Journal article
BSMART: A Matlab/C toolbox for analysis of multichannel neural time series
Neural networks, v 21(8), pp 1094-1104
Oct 2008
PMID: 18599267
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
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.
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Details
- Title
- BSMART: A Matlab/C toolbox for analysis of multichannel neural time series
- Creators
- Jie Cui - School of Health Information Science, University of Texas Health Science Center at Houston, 7000 Fannin Street, Suite 600, Houston, TX 77030, USALei Xu - School of Health Information Science, University of Texas Health Science Center at Houston, 7000 Fannin Street, Suite 600, Houston, TX 77030, USASteven L Bressler - Center for Complex Systems and Brain Sciences, Florida Atlantic University, Boca Raton, FL 33431, USAMingzhou Ding - Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USAHualou Liang - School of Health Information Science, University of Texas Health Science Center at Houston, 7000 Fannin Street, Suite 600, Houston, TX 77030, USA
- Publication Details
- Neural networks, v 21(8), pp 1094-1104
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000261028300007
- Scopus ID
- 2-s2.0-53249113374
- Other Identifier
- 991014878220404721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Neurosciences