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Emotional brain network decoded by biological spiking neural network

文献类型：期刊论文

作者Xu, Hubo1,6,7; Cao, Kexin1,6,7; Chen, Hongguang2; Abudusalamu, Awuti1,6,7; Wu, Wei3; Xue, Yanxue4,5,6,7
刊名FRONTIERS IN NEUROSCIENCE
出版日期2023-07-11
卷号17页码:17
关键词emotion affective computing brain network neural oscillation neuroregulation self-backpropagation spiking neural network brain-computer interface
DOI10.3389/fnins.2023.1200701
通讯作者Wu, Wei(wei.wu@ia.ac.cn) ; Xue, Yanxue(yanxuexue@bjmu.edu.cn)
英文摘要IntroductionEmotional disorders are essential manifestations of many neurological and psychiatric diseases. Nowadays, researchers try to explore bi-directional brain-computer interface techniques to help the patients. However, the related functional brain areas and biological markers are still unclear, and the dynamic connection mechanism is also unknown. MethodsTo find effective regions related to different emotion recognition and intervention, our research focuses on finding emotional EEG brain networks using spiking neural network algorithm with binary coding. We collected EEG data while human participants watched emotional videos (fear, sadness, happiness, and neutrality), and analyzed the dynamic connections between the electrodes and the biological rhythms of different emotions. ResultsThe analysis has shown that the local high-activation brain network of fear and sadness is mainly in the parietal lobe area. The local high-level brain network of happiness is in the prefrontal-temporal lobe-central area. Furthermore, the & alpha; frequency band could effectively represent negative emotions, while the & alpha; frequency band could be used as a biological marker of happiness. The decoding accuracy of the three emotions reached 86.36%, 95.18%, and 89.09%, respectively, fully reflecting the excellent emotional decoding performance of the spiking neural network with self- backpropagation. DiscussionThe introduction of the self-backpropagation mechanism effectively improves the performance of the spiking neural network model. Different emotions exhibit distinct EEG networks and neuro-oscillatory-based biological markers. These emotional brain networks and biological markers may provide important hints for brain-computer interface technique exploration to help related brain disease recovery.
WOS关键词EEG DATA ; RECOGNITION
资助项目National Natural Science Foundation of China[-32161143022] ; National Natural Science Foundation of China[81871046] ; National Natural Science Foundation of China[2022ZD0214500] ; National Natural Science Foundation of China[Z221100007422052]
WOS研究方向Neurosciences & Neurology
语种英语
出版者FRONTIERS MEDIA SA
WOS记录号WOS:001032453400001
资助机构National Natural Science Foundation of China
源URL[http://ir.ia.ac.cn/handle/173211/53786]  
专题多模态人工智能系统全国重点实验室
通讯作者Wu, Wei; Xue, Yanxue
作者单位1.Peking Univ, Sch Basic Med Sci, Dept Pharmacol, Beijing, Peoples R China
2.Peking Univ, Peking Univ Hosp 6, Inst Mental Hlth, Peking Univ Hosp 6,NHC Key Lab Mental Hlth, Beijing, Peoples R China
3.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing, Peoples R China
4.Chinese Inst Brain Res, Beijing, Peoples R China
5.Peking Univ, Key Lab Neurosci, Minist Educ, Natl Hlth Commiss, Beijing, Peoples R China
6.Peking Univ, Natl Inst Drug Dependence, Beijing, Peoples R China
7.Peking Univ, Beijing Key Lab Drug Dependence, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Xu, Hubo,Cao, Kexin,Chen, Hongguang,et al. Emotional brain network decoded by biological spiking neural network[J]. FRONTIERS IN NEUROSCIENCE,2023,17:17.
APA Xu, Hubo,Cao, Kexin,Chen, Hongguang,Abudusalamu, Awuti,Wu, Wei,&Xue, Yanxue.(2023).Emotional brain network decoded by biological spiking neural network.FRONTIERS IN NEUROSCIENCE,17,17.
MLA Xu, Hubo,et al."Emotional brain network decoded by biological spiking neural network".FRONTIERS IN NEUROSCIENCE 17(2023):17.

入库方式： OAI收割

来源：自动化研究所

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