Nadia Chabane

The paper analyzes EEG data from 4,812 individuals to identify shared and distinct neurophysiological signatures across psychiatric conditions and rare genetic variants.

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

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

The paper identifies altered functional connectivity patterns in young children with ASD using EEG data and links them to cognitive, social, and sensory dimensions of the disorder.

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

This study uses ASL-MRI to find reduced cerebral blood flow in the superior temporal sulcus in children with ASD, correlating with symptom severity and similar to previous PET/SPECT findings.