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EEG entropy analysis in autistic children.
J Clin Neurosci. 2018 Nov 28;:
Authors: Kang J, Chen H, Li X, Li X
Abstract
Autism spectrum disorder (ASD) is a complex and heterogeneous neurodevelopmental disorder, which is characterized by impairments of social interaction and communication, and by stereotyped and repetitive behaviors. Extensive evidences demonstrated that the core neurobiological mechanism of autism spectrum disorder is aberrant neural connectivity, so the entropy of EEG can be applied to quantify this aberrant neural connectivity. In this study, we investigated four entropy methods to analyse the resting-state EEG of the autistic children and the typical development (TD) children. Through 43 children diagnosed with autism aged from 4 to 8 years old as compared to 43 normal children matched for age and gender, we found region-specifically and entropy-specifically which were more sensitive with the increase of age. In detail, for 4 years old group, there is significant difference in central by Renyi permutation entropy method; the significant differences are in frontal and central by sample entropy for 5 years old group; the significant difference is in frontal by fuzzy entropy for 6 years old group; the significant difference is in central by Renyi wavelet entropy for 7 years old group and the difference is in occipital by Renyi wavelet entropy for 8 years old group. The results might guide us to make an accurate distinction between ASD and TD children.
PMID: 30503641 [PubMed - as supplied by publisher]
from PubMed via alexandrossfakianakis on Inoreader https://ift.tt/2RJkCfC
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