Seizures

Mobility Function and Aperiodic Electrocortical Activity in Younger and Older Adults.

Mobility declines with age to the extent that walking speed is often considered a vital sign. Identifying electrocortical changes behind this decline would aid with early identification and intervention. Electroencephalography (EEG) metrics may provide insight into neural factors contributing to mobility decline with aging. Recent research has shown a differentiation in aperiodic EEG across age gr...

Identification of Mitochondrial Dysfunction-Related Candidate Biomarkers and Analysis of the Immune Cell Infiltration in Epilepsy.

Epilepsy is a severe neurological disorder with complex pathogenesis. Mitochondrial dysfunction (MitD) is increasingly recognized as a key driver of epileptogenesis and seizure generation, contributing to neuronal hyperexcitability and network instability. However, the potential mechanisms linking MitD to epilepsy remain incompletely understood. This study aimed to identify MitD-related biomarkers...

EEG-Based Clustering Shows Distinct Separation of Chronic Pain Patients Before Spinal Cord Stimulation Surgery.

Chronic pain is associated with disrupted cortical activity, yet individual variability in these neural patterns remains poorly understood. Electroenc...

TF-MCL: Time-frequency fusion and multi-domain cross-loss for self-supervised depression detection.

In recent years, there has been a notable increase in the use of supervised detection methods of major depressive disorder (MDD) based on electroencep...

Insular morphological abnormalities in focal to bilateral tonic-clonic seizures.

PURPOSE: Focal to bilateral tonic-clonic seizures (FBTCS) is the most severe form of epileptic seizures, posing a major challenge in both management a...

Integrating fuzzy logic and neural networks with multi-criteria decision-making for intelligent evaluation of drug compound design attributes.

This study proposes a fuzzy machine learning framework for optimizing antiepileptic drug selection using Quantitative Structure-Property Relationship ...

Closed-loop stimulation modulates attention shifting in children.

Spontaneous fluctuations in attention can impede adaptation to changing goals and environments. Endogenous control over attentional shifts, referred t...

Exploring human GABA transporter 3 binders for epilepsy through quantum reactivity analysis, molecular dynamics, machine learning prediction, and network pharmacology.

CONTEXT: Drug-resistant epilepsy (DRE) remains a major therapeutic challenge, affecting millions of patients globally who do not respond to convention...

MPAN: A Multi-Prototype Adaptive Network for Few-Shot EEG-Based Biometric Recognition.

Biometric recognition based on electroencephalography (EEG), which captures intrinsic neural dynamics via scalp-recorded electrical activity, has show...

NeuroNetFusion: enhanced EEG abnormality classification via multi-network TF-IDF feature selection.

To address the inherent complexity and nonlinearity of electroencephalogram (EEG) signals, this study proposes a refined classification framework, Neu...

Adaptive drift-aware multi-stage deep learning framework for EEG-based schizophrenia diagnosis.

This study introduces a novel adaptive deep learning framework for EEG-based schizophrenia diagnosis that addresses the limitations of existing static...

DeepEpiX: a software for visualization, annotation and automatic epileptical spike detection in MEG recordings.

BACKGROUND: Magnetoencephalography (MEG) non-invasively records brain activity. It is widely used in presurgical evaluation of drug-resistant epilepsy...

Computational neuroelectrophysiology and artificial intelligence for drug-resistant epilepsy: Recent advances, current challenges, and future directions.

Drug-resistant epilepsy (DRE) affects approximately 30% of epilepsy patients, with surgical cure rates below 70%. This challenge drives a fundamental ...

Noninvasive neurophysiological diagnostics of delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage: a scoping review.

BACKGROUND: Delayed cerebral ischemia (DCI) is a major complication following aneurysmal subarachnoid hemorrhage (aSAH), affecting outcomes. Given its...

A deep hybrid CNN-BiLSTM-BiGRU architecture with explainability for mild cognitive impairment detection using EEG.

Accurate detection of Mild Cognitive Impairment (MCI) is critical for timely intervention and for slowing progression to Alzheimer's disease. Electroe...

A multi-view TSK fuzzy system with deformable Gaussian membership functions and rule-level attention for classification.

This study presents a novel multi-view TSK fuzzy system that integrates deformable Gaussian membership functions with a rule-level attention mechanism...

Determinants and Machine Learning Prediction of Subtherapeutic Sodium Valproate Concentrations in Epilepsy Management in Xinjiang, China.

BACKGROUND AND OBJECTIVE: Valproic acid is a classic antiepileptic drug; however, it is characterized by a narrow therapeutic window, limited safety m...

Brain-age defines a structural signature of outcomes after vagus nerve stimulation in children.

INTRODUCTION: Outcomes following vagus nerve stimulation (VNS) are difficult to predict prior to surgery in pediatric drug-resistant epilepsy (DRE). W...

AI-Driven Mapping of Seizure Spread Patterns.

OBJECTIVE: The focus of epilepsy research has largely been on seizure onset; however, physicians typically examine the patterns of seizure spread past...

Artificial intelligence in the assessment of epilepsy-related genetic mutations: Learned from GABAA receptors and GABA transporter 1.

This review examines how recent genetic and technological advances have transformed our understanding and treatment of genetic epilepsies (GEs), with ...