Neural decoding of speech intention could advance the development and application of brain-computer interface (BCI) technology. Currently, lack of dataset limited the research on decoding the true speech intention, especially the diverse intentions e...
Improving language learning through a better understanding of how brain activity and emotional intelligence interact is a promising research direction with practical value in education. Traditional methods in this area often use static models, which ...
Video-electroencephalography (vEEG) monitoring is currently the reference standard in the diagnosis of epilepsy. Manual analysis of vEEG recordings is time-consuming and inter-rater agreement is low even when the annotation is done by experienced doc...
International journal of neural systems
Oct 18, 2025
Decoding electroencephalographic (EEG) signals is of key importance in the development of brain-computer interface (BCI) systems. However, high inter-subject variability in EEG signals requires user-specific calibration, which can be time-consuming a...
BACKGROUND: Depression exhibits significant heterogeneity in antidepressant treatment response. This study aimed to develop an Electroencephalography (EEG)-based machine learning model integrating multidimensional features to predict selective seroto...
. Deep learning has emerged as a powerful approach for decoding electroencephalography (EEG)-based brain-computer interface (BCI) signals. However, its effectiveness is often limited by the scarcity and variability of available training data. Existin...
BACKGROUND: Depression is a major public health concern, with a rising prevalence among adolescents and young adults. However, the neural mechanisms underlying depressive symptoms remain poorly understood. This study aimed to identify patterns of alt...
Transcranial Electrical Stimulation (tES) is a non-invasive neuromodulation technique that generates artifacts in simultaneous EEG recordings, hindering brain activity analysis. This study analyzes Machine Learning (ML) methods for tES noise artifact...
This study assessed whether resting-state quantitative EEG (qEEG) can differentiate tinnitus laterality under rigorous multiple-comparison control and nested, cross-validated machine learning (ML). We analyzed 210 pre-specified qEEG features-spectral...
Alzheimer's disease (AD) is a progressive neurological disorder that causes brain cell degeneration and leads to dementia. Early and accurate detection of AD is crucial, as it allows timely treatment before the brain suffers permanent damage. In rece...
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