This valuable manuscript provides solid evidence regarding the role of alpha oscillations in sensory gain control. The authors use an attention-cuing task in an initial EEG study followed by a ...

Deep learning has emerged as a transformative tool for the automated detection and classification of seizure events from intracranial EEG (iEEG) recordings. In this review, we synthesize recent ...

Researchers have discovered there was an anomaly in Earth's gravitational field between 2006 and 2008, potentially caused by a mineral shift deep within Earth's mantle. GRACE satellites detected a ...

Abstract: Many intriguing applications, such as the ability to move prosthetic limbs and enable more fluid man-machine contact, may be made possible by automatic interpretation of brain readings. The ...

This repository contains the implementation, benchmarks, and supporting tools for my MSc dissertation project: Self-learning Variational Autoencoder for EEG Artifact Removal (Key code only). Benchmark ...

Abstract: Alzheimer's disease (AD), is a prevalent neurodegenerative disorder, characterized by cognitive decline. Alongside AD, and Frontotemporal dementia (FTD) poses significant challenges in ...

An overview of attention detection using EEG signals, which includes six steps: an experimental paradigm design, in which the task and the stimuli are defined and presented to the subjects; EEG data ...

The purpose of this study was to apply deep learning to music perception education. Music perception therapy for autistic children using gesture interactive robots based on the concept of educational ...