1 citations · 3 across the 9 of their papers we have counts for
9 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…
A New Brain Network Construction Paradigm for Brain Disorder via Diffusion-based Graph Contrastive Learning
Yongcheng Zong, Shuqiang Wang
Brain network analysis plays an increasingly important role in studying brain function and the exploring of disease mechanisms. However, existing brain network construction tools h…
BDHT: Generative AI Enables Causality Analysis for Mild Cognitive Impairment
Qiankun Zuo, Ling Chen, Yanyan Shen +3
Effective connectivity estimation plays a crucial role in understanding the interactions and information flow between different brain regions. However, the functional time series u…
BrainNetDiff: Generative AI Empowers Brain Network Generation via Multimodal Diffusion Model
Yongcheng Zong, Shuqiang Wang
Brain network analysis has emerged as pivotal method for gaining a deeper understanding of brain functions and disease mechanisms. Despite the existence of various network construc…
Alzheimer's Disease Prediction via Brain Structural-Functional Deep Fusing Network
Qiankun Zuo, Junren Pan, Shuqiang Wang
Fusing structural-functional images of the brain has shown great potential to analyze the deterioration of Alzheimer's disease (AD). However, it is a big challenge to effectively f…
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…