Atypical alpha oscillatory EEG dynamics in children with Angelman syndrome.

ABSTRACT:

Objectives

Biomarkers 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.

Method

We analyzed 159 EEG recordings from 95 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 thresh

SUBMITTER: Dickinson AH 

PROVIDER: S-EPMC12409793 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature