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Beyond homogeneity: Charting the landscape of heterogeneity in psychiatric electroencephalography

Ebadi, A.; Allouch, S.; Mheich, A.; Tabbal, J.; Kabbara, A.; Robert, G.; Lefebvre, A.; Iftimovici, A.; Rodriguez-Herreros, B.; Chabane, N.; HASSAN, M.

2024-03-08 neuroscience
10.1101/2024.03.04.583393 bioRxiv
Show abstract

Electroencephalography (EEG) has been thoroughly studied for decades in psychiatry research. Yet its integration into clinical practice as a diagnostic/prognostic tool remains unachieved. We hypothesize that a key reason is the underlying patients heterogeneity, overlooked in psychiatric EEG research relying on a case-control approach. We combine HD-EEG with normative modeling to quantify this heterogeneity using two well-established and extensively investigated EEG characteristics -spectral power and functional connectivity-across a cohort of 1674 patients with attention-deficit/hyperactivity disorder, autism spectrum disorder, learning disorder, or anxiety, and 560 matched controls. Normative models showed that deviations from population norms among patients were highly heterogeneous and frequency-dependent. Deviation spatial overlap across patients did not exceed 40% and 24% for spectral and connectivity, respectively. Considering individual deviations in patients has significantly enhanced comparative analysis, and the identification of patient-specific markers has demonstrated a correlation with clinical assessments, representing a crucial step towards attaining precision psychiatry through EEG.

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