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author:

Huang, Zhihua (Huang, Zhihua.) [1] (Scholars:黄志华) | Jiang, Kun (Jiang, Kun.) [2] | Li, Jing (Li, Jing.) [3] | Zhu, Wenxing (Zhu, Wenxing.) [4] (Scholars:朱文兴) | Zheng, Huiru (Zheng, Huiru.) [5] | Wang, Yiwen (Wang, Yiwen.) [6] (Scholars:王益文)

Indexed by:

EI Scopus SCIE

Abstract:

Decision-making is a very important cognitive process in our daily life. There has been increasing interest in the discriminability of single-trial electroencephalogram (EEG) during decision-making. In this study, we designed a machine learning based framework to explore the discriminability of single-trial EEG corresponding to different decisions. For each subject, the framework split the decision-making trials into two parts, trained a feature model and a classifier on the first part, and evaluated the discriminability on the second part using the feature model and classifier. A proposed algorithm and five existing algorithms were applied to fulfill the feature models, and the algorithm Linear Discriminative Analysis (LDA) was used to implement the classifiers. We recruited 21 subjects to participate in Chicken Game (CG) experiments. The results show that there exists the discriminability of single-trial EEG between the cooperation and aggression decisions during the CG experiments, with the classification accuray of 75% (+/- 6%), and the discriminability is mainly from the EEG information below 40 Hz. The further analysis indicates that the contributions of different brain regions to the discriminability are consistent with the existing knowledge on the cognitive mechanism of decision-making, confirming the reliability of the conclusions. This study exhibits that it is feasible to apply machine learning methods to EEG analysis of decision-making cognitive process.

Keyword:

Adaptive frequency common spatial pattern Chicken game Decision-making Discriminability of single-trial EEG

Community:

  • [ 1 ] [Huang, Zhihua]Fuzhou Univ, Coll Comp & Data Sci, Fuzhou 350108, Peoples R China
  • [ 2 ] [Jiang, Kun]Fuzhou Univ, Coll Comp & Data Sci, Fuzhou 350108, Peoples R China
  • [ 3 ] [Li, Jing]Fuzhou Univ, Coll Comp & Data Sci, Fuzhou 350108, Peoples R China
  • [ 4 ] [Zhu, Wenxing]Fuzhou Univ, Sch Math & Stat, Fuzhou 350108, Peoples R China
  • [ 5 ] [Zheng, Huiru]Ulster Univ, Sch Comp, Belfast, Antrim, North Ireland
  • [ 6 ] [Wang, Yiwen]Fuzhou Univ, Sch Econ & Management, Fuzhou 350108, Peoples R China

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Source :

MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING

ISSN: 0140-0118

Year: 2022

Issue: 8

Volume: 60

Page: 2217-2227

3 . 2

JCR@2022

2 . 6 0 0

JCR@2023

ESI Discipline: ENGINEERING;

ESI HC Threshold:66

JCR Journal Grade:2

CAS Journal Grade:3

Cited Count:

WoS CC Cited Count: 4

SCOPUS Cited Count: 3

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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