4 papers · 1 filter
BrainBench: Benchmarking Large Language Models for Comprehensive EEG Understanding
Yangxuan Zhou, Yuning Chen, Chen Wu +4
Electroencephalography (EEG) analysis extends beyond assigning predefined labels to recordings; it requires workflows connecting natural-language instructions, signal processing, q…
BrainAgent: A Large Language Model-Driven Multi-Agent Framework for Autonomous Brain Signal Understanding
Yangxuan Zhou, Sha Zhao, Jiquan Wang +2
Brain-Computer Interfaces (BCIs) and brain signal understanding are pivotal for clinical health and next-generation interactions. Despite this significance, its widespread adoption…
EvoBrain: Continual Learning of EEG Foundation Models Across Heterogeneous BCI Tasks
Yangxuan Zhou, Sha Zhao, Jiquan Wang +2
Electroencephalography (EEG) is the cornerstone of non-invasive brain-computer interfaces (BCIs), yet conventional decoding relies on fragmented, task-specific architectures that s…
SPICED: A Synaptic Homeostasis-Inspired Framework for Unsupervised Continual EEG Decoding
Yangxuan Zhou, Sha Zhao, Jiquan Wang +4
Human brain achieves dynamic stability-plasticity balance through synaptic homeostasis. Inspired by this biological principle, we propose SPICED: a neuromorphic framework that inte…