3 papers
eess.SP2026
EEG-JEPA: Structured Latent Prediction for EEG Foundation Models
Jinhao Li, Zhiyuan Ma, Xueqiao Han +8
Electroencephalography (EEG) foundation models aim to learn reusable representations from large-scale unlabeled recordings. A common pretraining strategy is masked waveform reconst…
q-bio.NC2026
Training-Driven Representational Geometry Modularization Predicts Brain Alignment in Language Models
Yixuan Liu, Zhiyuan Ma, Likai Tang +5
How large language models (LLMs) align with the neural representation and computation of human language is a central question in cognitive science. Using representational geometry…
cs.HC2024
Dynamic-Attention-based EEG State Transition Modeling for Emotion Recognition
Xinke Shen, Runmin Gan, Kaixuan Wang +5
Electroencephalogram (EEG)-based emotion decoding can objectively quantify people's emotional state and has broad application prospects in human-computer interaction and early dete…