Author

Dongqi Han

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Preprint Sep 2026

Natural Image Autoencoder-Based fMRI Representations for Trait and State Prediction

Foundation models pre-trained on large-scale fMRI datasets have shown strong downstream performance, but at substantial data and computation cost. To investigate how much fMRI-specific pre-training is actually needed for such performance, we introduce FReD, which derives fMRI representations from a frozen Deep Compress...

Juhyeon Park, Yeonwook Kim, P. Y. Kim et al. · 0 citations

Open access Jul 2026

From Hodgkin-Huxley to Pretrained Neural Inference AI

By pre-training artificial neural networks exclusively on large-scale synthetic data, this work demonstrates robust zero-shot generalization across diverse brain regions, experimental paradigms and species, enabling the accurate inference of single-unit activities and cell-type properties without exposure to real data.

Yimu Zhang, Dong-Qi Han, Zhen-Ning Lv et al. · bioRxiv · 0 citations