Giovanni Pellegrino

This study evaluates ten excitability metrics from MEG data to show cortical excitability is multidimensional with distinct spatial and functional patterns.

The paper investigates neural dynamics and cortical excitability in ADHD and typically developing individuals, finding a developmental continuum rather than distinct diagnostic differences.

This study evaluates EEG-based measures of cortical excitability before and after iTBS in healthy subjects, finding that gamma band phase consistency correlates with excitability changes in M1.

This study uses hdEEG to assess excitation/inhibition balance in TLE patients, finding a correlation with cognitive function and gene expression.

This paper evaluates ROI extraction methods for MEG connectivity analysis and recommends strategies based on sensitivity and specificity trade-offs.

This study investigates how structural brain organization influences altered functional dynamics in temporal lobe epilepsy using MRI and hdEEG data.

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 shows that MEG signatures for individual identification improve during task-related behavior compared to resting-state, with controlled tasks showing the most significant improvements.

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 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.