Multi-timescale hybrid components of the functional brain connectome: A bimodal EEG-fMRI decomposition. Abstract Concurrent electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) bridge brain connectivity
Acupuncture Relaxation, Vigilance Stage, and Autonomic Nervous System Function: A Comparative Study of Their Interrelationships. Abstract Objective: During acupuncture stimulation, autonomic nervous system (ANS) function
Pain phenotypes classified by machine learning using electroencephalography features. Abstract Pain is a multidimensional experience mediated by distributed neural networks in the brain. To study
Precise Slow Oscillation-Spindle Coupling Promotes Memory Consolidation in Younger and Older Adults. Abstract Memory consolidation during sleep relies on the precisely timed interaction of rhythmic
Effects of load and emotional state on EEG alpha-band power and inter-site synchrony during a visual working memory task. Abstract Motivationally/emotionally engaging stimuli are strong
Generative Adversarial Networks-Based Data Augmentation for Brain-Computer Interface. Abstract The performance of a classifier in a brain-computer interface (BCI) system is highly dependent on the
Combined Phase-Rate Coding by Persistently Active Neurons as a Mechanism for Maintaining Multiple Items in Working Memory in Humans. Abstract Maintaining multiple items in working
Decoding multiclass motor imagery EEG from the same upper limb by combining Riemannian geometry features and partial least squares regression. Abstract OBJECTIVE: Due to low
Brain Network Analysis by Stable and Unstable EEG Components. Abstract OBJECTIVE: Previous studies have already shown that electroencephalography (EEG) brain network (BN) can reflect the
Decoding kinetic features of hand motor preparation from single-trial EEG using convolutional neural networks. Abstract Building accurate movement decoding models from brain signals is crucial
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