By modeling the single-trial electroencephalogram of participants performing perceptual decisions, and building on predictions from two century-old psychological laws, we estimate the times of ...
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 ...
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 ...
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, ...
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 ...
Researchers have developed a deep learning model called LSTM-SAM that predicts extreme water levels from tropical cyclones more efficiently and accurately, especially in data-scarce coastal regions, ...
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 ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback