi: 10.1016/j.neunet.2008.05.007. Epub 2008 Jun 5.
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.
我们开发了一个Matlab/C工具箱Brain-SMART(多元自回归时间序列系统,即BSMART),用于对从多个传感器同时记录的连续神经时间序列数据进行频谱分析。可用功能包括时间序列数据的导入/导出、预处理(归一化和趋势消除)、自回归(AR)建模(多元/双变量模型估计和验证)、频谱量估计(自功率、相干性和格兰杰因果谱)、网络分析(包括相干性和因果网络)以及可视化(包括数据、功率、相干性和因果视图)。该工具箱提供了用于研究频段因果网络结构的工具,这些是其独特功能。所有功能都已集成到一个简单且用户友好的图形用户界面(GUI)环境中,便于访问。尽管我们仅在Windows和Linux操作系统上测试了该工具箱,但BSMART本身与系统无关。此工具箱在GNU公共许可证下可免费获取(http://www.brain-smart.org),用于开源开发。