6 papers
Brain-DiT: A Universal Multi-state fMRI Foundation Model with Metadata-Conditioned Pretraining
Junfeng Xia, Wenhao Ye, Xuanye Pan +3
Current fMRI foundation models primarily rely on a limited range of brain states and mismatched pretraining tasks, restricting their ability to learn generalized representations ac…
BrainWorld: A Structural-Prior-Conditioned Generative Model for Whole-Brain 4D fMRI Dynamics
Junfeng Xia, Wenhao Ye, Junxiang Zhang +3
Whole-brain 4D fMRI generation is valuable for modeling functional brain dynamics, yet existing fMRI foundation models mainly target representation learning and downstream predicti…
OpTI-Mouse: Optimization for Targeted Temporal Interference Stimulation in the Mouse Brain
Jingsheng Tang, Zhengkang Zhou, Yingyue Xin +4
Temporal Interference (TI) stimulation enables deep brain targeting, yet precise optimization tools for mouse models remain limited. We developed a computational optimization tool…
FlexiBrain: Resolution-Agnostic Voxel-Level Encoding for Native fMRI
Mo Wang, Wenhao Ye, Junfeng Xia +3
The success of large-scale deep learning models in neuroscience is fundamentally constrained by severe data heterogeneity. Native fMRI data aggregated from diverse sources exhibit…
Personalized Transcranial Electrical Stimulation: A Review of Computational Modeling and Optimization
Mo Wang, Kexin Zheng, Yingyue Xin +8
Objective. Personalized transcranial electrical stimulation (tES) has gained growing attention due to the substantial inter-individual variability in brain anatomy and physiology.…
DCA: Graph-Guided Deep Embedding Clustering for Brain Atlases
Mo Wang, Kaining Peng, Jingsheng Tang +2
Brain atlases are essential for reducing the dimensionality of neuroimaging data and enabling interpretable analysis. However, most existing atlases are predefined, group-level tem…