4 papers · 1 filter
Beyond Flattened Tokens: Structure-Preserving EEG Decoding with Reusable TriDim Blocks
Shiyue Su, Song Wang, Zekai Zhan +7
Effective EEG decoding requires representations that preserve organization among channels, local waveform dynamics, and long-range temporal context. Existing EEG architectures ofte…
Rethinking EEG-Based Disease Diagnosis: Decoupling Instance Representation Learning from Subject-Level Supervision
Zhiyuan Ma, Zeyuan Li, Zhiyi Lu +7
EEG-based disease diagnosis requires one prediction per subject, yet common pipelines segment recordings into short instances, inherit the subject label for every instance, and tra…
OmniEEG-Bench: A Standardized Evaluation Benchmark for EEG Foundation Models
Ziling Lu, Zongsheng Li, Xinke Shen +11
Electroencephalography (EEG) supports a variety of brain-computer interface (BCI) tasks ranging from brain-state monitoring to human-LLM interactions. EEG foundation models are eme…
Multi-dataset Joint Pre-training of Emotional EEG Enables Generalizable Affective Computing
Qingzhu Zhang, Jiani Zhong, Zongsheng Li +2
Task-specific pre-training is essential when task representations diverge from generic pre-training features. Existing task-general pre-training EEG models struggle with complex ta…