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Graph convolution network-based eeg signal analysis: a review.
Med Biol Eng Comput
January 2025
School of Control Science and Engineering, Tiangong University, Tianjin, 300387, China.
With the advancement of artificial intelligence technology, more and more effective methods are being used to identify and classify Electroencephalography (EEG) signals to address challenges in healthcare and brain-computer interface fields. The applications and major achievements of Graph Convolution Network (GCN) techniques in EEG signal analysis are reviewed in this paper. Through an exhaustive search of the published literature, a module-by-module discussion is carried out for the first time to address the current research status of GCN.
View Article and Find Full Text PDFEnhancing transcranial ultrasound stimulation planning with MRI-derived skull masks: a comparative analysis with CT-based processing.
J Neural Eng
January 2025
Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Transcranial ultrasound stimulation (TUS) presents challenges in ultrasound wave transmission through the skull, affecting study outcomes due to aberration and attenuation. While planning strategies incorporating 3D computed tomography (CT) scans help mitigate these issues, they expose participants to radiation, which can raise ethical concerns. A solution involves generating skull masks from participants' anatomical magnetic resonance imaging (MRI).
View Article and Find Full Text PDFThe representation of stimulus features during stable fixation and active vision.
J Neurosci
January 2025
The Department of Psychology and The Department of Cognitive and Brain Sciences, The Hebrew University of Jerusalem.
Predictive updating of an object's spatial coordinates from pre-saccade to post-saccade contributes to stable visual perception. Whether object features are predictively remapped remains contested. We set out to characterise the spatiotemporal dynamics of feature processing during stable fixation and active vision.
View Article and Find Full Text PDFNeural Sensitivity to Ambiguous Social Exclusion Reflects Information Processing Bias in Midadolescents With Higher Levels of Aggression.
Dev Psychobiol
January 2025
Department of Psychology, University of Texas at Dallas, Richardson, Texas, USA.
Aggression is commonly associated with increased experiences of peer rejection and maladaptive social information processing biases throughout development. Little is known about the neural correlates of peer rejection that might underlie social information processing biases, and whether these neural correlates are common or different across early- and mid-adolescents on a continuum of aggression. Using the Cyberball task, we examined mediofrontal theta (4-7 Hz) event-related EEG spectral power during conditions of explicit and ambiguous social exclusion in 117 participants (57 early adolescents, ages 10-12 years, and 60 mid-adolescents, ages 14-16 years).
View Article and Find Full Text PDFObjective Neurophysiological Measures of Cognitive Performance in Elite Ice Hockey Players.
Open Access J Sports Med
January 2025
Brainnet, Faculty of Applied Sciences, Simon Fraser University, Metro Vancouver, BC, Canada.
Introduction: Athletic peak performance is increasingly focused on cognitive and mental factors. In the current study, cognitive performance was measured by neurophysiological responses in elite Junior-A hockey players.
Methods: Neurophysiological brain vital signs were extracted from event-related potentials (ERPs) to evaluate auditory sensation (the N100), basic attention (the P300), and cognitive processing (the N400).
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