Author

Jun-Xiang Zhang

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Preprint Sep 2026

BrainTaskonomy: Learning How to Pretrain and What to Transfer in fMRI Foundation Models

fMRI foundation models increasingly aggregate heterogeneous data across brain states, cohorts, and acquisition settings, yet pretraining domains are commonly treated as a flat mixture and downstream tasks are adapted independently. We study whether measured learning relations can organize both stages without modifying...

Jun-Feng Xia, Wen-Hao Ye, Jun-Xiang Zhang et al. · 1 citation

#machine learning Preprint Sep 2026

A Scaling Study for fMRI Foundation Models

Scaling laws have guided large-model development in computer vision and natural language processing, but the relationships among data, model size, and compute remain unclear for functional magnetic resonance imaging (fMRI) foundation models. Here, we conduct a controlled empirical study using pretraining data from more...

Wen-Hao Ye, Xuan-Ye Pan, Jun-Feng Xia et al. · 0 citations