Pascal Benquet

This paper introduces an automated EEG source imaging method using structured sparsity to improve localization of epileptic activity in single and multiple synchronous cases.

This study shows that kainate receptors (KARs) enable sustained pathological activity in the epileptic dentate gyrus by altering network dynamics and promoting disorganized firing patterns.

This paper introduces a computational model of an epileptic neocortical column to simulate and analyze interictal epileptiform events, revealing relationships between synaptic transmission and event types.

The paper evaluates EEG/MEG source-space network analysis techniques using a human brain computational model and identifies optimal methods for inverse modeling, connectivity measures, and dimensionality reduction.

This paper introduces a laminar neural mass model that realistically reproduces SEEG recordings during epileptic seizures and demonstrates its ability to capture key electrophysiological features.

This study investigates dynamic functional brain networks during cognitive action control in Parkinson's disease patients and healthy controls using HD-EEG, finding differences in network composition and temporal organization.

This study benchmarks nine source separation methods on MEG data to identify the most effective for tracking fast electrophysiological network dynamics during motor and memory tasks.

COALIA is a computational model of human EEG that simulates brain dynamics to study consciousness, reproducing EEG patterns and explaining clinical results in DOC patients and healthy volunteers.

This paper estimates excitatory and inhibitory post-synaptic potentials from local field potentials using a physiologically-grounded neural mass model, validated on simulated and in vivo data.

This study examines functional brain network changes in disorders of consciousness using EEG, finding reduced network integration and increased segregation in patients compared to healthy controls.