Christophe Grova

This study examines how connector hubs in temporal lobe epilepsy patients reorganize compared to healthy controls, finding widespread hub reductions and new hub emergence in contralateral regions.

This study identifies patient-specific functional biomarkers in temporal lobe epilepsy using multimodal MRI data to predict clinical outcomes and guide precision therapeutics.

This study shows sleep deprivation reduces brain network flexibility by altering thalamic regulation and coupling with cortical networks, leading to cognitive impairments.

NIRSTORM extends Brainstorm for fNIRS analysis, offering 3D hemodynamic reconstructions and optimal probe design within a multimodal framework.

This paper applies beamforming spatial filtering to EEG-fMRI data to improve detection of sleep spindles and enhance fMRI GLM analysis by reducing BCG artefacts.

The paper investigates how NREM sleep stages N2 and N3 modulate cognitive recovery after sleep deprivation by analyzing brain network segregation using fMRI and a new hierarchical segregation index.

This paper validates MEG source imaging by comparing it to an intracranial EEG atlas, finding that MEG accurately estimates oscillatory patterns in lateral regions but underestimates deep regions.

This study uses hierarchical Bayesian modeling to analyze how PAS stimulation affects cortical excitability and hemodynamic responses, finding a positive correlation between the two.

This study investigates the relationship between cortical excitability and hemodynamic activity using simultaneous TMS and fNIRS, finding a positive correlation between them.

This paper introduces a data-driven beamforming technique to reduce BCG artefacts in EEG-fMRI without using ECG signals, improving signal recovery for task-based neural activity.

This paper introduces a new fNIRS reconstruction method called Maximum Entropy on the Mean (MEM), which provides more accurate and robust reconstructions than the Minimum Norm Estimate (MNE) in both simulations and real data.

This study shows that fast oscillations >40Hz detected with high-density EEG can accurately localize the epileptogenic zone, outperforming conventional EEG methods.

This study shows that sleep deprivation alters the balance of cortical network integration and segregation, which correlates with cognitive deficits and recovery after a nap.