Beyond homogeneity: Charting the landscape of heterogeneity in psychiatric electroencephalography
Poster No:
404
Submission Type:
Abstract Submission
Authors:
Aida Ebadi1, Sahar Allouch1, Ahmad Mheich1,2, Judie Tabbal1, Aya Kabbara1,3, Gabriel Robert4,5, Aline Lefebvre6, Anton Iftimovici7,8, Borja Rodríguez- Herreros2, Nadia Chabane2, Mahmoud Hassan1,9
Institutions:
1MINDIG, Rennes, France, 2Service des Troubles du Spectre de l’Autisme et apparentés, Département de psychiatrie, CHUV, Lausanne, Switzerland, 3Faculty of science, Lebanese International University, Tripoli, Lebanon, 4Pôle de Psychiatrie Hospitalo-Universitaire de Psychiatrie Adulte, Centre Hospitalier Guillaume Régn, Rennes, France, 5U1228 Empenn UMR 6074 IRISA, Rennes, France, 6Paris Saclay University, Neurospin, CEA Saclay, Service Avis et Expertise TND, Fondation Vallée, Paris, France, 7Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266,, Paris, France, 8GHU Paris Psychiatrie et Neurosciences, Pôle hospitalo-universitaire d’évaluation, prévention, et innovation thérapeutique (PEPIT), Paris, France, 9School of Science and Engineering, Reykjavik University, Reykjavik, Iceland
First Author:
Co-Author(s):
Ahmad Mheich
MINDIG|Service des Troubles du Spectre de l’Autisme et apparentés, Département de psychiatrie, CHUV
Rennes, France|Lausanne, Switzerland
MINDIG|Service des Troubles du Spectre de l’Autisme et apparentés, Département de psychiatrie, CHUV
Rennes, France|Lausanne, Switzerland
Aya Kabbara
MINDIG|Faculty of science, Lebanese International University
Rennes, France|Tripoli, Lebanon
MINDIG|Faculty of science, Lebanese International University
Rennes, France|Tripoli, Lebanon
Gabriel Robert
Pôle de Psychiatrie Hospitalo-Universitaire de Psychiatrie Adulte, Centre Hospitalier Guillaume Régn|U1228 Empenn UMR 6074 IRISA
Rennes, France|Rennes, France
Pôle de Psychiatrie Hospitalo-Universitaire de Psychiatrie Adulte, Centre Hospitalier Guillaume Régn|U1228 Empenn UMR 6074 IRISA
Rennes, France|Rennes, France
Aline Lefebvre
Paris Saclay University, Neurospin, CEA Saclay, Service Avis et Expertise TND, Fondation Vallée
Paris, France
Paris Saclay University, Neurospin, CEA Saclay, Service Avis et Expertise TND, Fondation Vallée
Paris, France
Anton Iftimovici
Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266,|GHU Paris Psychiatrie et Neurosciences, Pôle hospitalo-universitaire d’évaluation, prévention, et innovation thérapeutique (PEPIT)
Paris, France|Paris, France
Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266,|GHU Paris Psychiatrie et Neurosciences, Pôle hospitalo-universitaire d’évaluation, prévention, et innovation thérapeutique (PEPIT)
Paris, France|Paris, France
Borja Rodríguez- Herreros
Service des Troubles du Spectre de l’Autisme et apparentés, Département de psychiatrie, CHUV
Lausanne, Switzerland
Service des Troubles du Spectre de l’Autisme et apparentés, Département de psychiatrie, CHUV
Lausanne, Switzerland
Nadia Chabane
Service des Troubles du Spectre de l’Autisme et apparentés, Département de psychiatrie, CHUV
Lausanne, Switzerland
Service des Troubles du Spectre de l’Autisme et apparentés, Département de psychiatrie, CHUV
Lausanne, Switzerland
Mahmoud Hassan
MINDIG|School of Science and Engineering, Reykjavik University
Rennes, France|Reykjavik, Iceland
MINDIG|School of Science and Engineering, Reykjavik University
Rennes, France|Reykjavik, Iceland
Introduction:
Although EEG has been a central tool in psychiatric research for many years, it has not yet achieved widespread clinical adoption, despite its numerous advantages (Miljevic, 2023). This may stem from conventional study designs that often assume homogeneity within patient groups and distinct separations between patients and controls-assumptions that do not reflect the complex reality of psychiatric disorders. A promising alternative is Normative Modeling (NM), which involves estimating normative trajectories within a reference population to evaluate individual deviations from these established norms (Marquand, 2016, Marquand, 2019). By capturing the nuances of individual variability, NM can further our understanding of patient heterogeneity in psychiatric disorders.
Methods:
We leverage high-density EEG (HD-EEG) and normative modeling to measure and quantify individual deviations in two key EEG features-spectral power and functional connectivity. The study included a cohort of 1,674 patients diagnosed with attention-deficit/hyperactivity disorder, autism spectrum disorder, learning disorder, or anxiety, alongside 560 matched control participants. Using normative models, we compared each patient's EEG metrics to population norms to assess frequency-dependent and spatial patterns of heterogeneity.
Results:
Our analysis revealed that deviations from normative EEG profiles were highly heterogeneous and frequency-dependent across patient groups. The spatial overlap of these deviations among patients was limited, reaching only up to 40% for spectral power and 24% for connectivity patterns. These findings indicate a significant level of individual variability, highlighting the inadequacy of traditional group-based EEG analyses in capturing patient-specific markers.
Conclusions:
The extensive heterogeneity in EEG patterns among psychiatric patients underscores the limitations of conventional group-based approaches and highlights the need for more personalized, patient-level analyses that can account for individual differences.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Modeling and Analysis Methods:
EEG/MEG Modeling and Analysis 2
Other Methods
Keywords:
Anxiety
Attention Deficit Disorder
Autism
Electroencephaolography (EEG)
Learning
Other - normative modeling
1|2Indicates the priority used for review
·Fig. 1 | Normative modeling of electrophysiological features across age and individual deviation assessment.
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Provide references using APA citation style.
of Affective Disorders 328 (May): 287–302.
Marquand, Andre F. (2019). Conceptualizing Mental Disorders as Deviations from Normative Functioning. Molecular Psychiatry 24 (10): 1565.
Marquand, Andre F. (2016). Understanding Heterogeneity
in Clinical Cohorts Using Normative Models: Beyond Case-Control Studies. Biological Psychiatry 80 (7):
552–61.