Network efficiency in autism spectrum disorder and its relation to brain overgrowth

被引:34
|
作者
Lewis, John D. [1 ]
Theilmann, Rebecca J. [2 ]
Townsend, Jeanne [3 ,4 ]
Evans, Alan C. [1 ]
机构
[1] McGill Univ, Montreal Neurol Inst, McConnell Brain Imaging Ctr, Montreal, PQ H3A 2B4, Canada
[2] Univ Calif San Diego, Dept Radiol, La Jolla, CA 92093 USA
[3] Univ Calif San Diego, Dept Neurosci, La Jolla, CA 92093 USA
[4] Univ Calif San Diego, Res Aging & Dev Lab, La Jolla, CA 92093 USA
来源
基金
加拿大创新基金会; 加拿大自然科学与工程研究理事会;
关键词
autism; brain size; network analysis; connectivity; tractography; optimal wiring; scaling; HIGH-FUNCTIONING AUTISM; CORPUS-CALLOSUM; SMALL-WORLD; HEAD CIRCUMFERENCE; CEREBRAL-CORTEX; SIZE; CONNECTIVITY; VOLUME; MAMMALS; GROWTH;
D O I
10.3389/fnhum.2013.00845
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
A substantial body of evidence links differences in brain size to differences in brain organization. We have hypothesized that the developmental aspect of this relation plays a role in autism spectrum disorder (ASD), a neurodevelopmental disorder which involves abnormalities in brain growth. Children with ASD have abnormally large brains by the second year of life, and for several years thereafter their brain size can be multiple standard deviations above the norm. The greater conduction delays and cellular costs presumably associated with the longer long-distance connections in these larger brains is thought to influence developmental processes, giving rise to an altered brain organization with less communication between spatially distant regions. This has been supported by computational models and by findings linking greater intra-cranial volume, an index of maximum brain-size during development, to reduced inter-hemispheric connectivity in individuals with ASD. In this paper, we further assess this hypothesis via a whole-brain analysis of network efficiency. We utilize diffusion tractography to estimate the strength and length of the connections between all pairs of cortical regions. We compute the efficiency of communication between each network node and all others, and within local neighborhoods; we then assess the relation of these measures to intra-cranial volume, and the differences in these measures between adults with autism and typical controls. Intra-cranial volume is shown to be inversely related to efficiency for wide-spread regions of cortex. Moreover, the spatial patterns of reductions in efficiency in autism bear a striking resemblance to the regional relationships between efficiency and intra-cranial volume, particularly for local efficiency. The results thus provide further support for the hypothesized link between brain overgrowth in children with autism and the efficiency of the organization of the brain in adults with autism.
引用
收藏
页数:12
相关论文
共 50 条
  • [1] Network inefficiencies and brain overgrowth in autism spectrum disorder
    Lewis, John D.
    Theilmann, Rebecca J.
    Townsend, Jeanne
    Evans, Alan
    INTERNATIONAL JOURNAL OF DEVELOPMENTAL NEUROSCIENCE, 2015, 47 : 129 - 129
  • [2] Disrupted Brain Network in Children with Autism Spectrum Disorder
    Zeng, Ke
    Kang, Jiannan
    Ouyang, Gaoxiang
    Li, Jingqing
    Han, Junxia
    Wang, Yao
    Sokhadze, Estate M.
    Casanova, Manuel F.
    Li, Xiaoli
    SCIENTIFIC REPORTS, 2017, 7
  • [3] Disrupted Brain Network in Children with Autism Spectrum Disorder
    Ke Zeng
    Jiannan Kang
    Gaoxiang Ouyang
    Jingqing Li
    Junxia Han
    Yao Wang
    Estate M. Sokhadze
    Manuel F. Casanova
    Xiaoli Li
    Scientific Reports, 7
  • [4] Altered brain network dynamics in youths with autism spectrum disorder
    Malaia, Evie
    Bates, Erik
    Seitzman, Benjamin
    Coppess, Katherine
    EXPERIMENTAL BRAIN RESEARCH, 2016, 234 (12) : 3425 - 3431
  • [5] Abnormal Brain Network Connectivity in Children With Autism Spectrum Disorder
    Zhang, Shu
    Li, Fali
    Jiang, Lin
    Peng, Yueheng
    Yao, Dezhong
    Xu, Peng
    INTERNATIONAL JOURNAL OF PSYCHOPHYSIOLOGY, 2021, 168 : S226 - S226
  • [6] Altered brain network dynamics in youths with autism spectrum disorder
    Evie Malaia
    Erik Bates
    Benjamin Seitzman
    Katherine Coppess
    Experimental Brain Research, 2016, 234 : 3425 - 3431
  • [7] Clinical Correlates of Early Generalized Overgrowth in Autism Spectrum Disorder
    Veenstra-VanderWeele, Jeremy
    McGuire, Kelly
    Shui, Amy M.
    JOURNAL OF THE AMERICAN ACADEMY OF CHILD AND ADOLESCENT PSYCHIATRY, 2015, 54 (11): : 957 - 958
  • [8] Modeling the dynamic brain network representation for autism spectrum disorder diagnosis
    Peng Cao
    Guangqi Wen
    Xiaoli Liu
    Jinzhu Yang
    Osmar R. Zaiane
    Medical & Biological Engineering & Computing, 2022, 60 : 1897 - 1913
  • [9] Modeling the dynamic brain network representation for autism spectrum disorder diagnosis
    Cao, Peng
    Wen, Guangqi
    Liu, Xiaoli
    Yang, Jinzhu
    Zaiane, Osmar R.
    Medical and Biological Engineering and Computing, 2022, 60 (07): : 1897 - 1913
  • [10] Evoked and intrinsic brain network dynamics in children with autism spectrum disorder
    Kupis, Lauren
    Romero, Celia
    Dirks, Bryce
    Hoang, Stephanie
    Parlade, Meaghan V.
    Beaumont, Amy L.
    Cardona, Sandra M.
    Alessandri, Michael
    Chang, Catie
    Nomi, Jason S.
    Uddin, Lucina Q.
    NEUROIMAGE-CLINICAL, 2020, 28