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

被引:136
|
作者
Cui, Jie [1 ]
Xu, Lei [1 ]
Bressler, Steven L. [2 ]
Ding, Mingzhou [3 ]
Liang, Hualou [1 ]
机构
[1] Univ Texas Hlth Sci Ctr Houston, Sch Hlth Informat Sci, Houston, TX 77030 USA
[2] Florida Atlantic Univ, Ctr Complex Syst & Brain Sci, Boca Raton, FL 33431 USA
[3] Univ Florida, Dept Biomed Engn, Gainesville, FL 32611 USA
基金
加拿大自然科学与工程研究理事会;
关键词
Open source toolbox; Neural time series; Multivariate signal analysis; Network analysis; Granger causality spectrum;
D O I
10.1016/j.neunet.2008.05.007
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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. (C) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1094 / 1104
页数:11
相关论文
共 50 条
  • [1] Time Series Modeling with MATLAB: The SSpace Toolbox
    Pedregal, Diego J.
    Villegas, Marco A.
    Villegas, Diego A.
    Trapero, Juan R.
    THEORY AND APPLICATIONS OF TIME SERIES ANALYSIS, 2019, : 71 - 84
  • [2] ADAT: A Matlab toolbox for handling time series athlete performance data
    James, Daniel A.
    Wixted, Andrew
    5TH ASIA-PACIFIC CONGRESS ON SPORTS TECHNOLOGY (APCST), 2011, 13 : 451 - 456
  • [3] The Biopsychology—Nonlinear Analysis Toolbox: A Free, Open-Source Matlab-Toolbox for the Non-linear Analysis of Time Series Data
    Christian Beste
    Tobias Otto
    Sven Hoffmann
    Neuroinformatics, 2010, 8 : 197 - 200
  • [4] NPDS toolbox: Neural population (De) synchronization toolbox for MATLAB
    Moayeri, Mohammad Mahdi
    Hemami, Mohammad
    Rad, Jamal Amani
    Parand, Kourosh
    NEUROCOMPUTING, 2022, 506 : 206 - 212
  • [5] The Biopsychology-Nonlinear Analysis Toolbox: A Free, Open-Source Matlab-Toolbox for the Non-linear Analysis of Time Series Data
    Beste, Christian
    Otto, Tobias
    Hoffmann, Sven
    NEUROINFORMATICS, 2010, 8 (03) : 197 - 200
  • [6] Neural network toolbox 3.0 for use with MATLAB™
    Gençay, R
    Selçuk, F
    INTERNATIONAL JOURNAL OF FORECASTING, 2001, 17 (02) : 305 - 317
  • [7] DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation
    Sherfey, Jason S.
    Soplata, Austin E.
    Ardid, Salva
    Roberts, Erik A.
    Stanley, David A.
    Pittman-Polletta, Benjamin R.
    Kopell, Nancy J.
    FRONTIERS IN NEUROINFORMATICS, 2018, 12
  • [8] The NNSYSID toolbox - A MATLAB(R) toolbox for system identification with neural networks
    Norgaard, M
    Ravn, O
    Hansen, LK
    Poulsen, NK
    PROCEEDINGS OF THE 1996 IEEE INTERNATIONAL SYMPOSIUM ON COMPUTER-AIDED CONTROL SYSTEM DESIGN, 1996, : 374 - 379
  • [9] Environmental time series analysis and forecasting with the Captain toolbox
    Taylor, C. James
    Pedregal, Diego J.
    Young, Peter C.
    Tych, Wlodek
    ENVIRONMENTAL MODELLING & SOFTWARE, 2007, 22 (06) : 797 - 814
  • [10] nSTAT: Open-source neural spike train analysis toolbox for Matlab
    Cajigas, I.
    Malik, W. Q.
    Brown, E. N.
    JOURNAL OF NEUROSCIENCE METHODS, 2012, 211 (02) : 245 - 264