上海大学学报(自然科学版)

• 通信与信息工程 • 上一篇    下一篇

心算任务下脑电信息传输

李颖洁,石菁,朱春妍,樊飞燕
  

  1. 上海大学 通信与信息工程学院,上海 200072
  • 收稿日期:2007-01-17 修回日期:1900-01-01 出版日期:2007-08-20 发布日期:2007-08-20
  • 通讯作者: 李颖洁

Information Transmission of Electroencephalogram Signal During Mental Arithmetic

LI Ying-jie, SHI Jing, ZHU Chun-yan, FAN Fei-yan
  

  1. School of Communication and Information Engineering, Shanghai University, Shanghai 200072, China
  • Received:2007-01-17 Revised:1900-01-01 Online:2007-08-20 Published:2007-08-20
  • Contact: LI Ying-jie

摘要: 通过计算多导脑电的互信息传输时间序列的复杂度,研究了心算任务和安静状态下不同认知水平的对象脑电特异表现.结果表明,不同的实验状态、不同认知能力的被试者以及大脑的不同部位均可对互信息复杂度产生显著影响.抑郁症在心算任务下的互信息传输复杂度显著低于(P<0.001)安静闭目状态下的复杂度,而正常对照组虽然在心算任务下的脑电互信息传输复杂度也较安静闭目状态时有所下降,但不具有统计意义.据此推测,完成认知作业时的脑电互信息复杂度在一定程度上反映了认知水平的不同.

关键词: 互信息复杂度, 脑电
,
认知功能

Abstract: Based on calculation of the complexity of mutual information transmission time series obtained from multi-channel EEG signals, this paper gives the main results of our studies on the characteristics in EEGs from subjects with different cognition levels and under different conditions. These conditions include doing mental arithmetic and resting with eyes closed. Our results show that all experiment conditions, cognition levels and areas of the brain have influences on the value of mutual information complexity of EEG time series. Those with depression problems have a significant lower (P<0.001) complexity under arithmetic task than that under resting conditions. However, the difference in the normal group is not significant. We conclude therefore that the mutual information complexity of EEG time series demonstrates the cognition level of the subjects to some degree.

Key words: cognitive function, electroencephalogram (EEG)
,
mutual information complexity

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