Related Experiment Video
Updated: Jun 21, 2026

EEG Mu Rhythm in Typical and Atypical Development
Published on: April 9, 2014
Periodic and aperiodic contributions to EEG delta power are translatable and complementary Angelman syndrome
Daniel P Montgomery1, Jeremy J Shide1, Adam M Didouchevski1
1Center for Neuroscience Research, Children's National Medical Center, Washington, DC, USA.
Background:
Angelman syndrome is a neurodevelopmental disorder caused by loss of maternal UBE3A expression. With promising therapies now in clinical trials, there is a pressing need for reliable and translatable biomarkers. Elevated delta power in electroencephalography (EEG) recordings is a hallmark of Angelman syndrome and a promising biomarker, but traditional measures of delta power conflate true delta oscillations with broadband spectral shifts, limiting interpretability and utility. We sought to investigate whether separating out periodic and aperiodic contributions to delta power would yield more interpretable biomarkers.
Methods:
We applied spectral parameterization to EEG recordings from children with Angelman syndrome (n = 95) and typically developing children (n = 185), and to cortical local field potential recordings from Ube3a mutant mice (n = 39) and littermate controls (n = 47) across postnatal development. We related periodic and aperiodic features to Bayley developmental scores in children, and to performance on a motor-based behavioral battery in mice.
Results:
Here we show that elevated delta power reflects a combination of increased periodic delta oscillations as well as elevated aperiodic slope and offset in both humans and mice. Periodic delta power predicts cognitive ability in children, while aperiodic features predict motor deficits in mice. These features also follow divergent developmental trajectories in both species, suggesting distinct underlying mechanisms.
Conclusions:
Aperiodic spectral features represent a translatable biomarker for Angelman syndrome. Periodic and aperiodic components of the delta phenotype show separable behavioral and developmental signatures, and their complementary use offers improved precision for biomarker-based evaluation in preclinical and clinical research.
More Related Videos
10:22Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy
Published on: December 6, 2016
06:37Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke
Published on: July 14, 2023