Mark James Cook

A Neural Mass Modelling Framework for Evaluating EEG Source Localisation of Seizure Activity

This paper presents a simulation framework to evaluate EEG source localisation methods by generating biologically plausible seizure dynamics and EEG signals with known ground truth.

Structural Eigenmodes of the Brain to Improve the Source Localisation of EEG: Application to Epileptiform Activity

This paper uses structural eigenmodes of the brain to improve EEG source localization in epilepsy, finding geometric eigenmodes slightly outperform connectome eigenmodes.

Forecasting Seizure Duration from Neural Connectivity Patterns in a Neural Mass Model

This study uses a neural mass model to predict seizure duration from neural connectivity patterns in a rat epilepsy model, finding that preictal connectivity parameters can forecast seizure length with high accuracy.

Dynamic Multiday Seizure Cycles in a Tetanus Toxin Rat Model of Epilepsy: Evolving Rhythms and Implications for Prediction

This study identifies dynamic multiday seizure cycles in a Tetanus Toxin rat model, showing evolving rhythms that may inform seizure prediction and treatment.

Cycles in Seizure Duration and Their Underlying Dynamics in the Tetanus Toxin Rat Model

This study identifies cyclical patterns in seizure duration in the Tetanus Toxin rat model, showing predictable rhythms linked to EEG power, which could improve epilepsy management.

Neural Dynamics and Seizure Correlations: Insights from Neural Mass Models in a Tetanus Toxin Rat Model of Epilepsy

This study uses a neural mass model to analyze iEEG data from a Tetanus Toxin rat epilepsy model, finding correlations between connectivity weights and seizure frequency, and showing longer recovery times before seizures.

Reduced Synaptic Heterogeneity in a Tetanus ToxinModel of Epilepsy: Insights from ComputationalModeling

This study uses a neural mass model to show reduced synaptic heterogeneity in a Tetanus Toxin rat epilepsy model, linked to increased network synchrony.

Response to photic stimulation as a measure of cortical excitability in epilepsy patients

This paper investigates how epilepsy patients respond to photic stimulation, finding differences in EEG biomarkers that suggest cortical excitability changes associated with seizure states.

Circadian distribution of epileptiform discharges in epilepsy: candidate mechanisms of variability

The paper uses a mathematical model to analyze EEG data from people with epilepsy and identifies cortisol levels and sleep stages as factors explaining daily variability in epileptiform discharges.

Inhibitory stabilized network behaviour in a balanced neural mass model of a cortical column

The paper develops a neural mass model of a cortical column to study inhibitory stabilization across layers, finding that layers 4 and 5 exhibit ISN behavior with paradoxical responses, while layer 2/3 does not.

Spatiotemporal patterns of high-frequency activity (80-170 Hz) in long-term intracranial EEG

This study analyzes long-term intracranial EEG recordings to examine variability and circadian patterns of high-frequency activity and epileptiform spikes in patients with drug-resistant epilepsy.

A taxonomy of seizure dynamotypes

This paper introduces a taxonomy of seizure dynamotypes based on bifurcation theory and applies it to EEG data, identifying 16 dynamotypes and their variations across patients.

Computer-assisted EEG diagnostic review for idiopathic generalized epilepsy

This paper presents a deep learning algorithm for computer-assisted EEG review in idiopathic generalized epilepsy, achieving high sensitivity and reducing human review time by 80%-99%.

Critical slowing as a biomarker for seizure susceptibility

This study identifies critical slowing as a biomarker for seizure susceptibility using long-term iEEG recordings from epilepsy patients.