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Shide, J. J.

Publications and source records attributed to Shide, J. J..

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Periodic and aperiodic contributions to EEG delta power are translatable and complementary Angelman syndrome biomarkers

Angelman syndrome (AS) is a neurodevelopmental disorder caused by loss of maternal UBE3A expression. With promising AS therapies now in clinical trials, there is a pressing need for reliable and translatable biomarkers. Elevated EEG delta power is a hallmark of AS and a promising biomarker, but traditional measures conflate delta oscillations with broadband spectral shifts, limiting interpretability and utility. We dissociated periodic and aperiodic contributions to delta power using spectral parameterization in children with AS and Ube3a mutant mice. In both species, elevated delta power reflected a combination of increased periodic delta oscillations and elevated aperiodic slope and offset. These features were linked to different behavioral domains and followed divergent developmental trajectories, suggesting distinct underlying mechanisms. Together, our findings establish aperiodic changes as a novel translatable EEG biomarker for AS and support the complementary use of periodic and aperiodic features in preclinical and clinical research.

neuroscience↗

Atypical Alpha Oscillatory EEG Dynamics in Children with Angelman Syndrome

ObjectivesBiomarkers of atypical brain development are crucial for advancing clinical trials and guiding therapeutic interventions in Angelman syndrome (AS). Electroencephalography (EEG) captures well-characterized developmental changes in peak alpha frequency (PAF) that reflect underlying neural circuit maturation and may provide a sensitive metric for mapping atypical neural trajectories in AS. MethodWe analyzed EEG recordings from 159 children with AS (ages 1-15 years) and 185 age-matched typically developing (TD) controls. PAF was quantified using a well-established curve-fitting method applied to 1/f-corrected power spectra. To validate robustness, we further evaluated PAF using an alternative prominence-based peak detection approach across varying detection thresholds. ResultsSignificant disruptions in PAF were evident in children with AS. While over 90% of EEGs from TD children exhibited a clear alpha peak, fewer than 50% of EEGs from children with AS showed a detectable PAF. Furthermore, when PAF was present, its frequency was significantly lower in AS children and did not show the typical age-related increases observed in TD children. Validation analyses confirmed consistently lower rates of PAF detection in AS across varying sensitivity thresholds, demonstrating the robustness of these results. ConclusionsPAF is a robust and developmentally sensitive marker of disrupted neural maturation in children with Angelman syndrome. As a quantifiable and sensitive measure of neural disruptions in AS, PAF has the potential to complement and enhance existing clinical trial outcome assessments by providing an objective index of underlying brain function. Future analyses will explore individual differences related to PAF in AS, to better understand mechanistic insights to guide targeted therapeutic strategies.

neuroscience↗