1 citations · 2 across the 4 of their papers we have counts for
5 papers
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…
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…
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…
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…