EEG development during resting state

This study analyses the spontaneous electroencephalogram (EEG) brain activity of 14 children diagnosed with Autism Spectrum Disorder (ASD) compared to 18 children with normal development, aged 5–11 years. (i) Power Spectral Density (PSD), (ii) variability across trials (coefficient of variation: CV), and (iii) complexity (multiscale entropy: MSE) of the brain signal analysis were computed on the resting state EEG. PSD (0.5–45 Hz) and CV were averaged over different frequency bands (low-delta, delta, theta, alpha, low-beta, high-beta and gamma). MSE were calculated with a coarse-grained procedure on 67 time scales and divided into fine, medium and coarse scales. In addition, significant neurophysiological variables were correlated with behavioral performance data (Kaufman Brief Intelligence Test (KBIT) and Autism Spectrum Quotient (AQ)). Results show increased PSD fast frequency bands (high-beta and gamma), higher variability (CV) and lower complexity (MSE) in children with ASD when compared to typically developed children. These results suggest a more variable, less complex and, probably, less adaptive neural networks with less capacity to generate optimal responses in ASD children.

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Linear and Non-linear Analyses of EEG in a Group of ASD Children During Resting State Condition

Angulo-Ruíz

Ruiz-Martínez

Rodríguez‐Martínez

et al. 2023

Brain Topogr

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EEG development during resting state

Cited by 1 publication

References 48 publications

Linear and Non-linear Analyses of EEG in a Group of ASD Children During Resting State Condition

Linear and Non-linear Analyses of EEG in a Group of ASD Children During Resting State Condition

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