1. Excitation-Inhibition Balance in Neurodevelopmental Disorders:: Towards a Network-level Neurophysiology Approach to Improve Diagnosis and Treatment Development
- Author
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Juarez Martinez, Erika Liliana and Juarez Martinez, Erika Liliana
- Abstract
Neurodevelopmental disorders (NDD) are characterized by neurocognitive involvement and life-limiting disabilities with classification primarily based on behavior and social symptoms, overlooking their neurobiology. This symptom-defined nosology results in clinical heterogeneity, complicates disease management, and leads to ineffective treatment development. This calls for a revolution in NDD classification towards one that considers the neurobiological mechanisms underlying behavior. This thesis investigates the role of altered neuronal oscillations due to imbalances in excitatory and inhibitory activity (E/I) as a neurophysiological framework in NDD. A balance between excitation and inhibition (E/I) is necessary for neuronal network organization, information processing, and cognitive integration. E/I imbalances are increasingly considered a pathophysiological mechanism in NDD. We propose a neurophysiology-based approach incorporating EEG measures sensitive to E/I changes to uncover a network dysfunction linked to individual behavioral profiles. This may enable physiological stratification within NDD and serve as a target to trial novel E/I-modulating therapies. Clinical estimations of neuronal network E/I ratios were lacking, so this project initially developed a method to quantify a functional measure of network-level E/I ratio (fE/I) using EEG (Chapter 1). Next, we tested the hypothesis that E/I imbalances characterize autism spectrum disorder (ASD). Initial findings revealed that individuals with ASD show a broader distribution of neuronal E/I ratios compared to healthy individuals, with variability linked to qualitative EEG abnormalities. This highlighted an unrecognized physiological heterogeneity within ASD that may influence symptomatology and treatment response. Further investigation using the EU-AIMS EEG dataset confirmed an association between network-level E/I, qualitative EEG abnormalities, and clinical symptoms in ASD (Chapter 2). These results suggest
- Published
- 2024
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