Cortical Hyperexcitability Shapes Large-Scale Brain Dynamics and Behavioral Outcome in Angelman Syndrome
Duma, G. M.; Bagnoli, M.; Stefanelli, G.; Mazzara, C.; Pellegrino, G.; Mento, G.; Sorrentino, P.; Toffoli, L.; Del Popolo Cristaldi, F.; Antoniazzi, L.; Dei Tos, J.; Azzolini, R.; Baggio, M.; Bonanni, P.; Danieli, A.
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Background Angelman syndrome (AS) is a rare neurodevelopmental disorder with characteristic electroencephalographic abnormalities caused by loss of function of the maternally inherited UBE3A gene. Converging evidence suggests a disrupted excitation-inhibition (E/I) balance towards hyperexcitability. However, noninvasive approaches capable of characterizing intrinsic cortical excitability and its relationship with large-scale brain dynamics in AS are still lacking. We used resting-state electroencephalography (EEG) to derive cortical excitability, testing the hypothesis that altered local E/I balance in AS is associated with instability of large-scale functional brain networks. Methods We recorded 7 minutes of task-free high-density EEG in 29 individuals with AS and 36 typically developing controls. Source-reconstructed cortical activity was used to compute the excitability index (EI), based on mean spatial phase synchronization in the gamma band. Dynamic functional connectivity was computed and summarized as fluidity index, which estimates temporal variability of network configurations. We assessed group differences and associations between EEG features, clinical variables and caregiver-reported questionnaires. Results AS participants showed increased EI in anterior cingulate, dorsolateral prefrontal, temporoparietal, and occipital regions. Fluidity was larger in AS across frequency bands, indicating greater network instability. EI positively predicted fluidity in widespread regions in AS, whereas the opposite pattern was observed in controls. Higher EI correlated with fewer antiseizure medications and with greater sensory-seeking behavior. Conclusions AS is characterized by cortical hyperexcitability coupled with unstable large-scale network dynamics. The EI provides a biologically meaningful marker linking intrinsic E/I imbalance to behavioral features and treatment-related variables
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