6 papers
Aligning Shared and Routed Experts for Cross-Subject EEG Generalization
Zhi Zhang, Yan Liu, Zhejing Hu +7
Cross-subject EEG generalization is challenging due to substantial heterogeneity across subjects. Existing methods typically learn either a shared subject-invariant model or multip…
Bridging scalp and intracranial EEG in BCI via pretrained neural representations and geometric constraint embedding
Yihang Dong, Changhong Jing, Shuqiang Wang
Electroencephalography (EEG) has become one of the key modalities underpinning brain-computer interfaces (BCIs) due to its high temporal resolution, rapid responsiveness, non-invas…
Generative AI Enables Structural Brain Network Construction from fMRI via Symmetric Diffusion Learning
Qiankun Zuo, Bangjun Lei, Wanyu Qiu +3
Mapping from functional connectivity (FC) to structural connectivity (SC) can facilitate multimodal brain network fusion and discover potential biomarkers for clinical implications…
PTSM: Physiology-aware and Task-invariant Spatio-temporal Modeling for Cross-Subject EEG Decoding
Changhong Jing, Yan Liu, Shuqiang Wang +5
Cross-subject electroencephalography (EEG) decoding remains a fundamental challenge in brain-computer interface (BCI) research due to substantial inter-subject variability and the…
Brain Network Analysis Based on Fine-tuned Self-supervised Model for Brain Disease Diagnosis
Yifei Tang, Hongjie Jiang, Changhong Jing +2
Functional brain network analysis has become an indispensable tool for brain disease analysis. It is profoundly impacted by deep learning methods, which can characterize complex co…
BG-GAN: Generative AI Enable Representing Brain Structure-Function Connections for Alzheimer's Disease
Tong Zhou, Chen Ding, Changhong Jing +8
The relationship between brain structure and function is critical for revealing the pathogenesis of brain disorders, including Alzheimer's disease (AD). However, mapping brain stru…