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 ...

New research looks at EEG's role in real-time monitoring of workers' cognitive and emotional states and its potential in automating the detection of psychological hazards like stress and fatigue, ...

Abstract: This paper presents a comprehensive approach for detecting insomnia using EEG signal analysis by combining traditional machine learning, deep learning, and Neural Tangent Kernel (NTK) ...

A new brainwave test could detect early signs of Alzheimer’s years before diagnosis — in just three minutes. That’s according to researchers at the University of Bath and the University of Bristol, ...

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 ...

Epilepsy is a neurological disorder affecting ~50 million patients worldwide (30% refractory cases) with complex dynamical behavior governed by nonlinear differential equations. Seizures severely ...