Cortical Hyperexcitability Shapes Large-Scale Brain Dynamics and Behavioral Outcome in Angelman Syndrome.

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 toward 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 control participants. 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 the 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: Participants with AS showed increased EI in the 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 the AS group, whereas the opposite pattern was observed in the control group. Higher EI correlated with fewer antiseizure medications and greater sensory-seeking behavior. Conclusions: AS is characterized by cortical hyperexcitability coupled with unstable large-scale network dynamics. EI provides a biologically meaningful marker linking intrinsic E/I imbalance to behavioral features and treatment-related variables.