Literature DB >> 30503641

EEG entropy analysis in autistic children.

Jiannan Kang1, Huimin Chen2, Xin Li3, Xiaoli Li4.   

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.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Autism; Children; EEG; Entropy; Neural connectivity

Mesh:

Year:  2018        PMID: 30503641     DOI: 10.1016/j.jocn.2018.11.027

Source DB:  PubMed          Journal:  J Clin Neurosci        ISSN: 0967-5868            Impact factor:   1.961


  2 in total

1.  The automated preprocessing pipe-line for the estimation of scale-wise entropy from EEG data (APPLESEED): Development and validation for use in pediatric populations.

Authors:  Meghan H Puglia; Jacqueline S Slobin; Cabell L Williams
Journal:  Dev Cogn Neurosci       Date:  2022-10-17       Impact factor: 5.811

2.  Individual Cortical Entropy Profile: Test-Retest Reliability, Predictive Power for Cognitive Ability, and Neuroanatomical Foundation.

Authors:  Mianxin Liu; Xinyang Liu; Andrea Hildebrandt; Changsong Zhou
Journal:  Cereb Cortex Commun       Date:  2020-05-07
  2 in total

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