29 citations · 91 across the 15 of their papers we have counts for
4 papers · 1 filter
DEFT: Disentanglement-Enhanced Fine-Tuning for EEG Foundation Models
Yuqiu Deng, Muyun Jiang, Zongpeng Zhang +8
EEG foundation models (EFMs) have improved EEG representation learning by transferring knowledge from large-scale multi-subject pretraining to downstream tasks. However, their pret…
Natural Image Autoencoder-Based fMRI Representations for Trait and State Prediction
Juhyeon Park, Yeonwoo Kim, Peter Yongho Kim +5
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-spec…
Beyond representational alignment with brain-guided language models for robust reasoning
Mingqing Xiao, Kai Du, Zhouchen Lin
The correspondence between large language models (LLMs) and the neural mechanisms underlying human higher-order cognition remains insufficiently characterized. Given that language…
Kuramoto Oscillatory Phase Encoding: Neuro-inspired Synchronization for Improved Learning Efficiency
Mingqing Xiao, Yansen Wang, Dongqi Han +2
Spatiotemporal neural dynamics and oscillatory synchronization are widely implicated in biological information processing and have been hypothesized to support flexible coordinatio…