文献类型：期刊文献

英文题名：Brain Emotion Perception Inspired EEG Emotion Recognition With Deep Reinforcement Learning

作者：Li, Dongdong[1];Xie, Li[1];Wang, Zhe[1];Yang, Hai[1]

机构：[1]East China Univ Sci & Technol, Dept Comp Sci & Engn, Shanghai 200237, Peoples R China

年份：2024

卷号：35

期号：9

起止页码：12979

外文期刊名：IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS

收录：;EI(收录号：20232114131781);WOS:【SCI-EXPANDED(收录号:WOS:000986553700001)】；

基金：This work was supported in part by the Natural Science Foundation of China under Grant 62276098 and Grant 62076094; in part by the Shanghai Science and Technology Program-Federated-based cross-domain and cross-task incremental learning-under Grant 21511100800; and in part by the Shanghai Science and Technology Program-Distributed and generative few-shot algorithm and theory research-under Grant 20511100600

语种：英文

外文关键词：Thalamus; Frontal lobe; Reinforcement learning; Electroencephalography; Emotion recognition; Hypothalamus; Brain modeling; Electroencephalogram (EEG); emotion perception; emotion recognition; reinforcement learning

摘要：Inspired by the well-known Papez circuit theory and neuroscience knowledge of reinforcement learning, a double dueling deep $Q$ network (DQN) is built incorporating the electroencephalogram (EEG) signals of the frontal lobe as prior information, which is named frontal lobe double dueling DQN (FLD3QN). The framework of FLD3QN is constructed in accord with the brain emotion mechanism which takes the frontal lobe and the thalamus as the core, in which the part of the Papez circuit is simulated by the bifrontal lobe residual convolution neural network (BiFRCNN). Moreover, a step penalty factor is designed to constrain the number of mistakes of the agent. The ablation studies results on the public EEG emotion dataset DEAP verified the important roles of the frontal lobe and the Papez circuit in modeling the procedure of learning rewards during the perception of emotions, with a great increase in the average accuracies by 25.24% and 23.31% in valence and arousal dimensions.