首页    期刊浏览 2024年11月05日 星期二
登录注册

文章基本信息

  • 标题:LIMO EEG: A Toolbox for Hierarchical LInear MOdeling of ElectroEncephaloGraphic Data
  • 本地全文:下载
  • 作者:Cyril R. Pernet ; Nicolas Chauveau ; Carl Gaspar
  • 期刊名称:Computational Intelligence and Neuroscience
  • 印刷版ISSN:1687-5265
  • 电子版ISSN:1687-5273
  • 出版年度:2011
  • 卷号:2011
  • DOI:10.1155/2011/831409
  • 出版社:Hindawi Publishing Corporation
  • 摘要:Magnetic- and electric-evoked brain responses have traditionally been analyzed by comparing the peaks or mean amplitudes of signals from selected channels and averaged across trials. More recently, tools have been developed to investigate single trial response variability (e.g., EEGLAB) and to test differences between averaged evoked responses over the entire scalp and time dimensions (e.g., SPM, Fieldtrip). LIMO EEG is a Matlab toolbox (EEGLAB compatible) to analyse evoked responses over all space and time dimensions, while accounting for single trial variability using a simple hierarchical linear modelling of the data. In addition, LIMO EEG provides robust parametric tests, therefore providing a new and complementary tool in the analysis of neural evoked responses.
国家哲学社会科学文献中心版权所有