Neurology

Seizures

Latest AI and machine learning research in seizures for healthcare professionals.

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Robust and Clinically Reliable EEG Biomarkers: A Cross Population Framework for Generalizable Parkinson's Disease Detection

Developing robust and clinically reliable EEG biomarkers requires evaluation frameworks that explici...

Task-guided Spatiotemporal Network with Diffusion Augmentation for EEG-based Dementia Diagnosis and MMSE Prediction

Patients with dementia typically exhibit cognitive impairment, which is routinely assessed using the...

BandRouteNet: An Adaptive Band Routing Neural Network for EEG Artifact Removal

Electroencephalography (EEG) is highly susceptible to artifact contamination, such as electrooculogr...

Decoding the phenomenology of spontaneous thought using large language-model ratings on verbal retrospective free reports

Spontaneous thoughts constitute most of everyday inner experience, yet long-standing methodological ...

Structure-Guided Diffusion Model for EEG-Based Visual Cognition Reconstruction

Objective: Decoding visual information from electroencephalography (EEG) is an important problem in ...

Image-grounded encoding models reveal distinct temporal profiles of naturalistic object and scene processing in the human brain

The human brain processes large amounts of complex visual information in order to effectively intera...

Subject-Aware Multi-Granularity Alignment for Zero-Shot EEG-to-Image Retrieval

Zero-shot EEG-to-image retrieval aims to decode perceived visual content from electroencephalography...

Predicting Post-Traumatic Epilepsy from Clinical Records using Large Language Model Embeddings

Objective: Post-traumatic epilepsy (PTE) is a debilitating neurological disorder that develops after...

Neural mechanism of postural sway-related beta-band oscillations: a cortico-basal ganglia-thalamic network model of intermittent control

Recent EEG studies of human quiet stance have identified beta-band event-related desynchronization (...

EEG-Based Multimodal Learning via Hyperbolic Mixture-of-Curvature Experts

Electroencephalography (EEG)-based multimodal learning integrates brain signals with complementary m...

Classification of Epileptic iEEG using Topological Machine Learning

Epileptic seizure detection from EEG signals remains challenging due to the high dimensionality and ...

EEG2Vision: A Multimodal EEG-Based Framework for 2D Visual Reconstruction in Cognitive Neuroscience

Reconstructing visual stimuli from non-invasive electroencephalography (EEG) remains challenging due...

Brain3D: EEG-to-3D Decoding of Visual Representations via Multimodal Reasoning

Decoding visual information from electroencephalography (EEG) has recently achieved promising result...

Optimizing EEG Graph Structure for Seizure Detection: An Information Bottleneck and Self-Supervised Learning Approach

Seizure detection from EEG signals is highly challenging due to complex spatiotemporal dynamics and ...

BrainYears: A functional EEG-based brain age clock enables intervention-ready measurements of brain aging

Biological brain aging is a major determinant of cognitive decline and neurodegenerative disease, ye...

EEG Foundation Model Improves Online Directional Motor Imagery Brain-computer Interface Control

Brain-Computer interfaces (BCIs) offer a link between neural signals and external computation, enabl...

Altered EEG markers of reward learning during abstinence in alcohol dependence: a probabilistic reversal learning study

Maladaptive reward learning and decision-making circuity are key factors in the onset and progressio...

Preventing Data Leakage in EEG-Based Survival Prediction: A Two-Stage Embedding and Transformer Framework

Deep learning models have shown promise in EEG-based outcome prediction for comatose patients after ...

EEG-SSFormer: Towards a Robust Mamba-Based Architecture for Dementia Detection from Resting State Electroencephalography

Resting-state electroencephalography (rs-EEG) offers a cost effective and portable alternative to co...

Spectral and non-spectral EEG measures in the prediction of working memory task performance and psychopathology

Working memory (WM) supports the temporary maintenance of goal-relevant information and is disrupted...

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