Seizures

The footprint of colour in EEG signal

Our perception of the world is inherently colourful, and colour provides well-documented benefits for vision: it helps us see things quicker and remember them better. We hypothesised that colour is not only central to perception but also a rich, decodable source of information in electroencephalography (EEG) signals recorded non-invasively from the scalp. While previous work has shown that brain a...

Direct Prediction of the Complex-Valued Analytic Signal of EEG from Raw Multichannel Data

Accurate estimation of instantaneous neural dynamics is essential for electroencephalography (EEG)-based brain–state analysis and future closed-loop applications. Conventional phase estimation methods that rely on bandpass filtering and autoregressive prediction are limited by reduced accuracy near the current time point, poor future prediction capability, and susceptibility to inconsistencies in ...

Network Rerouting Under Ayahuasca: Temporally and Hemisphere-Resolved EEG Connectomics

Ayahuasca profoundly alters conscious experience, yet robust, time-resolved EEG markers of its network-level effects remain limited. We combined machi...

Motion sequencing reveals hidden patterns of repetitive behavior in a mouse model of epilepsy

Epilepsy is the 4th most prevalent neurological condition with 50 million cases worldwide. Patients with epilepsy bare a disproportionate burden of co...

Temporal Dynamics of High-Frequency Oscillations in Alzheimer’s Disease: A Longitudinal Study in hAPP-J20 Mice

Alzheimer’s disease (AD) is characterized by progressive cognitive decline and increased seizure susceptibility; yet both the mechanistic and temporal...

Pre-movement neural population activity in human motor cortex reflects the subsequent outcome of futsal free kicks

Recent sports science studies suggest that optimizing neural activity can enhance motor performance, but practical applications have been hindered by ...

Heart rate fragmentation improves general anesthesia state classification using machine learning

Accurate assessment of consciousness during general anesthesia is crucial for optimizing anesthetic dosage and patient safety. Current electroencephal...

High density EEG and deep learning improves outcome prediction on the first day of coma after cardiac arrest

We assessed outcome prediction of comatose patients using a deep learning analysis applied to resting EEG on the first and second day after cardiac ar...

VIDEO BASED DETECTION OF EPILEPTIC SEIZURES USING A THREE-DIMENSIONAL CONVOLUTIONAL NEURAL NETWORK

Seizure detection in epilepsy monitoring units (EMU) is essential for the clinical assessment of drug-resistant epilepsy. Automated video analysis usi...

Enhancing Rare Disease Education through AI-Driven Podcast Generation

Rare diseases, including many rare genetic epilepsies and neurodevelopmental disorders, present significant challenges in timely diagnosis, treatment,...

Improving Diagnostic Accuracy of Routine EEG for Epilepsy using Deep Learning

The diagnostic yield of routine EEG in epilepsy is limited by low sensitivity and the potential for misinterpretation of interictal epileptiform disch...

Predicting Seizures Episodes and High-Risk Events in Autism Through Adverse Behavioral Patterns

To determine whether historical behavior data can predict the occurrence of high-risk behavioral or seizure events in individuals with profound Autism...

VR-based Gamma Sensory Stimulation: A feasibility study

Alzheimer’s disease (AD) presents a critical global health challenge, with current therapies offering limited efficacy and safety in halting disease p...

Miniaturization of Epileptic Abnormal Electrocorticogram Detector Using 3D Convolutional Neural Network

Epilepsy is a neurological disorder characterized by sudden and recurrent seizures caused by abnormal electrical activity in the brain. Responsive Neu...

Deep Learning-Driven EEG Analysis for Personalized Deep Brain Stimulation Programming in Parkinson’s Disease

Deep Brain Stimulation (DBS) is an invasive procedure used to alleviate motor symptoms in Parkinson’s Disease (PD) patients. While brain activity can ...

Transcriptomic analyses of human brains with Alzheimer’s disease identified dysregulated epilepsy-causing genes

Alzheimer’s Disease (AD) patients at multiple stages of disease progression have a high prevalence of seizures. However, whether AD and epilepsy share...

Language Model Applications for Early Diagnosis of Childhood Epilepsy

Accurate and timely epilepsy diagnosis is crucial to reduce delayed or unnecessary treatment. While language serves as an indispensable source of info...

The Clinical Value of ChatGPT for Epilepsy Presurgical Decision Making: Systematic Evaluation on Seizure Semiology Interpretation

For patients with drug-resistant focal epilepsy (DRE), surgical resection of the epileptogenic zone (EZ) is an effective treatment to control seizures...

Automatic classification of eeg signals, based on image interpretation of spatio-temporal information

Brain-Computer Interface (BCI) applications provide a direct way to map human brain activity onto the control of external devices, without a need for ...

Liquid-Dendrite Spiking Neural Network for Edge Devices: A 130 K-Parameter, 535 KB Model for Time-Domain Epileptic Seizure Detection

Epilepsy is a significant global health issue, requiring dependable diagnostic tools like scalp encephalogram (scalp-EEG), sub-scalp EEG, and intracra...