Seizures

Brain connectivity predict surgical outcomes of low-grade epilepsy-associated neuroepithelial tumors.

OBJECTIVE: Low-grade epilepsy-associated neuroepithelial tumors (LEATs) often cause drug-resistant epilepsy. Despite complete resection of these lesions, approximately 20% of patients continue to experience suboptimal seizure control. This study aims to investigate the predictive value of quantitative features in determining the surgical outcomes for LEAT patients. METHODS: We retrospectively anal...

Mind the Gap! What do people with epilepsy want to know?

BACKGROUND: There is little research about the questions asked by people with epilepsy, and how these are answered. Information sources include standardised medical or charity websites, responses generated by artificial intelligence paradigms and informal peer support. METHODS: Through social media (X, formerly Twitter) people with epilepsy were asked "what would you ask a neurologist/epileptologi...

Quantitative EEG enhances early assessment and prognostic stratification of brain dysfunction in infants with abusive head trauma.

AIM: To assess the value of quantitative EEG (qEEG) as a diagnostic and prognostic biomarker in infants with abusive head trauma (AHT). Despite its ce...

Intelligent electroencephalogram feature engineering for rapid mental health diagnosis.

Schizophrenia is one of the serious disorders and, if left untreated, can result in a range of problems with cognition, behavior, and emotions that af...

An event-based filtering and weighted enhanced deep learning epileptic seizure prediction method.

The timely detection of impending seizures can offer physicians a critical window of opportunity to implement interventions and enable epileptic patie...

Lightweight Seizure Prediction Model based on Kernel-Enhanced Global Temporal Attention.

Clinically, epilepsy manifests as a chronic condition marked by unprovoked, recurrent seizures, plaguing over 70 million individuals with debilitating...

Neurophysiological differentiation of Boder's dyslexia subtypes using harmonised quantitative EEG cross-spectra.

Developmental dyslexia is a heterogeneous disorder classically divided into distinct subtypes. Elena Boder's, 1973 model conceptualised reading and sp...

ELAI-SGCN: An explainable lightweight adaptive information-perceiving spiking graph convolutional network for EEG-based emotion recognition.

BACKGROUND: Emotion recognition is increasingly essential for diagnosing mental disorders like depression and anxiety. Electroencephalography (EEG) is...

Recognizing intentions with body segmental cues of gait cycles before direction change during continuous walking.

BACKGROUND: Gait intention is typically detected using electroencephalogram (EEG) and primarily focuses on recognizing the initiation of walking. Rece...

One Hundred Years Later! The Current Utility of EEG Tools in Psychiatry: Some Insights and Perspectives.

ObjectiveSince the pioneering work of Hans Berger in 1929 introducing the utility of human electroencephanlography (EEG) in psychiatry, a considerable...

Propagation mapping using iterative independent component analysis for seizure onset zone localization in temporal lobe epilepsy.

BACKGROUND: Epilepsy affects approximately 70 million people worldwide, with a third of them being drug-resistant and requiring surgical intervention....

GCANet: Enhancing EEG-based auditory attention decoding with temporal frequency GCN and cross attention mechanisms.

In complex auditory environments, individuals rely on selective auditory attention to focus on a target speaker while suppressing competing sounds, a ...

Spectral anomaly detection in physiological time-series data: A systematic review.

BACKGROUND: The identification of anomalies in physiological time-series data, specifically ECG and EEG spectra, is a key part of the diagnostic proce...

Development of a predictive model for eosinophilia in patients treated with ampicillin/sulbactam or piperacillin/tazobactam.

AIM: We aim to identify risk factors for antibiotic-induced eosinophilia in hospitalized patients receiving penicillin/beta-lactamase inhibitor therap...

A Novel Morlet Convolutional Neural Network.

Automatic seizure detection holds significant importance for epilepsy diagnosis and treatment. Convolutional neural networks (CNNs) have shown immense...

Electroencephalography-Based Machine and Deep Learning Approaches for the Diagnosis of Dissociative Disorders: A Comprehensive Review.

Dissociative disorders (DDs), including dissociative identity disorder and depersonalization disorder, are complex and often misdiagnosed psychiatric ...

Revisiting drunk driving risk among individuals with alcohol use disorder using unsupervised learning: From clinical characteristics and neuropsychological performance to EEG data.

The strong association between alcohol use disorder (AUD) and driving under the influence of alcohol (DUIA) suggests substantial overlaps across the b...

Cross-subject emotion recognition with loop adaptive adversarial transfer network.

Emotion recognition has broad application prospects in real life. The variability across subjects in emotion-related electroencephalogram (EEG) signal...

Fuzzy symbolic convergent cross mapping: A causal coupling measure for EEG signals in disorders of consciousness patients.

Accurate and timely diagnosis in disorders of consciousness (DOC) patients remains a core clinical challenge. Electroencephalography (EEG) shows stron...

Unconscious elevated bottom-up processing in depression: Insights from dynamic causal modeling with EEG and fMRI.

INTRODUCTION: MRI compatible EEG systems enable simultaneous EEG-fMRI data assessment, which provides high spatial and high temporal resolution of neu...