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20242026
most citedDynamic-Attention-based EEG State Transition Modeling for Emotion Recognition

1 citations · 1 across the 5 of their papers we have counts for

collaborators

7 papers

cs.LG2026

GeoNIRS: Geometry-Aware Pretraining for Heterogeneous fNIRS Representation Learning

Zongsheng Li, Shengyuan Zhu, Zimo Zhang +3

Functional near-infrared spectroscopy (fNIRS) provides portable and spatially localized measurements of cortical hemodynamics, but differences in channel count, probe layout, signa…

cs.LG2026

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…

q-bio.NC2026

A geometry aware framework enhances noninvasive mapping of whole human brain dynamics

Song Wang, Kexin Lou, Chen Wei +8

Non-invasive electrophysiology lacks methods that accurately reconstruct whole-brain spatiotemporal dynamics while incorporating individual cortical geometry, leaving current elect…

cs.CV2026

Forecasting Epileptic Seizures from Contactless Camera via Cross-Species Transfer Learning

Mingkai Zhai, Wei Wang, Zongsheng Li +1

Epileptic seizure forecasting is a clinically important yet challenging problem in epilepsy research. Existing approaches predominantly rely on neural signals such as electroenceph…

cs.LG2025

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…

cs.HC2024★ 1 cited

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…

q-bio.NC2024

Contrastive Learning of Shared Spatiotemporal EEG Representations Across Individuals for Naturalistic Neuroscience

Xinke Shen, Lingyi Tao, Xuyang Chen +3

Neural representations induced by naturalistic stimuli offer insights into how humans respond to stimuli in daily life. Understanding neural mechanisms underlying naturalistic stim…