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Interaction Between Dynamic Affection and Arithmetic Cognitive Ability: A Practical Investigation With EEG Measurement.

Authors :
Yang, Xiaonan
Peng, Yilu
Han, Yuyang
Li, Fangyi
Zhang, Qin
Wu, Shuo
Wu, Xia
Source :
IEEE Transactions on Affective Computing; Jul-Sep2024, Vol. 15 Issue 3, p1427-1438, 12p
Publication Year :
2024

Abstract

Emotions play an essential role in affecting the performance of cognitive abilities in continuous cognitive tasks. Most previous studies share a common issue in that the evoked emotions are simply presumed to be real emotions, without taking into account the observation that emotions may be changed when carrying out cognitive activities. This may lead to the inaccurate detection of true emotions, which further adversely affects the investigation of interactions between emotion and cognition. To address this challenging problem, the present work develops an innovative study using EEG measurement to investigate the interaction between dynamic affection and cognitive ability. In particular, a real-time emotion detection model by the use of physiological signals (i.e., EEG) is constructed, to dynamically monitor the current emotional state. Given the observed emotion, the analysis of the interaction between cognitive abilities and dynamic emotions is undertaken from the perspectives of both behavioral performance and brain mechanisms. Research outcomes indicate that emotions are not stable, and are indeed dynamically changed by cognitive performance. Meanwhile, cognitive activities also influence the brain activation pattern revealed under different emotions, which validates the necessity of introducing the dynamic emotion monitoring model. In addition, the best performance has been found when the emotional state is neutral in terms of accuracy and response time. The results of this study provide a potential basis for assessing the cognitive abilities of individuals with different emotions in a variety of applications of cognitive scenarios. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19493045
Volume :
15
Issue :
3
Database :
Complementary Index
Journal :
IEEE Transactions on Affective Computing
Publication Type :
Academic Journal
Accession number :
179509542
Full Text :
https://doi.org/10.1109/TAFFC.2023.3347391