Publications (5)
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…
A geometry aware framework enhances noninvasive mapping of whole human brain dynamics
Song Wang, Kexin Lou, Chen Wei +8
Non-invasive electrophysiology lacks methods that accurately reconstruct whole-brain spatiotemporal dynamics while incorporating individual cortical geometry, leaving current elect…
SLIM-Brain: A Data- and Training-Efficient Foundation Model for fMRI Data Analysis
Mo Wang, Junfeng Xia, Wenhao Ye +5
Foundation models are emerging as a powerful paradigm for fMRI analysis, but current approaches face a dual bottleneck of data- and training-efficiency. Atlas-based methods aggrega…
Mapping effective connectivity by virtually perturbing a surrogate brain
Zixiang Luo, Kaining Peng, Zhichao Liang +6
Effective connectivity (EC), indicative of the causal interactions between brain regions, is fundamental to understanding information processing in the brain. Traditional approache…
Uncovering cognitive taskonomy through transfer learning in masked autoencoder-based fMRI reconstruction
Youzhi Qu, Junfeng Xia, Xinyao Jian +5
Data reconstruction is a widely used pre-training task to learn the generalized features for many downstream tasks. Although reconstruction tasks have been applied to neural signal…