Identifying Individualized Functional Brain Networks: An Unsupervised Deep Temporal Attention Based Autoencoder Model

Identifying functional brain networks (FBNs) under naturalistic stimuli is crucial for understanding the brain function. While numerous studies have employed deep learning methods to model neural responses, most of them overlook self-attention mechanism of brain and the temporal dependencies in neur...

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Veröffentlicht in:	Proceedings (International Symposium on Biomedical Imaging) S. 1 - 5
Hauptverfasser:	Wang, Kexin, Ren, Yudan, Liu, Zhengyang, Yin, Song, Ding, Zhenqing, Li, Xiao, He, Xiaowei
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 27.05.2024
Schlagworte:	Brain modeling Correlation Deep learning FBN identification Feature extraction Fingerprint recognition Individualized FBNs Naturalistic fMRI Neural activity Self-attention mechanisms Vectors
ISSN:	1945-8452
Online-Zugang:	Volltext
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