Disrupted Brain Network in Children with Autism Spectrum Disorder

Ke Zeng,Estate M Sokhadze,Gaoxiang Ouyang,Yao Wang,Jiannan Kang,Manuel F Casanova,Junxia Han,Xiaoli Li,Jingqing Li

doi:10.1038/s41598-017-16440-z

Abstract

Alterations in brain connectivity have been extensively reported in autism spectrum disorder (ASD), while their effects on the topology of brain network are still unclear. This study investigated whether and how the brain networks in children with ASD were abnormally organized with resting state EEG. Temporal synchronization analysis was first applied to capture the aberrant brain connectivity. Then brain network topology was characterized by three graph analysis methods including the commonly-used weighted and binary graph, as well as minimum spanning tree (MST). Whole brain connectivity in ASD group was found to be significantly reduced in theta and alpha band compared to typically development children (TD). Weighted graph found significantly decreased path length together with marginally significantly decreased clustering coefficient in ASD in alpha band, indicating a loss of small-world architecture to a random network. Such abnormal network topology was also demonstrated in the binary graph. In MST analysis, children with ASD showed a significant lower leaf fractions with a decrease trend of tree hierarchy in the alpha band, suggesting a shift towards line-like decentralized organization in ASD. The altered brain network may offer an insight into the underlying pathology of ASD and possibly serve as a biomarker that may aid in diagnosis of ASD.

Highlights

It is widely acknowledged that autism spectrum disorder (ASD) is a disorder of brain development prompting an increasing number of studies adopting brain imaging techniques to understand the neurobiology of this condition
It can be intuitionisticly found that most of the atypical functional connectivity in ASD exhibited a decrease compared with the typically development children (TD) group, especially in delta, theta and alpha band
We found that childhood autism is characterized by a disrupted brain networks, which may be a distinguishing feature in children with ASD

Summary

Introduction

It is widely acknowledged that ASD is a disorder of brain development prompting an increasing number of studies adopting brain imaging techniques to understand the neurobiology of this condition. A large case study with 984 children (430 ASD and 554 Controls) demonstrated when EEG coherence between brain regions were used to identify children with ASD, the classification accuracy can reach up to 86%, suggesting a stable pattern of abnormal functional connection in ASD12. There is evidence of large scale network reorganization during normal development of brain[20] All of these make the investigation of the brain network organization in ASD of great relevance. The MST is defined as an acyclic sub-network of original weighted network that connects all nodes while minimizing connection cost (sum of all connection distances) In this way, all networks in different conditions would have the same number of nodes and edges, enabling a direct comparison of their network topology while avoiding potential biases introduced by the normalization.

Methods

Results

Conclusion