Aya Kabbara

How Much Does Electrode Density Matter? A Multilevel Evaluation from EEG Signals to Cortical Networks

This study evaluates how electrode density impacts EEG analysis across multiple levels, finding that lower densities affect regional and source-level analyses more than global measures.

Characterizing the heterogeneity of neurodegenerative diseases through EEG normative modeling

This study uses EEG and normative modeling to identify deviations in neurophysiological features in Parkinson's and Alzheimer's patients, showing significant heterogeneity and correlations with clinical scores.

Beyond homogeneity: Charting the landscape of heterogeneity in psychiatric electroencephalography

This paper quantifies EEG heterogeneity in psychiatric disorders using normative modeling, finding significant individual deviations that correlate with clinical assessments.

Effect of analytical variability in estimating EEG-based functional connectivity

This study examines how methodological choices in EEG source connectivity analysis affect results consistency and similarity across subjects.

Successful reproduction of a large EEG study across software packages

This paper reanalyzed EEG data using three software tools to assess how preprocessing variability affects results.

Dynamic rewiring of electrophysiological brain networks during learning

This study tracks changes in electrophysiological brain networks during 6 weeks of motor skill training and finds increased frequency-specific flexibility in brain regions associated with learning.

Assessing HD-EEG functional connectivity states using ahuman brain computational model

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.

Effect of channel density, inverse solutions and connectivity measures on EEG resting-state networks: a simulation study

This study evaluates how EEG channel density, inverse solutions, and connectivity measures affect resting-state network reconstruction accuracy using simulations.

Impaired dynamics of prefrontal beta-band networks during cognitive action control in Parkinson's disease

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.

Mean-field modeling of brain-scale dynamics for the evaluation of EEG source-space networks

The paper evaluates EEG source-space networks using a large-scale brain activity model called COALIA, showing that high electrode density and specific inverse solution/connectivity measure combinations improve network estimation.

Dynamics of task-related electrophysiological networks: a benchmarking study

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.

The dynamic modular fingerprints of the human brain at rest

This study examines dynamic brain modularity at rest using EEG/MEG, revealing spatiotemporal patterns and sub-networks within RSNs, and links dynamics to mental imagery.

Brain network dynamics correlate with personality traits

This study uses dynamic functional connectivity measures from EEG and MEG data to show that personality traits like neuroticism, extraversion, and openness correlate with brain network dynamics.

Detecting M/EEG modular brain states in rest and task

This paper introduces a framework to detect fast modular brain states during rest and task, validated on MEG and EEG data from healthy subjects and Parkinson's patients.