Seizures

Neurophysiological mechanisms and predictive modeling of SSRI treatment response in depression disorder based on multidimensional EEG features.

BACKGROUND: Depression exhibits significant heterogeneity in antidepressant treatment response. This...

Brain dynamics and depressive symptoms in young adults: Evidence from EEG.

BACKGROUND: Depression is a major public health concern, with a rising prevalence among adolescents ...

CNN-Autoformer: Automated EEG-Based Seizure Detection and Localization Using Hybrid Deep Learning.

Epilepsy is a neurological disorder characterized by transient and recurrent abnormal brain activity...

Distinct electroencephalogram microstate in patients with methamphetamine use disorder and obsessive-compulsive disorder.

BACKGROUND: Electroencephalogram (EEG) microstates reflect momentary localized brain activity and ma...

Visually-Inspired Multimodal Iterative Attentional Network for High-Precision EEG-Eye-Movement Emotion Recognition.

Advancements in artificial intelligence have propelled affective computing toward unprecedented accu...

A novel machine learning-based method to quantify the effect of transcranial direct current stimulation on opioid users.

BACKGROUND: Opioid addiction is a major public health concern, associated with numerous health and s...

A multi-level teacher assistant-based knowledge distillation framework with dynamic feedback for motor imagery EEG decoding.

Deep learning has shown promise in motor imagery-based electroencephalogram (MI-EEG) decoding, a cri...

Driver Emotion Recognition Using Multimodal Signals by Combining Conformer and Autoformer.

This study aims to develop a multimodal driver emotion recognition system that accurately identifies...

Spiking neural networks for EEG signal analysis: From theory to practice.

The intricate and efficient information processing of the human brain, driven by spiking neural inte...

Dysmorphic neurons express markers of inhibitory glycinergic signaling in focal cortical dysplasia IIb.

Focal cortical dysplasia (FCD) is a neurodevelopmental malformation that often manifests as medicall...

Flexible wearable medical devices: from material innovations and data processing to intelligent healthcare applications.

BACKGROUND: Flexible wearable medical devices drive healthcare transformation via non-invasive, real...

Diffusion Model-Based Multi-Channel EEG Representation and Forecasting for Early Epileptic Seizure Warning.

Predicting delirium in critically Ill COVID-19 patients using EEG-derived data: a machine learning approach.

Delirium is a severe and common complication among critically ill patients, particularly those with ...

Neural correlates of evaluative bias against AI-labeled versus human-labeled artworks.

The rapid advancement of generative artificial intelligence (AI) has enabled machines to produce cre...

Short-horizon neonatal seizure prediction using EEG-based deep learning.

Strategies to predict neonatal seizure risk have typically focused on long-term static predictions w...

How EEG preprocessing shapes decoding performance.

Electroencephalography (EEG) preprocessing varies widely between studies, but its impact on classifi...

An investigation of multimodal EMG-EEG fusion strategies for upper-limb gesture classification.

. Upper-limb gesture identification is an important problem in the advancement of robotic prostheses...

A transformer-based network with second-order pooling for motor imagery EEG classification.

. Electroencephalography (EEG) signals can reflect motor intention signals in the brain. In recent y...

Brain region localization: a rapid Parkinson's disease detection method based on EEG signals.

Parkinson's disease (PD) is a prevalent neurodegenerative disorder worldwide, often progressing to m...

Detection of focal impaired awareness seizures using a biometric shirt.

OBJECTIVE: In recent years, seizure detection using wearable technology has gained significant atten...

A Composable Channel-Adaptive Architecture for Seizure Classification.

Multi-variate time-series are one of the primary data modalities involved in large classes of proble...