Paper Info
Title
Time-Frequency Analysis Of Electroencephalogram Signals In A Cognitive Decision-Making Task
Abstract
Choices and decisions involve a series of complex cognitive processes, and the time-frequency analysis of electroencephalogram (EEG) signals can help understand the brain activities in different cognitive tasks. In this study, a decision-making cognitive task of rock-paper-scissors was designed, and the complex decision-making task was divided into three stages (decision planning, confirmation, and feedback). 64 channels of EEG signals were simultaneously recorded using the Neuroscan QuikCap system during the whole task. The average spectral power and phase synchronization values of each frequency band (delta, theta, alpha and beta band) were extracted and compared within and across different stages. The results showed the desire to win or not to lose within the first stage might be accompanied by the increase of alpha and theta components. In the second stage, the spectral power inhibition of alpha wave and phase synchronization increase of delta wave indicated that subjects would improve their attentions when they confirmed their choice. In the third stage, the theta increased effect and alpha decreased effect were related to different feedback. This pilot study suggests that the time-frequency analysis of EEG signals could be a great tool to visualize the brain activities in response to different cognitive tasks.
Year
DOI
Venue
2020
10.1109/EMBC44109.2020.9176202
42ND ANNUAL INTERNATIONAL CONFERENCES OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY: ENABLING INNOVATIVE TECHNOLOGIES FOR GLOBAL HEALTHCARE EMBC'20
Keywords
DocType
Volume
time-frequency analysis, electroencephalogram signals, cognitive tasks
Conference
2020
ISSN
Citations 
PageRank 
1557-170X
0
0.34
References 
Authors
0
9
Name
Order
Citations
PageRank
Cheng Wang100.34
Mingxing Zhu216.03
Xin Wang3587177.85
Xiaochen Wang400.34
Haoshi Zhang512.79
Hanjie Deng601.35
Han Cui701.01
Shixiong Chen82512.77
Guanglin Li931457.23