Sahar Allouch

The Lifespan Architecture of Human EEG

The paper maps lifespan EEG trajectories across age groups, revealing nonlinear patterns and spatial variations in brain activity.

Robust EEG brain-behavior associations emerge only at large sample sizes

The paper shows that EEG-brain behavior associations are unstable with small samples but become reliable with large cohorts.

Sample size critically shapes the reliability of EEG case-control findings in psychiatry

The paper shows that small sample sizes in EEG case-control studies lead to unreliable results, while larger samples produce consistent and reproducible findings.

Transdiagnostic electrophysiological subtypes reveal brain-behavior dimensions in youth psychiatry

The paper identifies three neurophysiological biotypes in youth using EEG data, revealing brain-behavior relationships that challenge traditional diagnostic categories.

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.

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.

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.