Sensorimotor Peak Alpha Frequency Is a Reliable Biomarker of Prolonged Pain Sensitivity. Abstract Previous research has observed that the speed of alpha band oscillations (8-12 Hz
Autonomic/Central Coupling Benefits Working Memory in Healthy Young Adults. Abstract Working memory (WM) is an executive function that can improve with training. However, the precise
Machine-Learning-Based Diagnostics of EEG Pathology. Abstract Machine learning (ML) methods have the potential to automate clinical EEG analysis. They can be categorized into feature-based (with
Convolutional neural network for detection and classification of seizures in clinical data. Abstract Epileptic seizure detection and classification in clinical electroencephalogram data still is a
Subject-Specific feature selection for near infrared spectroscopy based brain-computer interfaces. Abstract BACKGROUND AND OBJECTIVE: Brain-computer interfaces (BCIs) enable people to control an external device by
The Strength of Alpha-Beta Oscillatory Coupling Predicts Motor Timing Precision. Abstract Precise timing makes the difference between harmony and cacophony, but how the brain achieves
Conducting Concurrent Electroencephalography and Functional Near-Infrared Spectroscopy Recordings with a Flanker Task. Abstract Concurrent EEG and fNIRS recordings offer an excellent opportunity to gain a
Exploration of User’s Mental State Changes during Performing Brain-Computer Interface. Abstract Substantial developments have been established in the past few years for enhancing the performance
A natural evolution optimization based deep learning algorithm for neurological disorder classification. Abstract Neurological disorders are one of the significant problems of the nervous system
Classifying Creativity: Applying Machine Learning Techniques to Divergent Thinking EEG Data. Abstract Prior research has shown that greater EEG alpha power (8-13 Hz) is characteristic
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