Entropy, complexity, and spectral features of EEG signals in autism and typical development: a quantitative approach.

ABSTRACT: Autism spectrum disorder (ASD) is a neurodevelopmental condition that affects the brain's function. Electroencephalography (EEG) is a non-invasive technique that measures the electrical activity of the brain and can reveal its dynamics and information processing. This study explores an eyes-opened resting state quantitative EEG analysis of 49 children with ASD and 39 typically developing (TD or Control) children, using various features of entropy and complexity. Time and frequency domain features were applied for all EEG channels, such as the power spectra, brain rate, sample entropy, permutation entropy, spectral entropy, Tsallis entropy, Rényi entropy, Lempel-Ziv complexity, and Higuchi fractal dimension. The features were compared between the ASD and TD groups and tested for statistical

SUBMITTER: Tenev A 

PROVIDER: S-EPMC11832502 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature