Attention Fusion and Abnormal Brain Topology Neural Network for Mild Depression Recognition

Liangliang Liu*, Jing Zhu, Shuting Sun*, Xiaowei Li*, Guanru Wang, Bin Hu*

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Many studies attempt to explore the underlying mechanisms of depression and distinguish between depression patients and normal controls (NC) using electroencephalography (EEG) techniques. With the advancement of deep learning methods, an increasing number of studies aim to design Computer-Aided Diagnosis (CAD) systems for mild depression (MD) to achieve early identification. However, few studies construct models based on abnormal brain topological structures specific to MD patients. In this study, we investigate the abnormal brain topological structures of individuals with MD based on EEG data obtained during an emotional face paradigm. Functional connectivity analysis reveals a higher proportion of inter-hemispheric connections in the MD group compared to intra-hemispheric connections. Additionally, intra-hemispheric connections are primarily observed within the frontal and parietal lobes of both groups. Hierarchical clustering analysis results indicate impairments in the frontal and parietal lobes in the MD group compared to the NC group. Based on these findings, we propose a novel feature called 'cross-brain feature' and introduce a multi-cross-brain attention fusion mechanism to integrate information between brain regions. We train and test our models using 5-fold cross-validation. The results demonstrate that the classification model based on abnormal brain topological structures achieves the highest performance among the three state-of-the-art algorithms, with an accuracy of 80.1%, an area under the ROC curve (AUC) of 80%, and a sensitivity (SEN) of 86.3%. These findings suggest that combining abnormal brain topological structures derived from functional connectivity matrices with deep learning techniques can provide an effective objective approach to the early detection of depression.

源语言英语
主期刊名Proceedings - 2023 2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023
编辑Xingpeng Jiang, Haiying Wang, Reda Alhajj, Xiaohua Hu, Felix Engel, Mufti Mahmud, Nadia Pisanti, Xuefeng Cui, Hong Song
出版商Institute of Electrical and Electronics Engineers Inc.
2543-2550
页数8
ISBN(电子版)9798350337488
DOI
出版状态已出版 - 2023
已对外发布
活动2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023 - Istanbul, 土耳其
期限: 5 12月 20238 12月 2023

出版系列

姓名Proceedings - 2023 2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

会议

会议2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023
国家/地区土耳其
Istanbul
时期5/12/238/12/23

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