Author

Jun Yan

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Open access Sep 2026

Interpretable Multiscale Directed Temporal Graph Learning for MEG-Based Identification and Lateralization of Temporal Lobe Epilepsy

Objective: To address the limitations of existing deep learning methods for brain networks in jointly modeling directional interregional connectivity, multiband information, and short-term dynamic features, this study proposes a multiscale directed temporal graph convolutional network (MSD-STGNN) for the three-class cl...

Yi-Lin Jiang, He Wang, Jun Yan et al. · Italian National Conference... · 0 citations

Open access Jan 2026

Network Analysis of Sensory Phenomena and Obsessive‐Compulsive Symptoms in OCD: A Multicenter Study

Background Sensory phenomena (SP) affect 60%–80% of obsessive‐compulsive (OC) disorder (OCD) patients, demonstrate dimension‐specific symptom associations, yet their mechanistic role in OCD’s network architecture remains unexamined. Methods In this cross‐sectional study, 1350 clinician‐diagnosed OCD patients from the C...

Yue Sun, Xuedi Zhang, Wen-Xin Tang et al. · Depression and Anxiety · 0 citations

Jul 2026

Enhanced multimodal MRI classification of schizophrenia through cross-attention graph neural networks

Findings indicate that anatomically grounded node-level multimodal fusion can improve classification performance while preserving neurobiological interpretability, thereby providing a principled framework for multimodal schizophrenia classification and biomarker discovery.

Jing-Jing Gao, J. Wu, Mao-Min Qian et al. · Medical Image Anal. · 0 citations