Electroencephalography (EEG) is a non-invasive measurement method for brain activity.
Due to its safety, high resolution, and hypersensitivity to dynamic changes in brain neural …

This study compared the efficacy of Motor Imagery brain-computer interface (MI-BCI)
combined with physiotherapy and physiotherapy alone in ischemic stroke before and after …

The detection of unfavorable driving states (UDS) of drivers based on electroencephalogram
(EEG) measures has received continuous attention from extensive scholars on account of …

Autism spectrum disorder (ASD) is a prevalent neurodevelopmental disorder with severe
cognitive impairment. Several studies have reported that brain functional network …

Objective. Exercise-induced muscle fatigue is a complex physiological phenomenon
involving the central and peripheral nervous systems, and fatigue tolerance varies across …

The research on robustness of brain-like models contributes to promoting its neural
information processing ability, and the understanding of bio-brain function. However, the …

Emotion recognition from electroencephalogram (EEG) data has been a research spotlight
in both academic and industrial communities, which lays a solid foundation to achieve …

Multi-channel electroencephalography (EEG) is used to capture features associated with
motor imagery (MI) based brain-computer interface (BCI) with a wide spatial coverage …

Graph convolutional neural networks (GCN) have attracted much attention in the task of
electroencephalogram (EEG) emotion recognition. However, most features of current GCNs …

Limited by the current experimental techniques and neurodynamical models, the
dysregulation mechanisms of decision-making related neural circuits in major depressive …