5 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…
A Pre-trained EEG-to-MEG Generative Framework for Enhancing BCI Decoding
Zhuo Li, Shuqiang Wang
Electroencephalography (EEG) and magnetoencephalography (MEG) play important and complementary roles in non-invasive brain-computer interface (BCI) decoding. However, compared to t…
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…
ConnectomeDiffuser: Generative AI Enables Brain Network Construction from Diffusion Tensor Imaging
Xuhang Chen, Michael Kwok-Po Ng, Kim-Fung Tsang +2
Brain network analysis plays a crucial role in diagnosing and monitoring neurodegenerative disorders such as Alzheimer's disease (AD). Existing approaches for constructing structur…
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…