期刊
DEVELOPMENTAL COGNITIVE NEUROSCIENCE
卷 36, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.dcn.2019.100630
关键词
Brain-behavior relationships; Mean square successive difference; Partial least squares; Resting-state fMRI; Sample entropy
资金
- Ontario Graduate Scholarship
- Finkler Graduate Student Fellowship
- Natural Sciences and Engineering Research Council of Canada [RGPIN-2018-04457]
Variability of neural signaling is an important index of healthy brain functioning, as is signal complexity, which relates to information processing capacity. Alterations in variability and complexity may underlie certain brain dysfunctions. Here, resting-state fMRI was used to examine variability and complexity in children and adolescents with and without autism spectrum disorder (ASD). Variability was measured using the mean square successive difference (MSSD) of the time series, and complexity was assessed using sample entropy. A categorical approach was implemented to determine if the brain measures differed between diagnostic groups (ASD and controls). A dimensional approach was used to examine the continuum of relationships between each brain measure and behavioral severity, age, IQ, and the global efficiency (GE) of each participant's structural connectome, which reflects the structural capacity for information processing. Using the categorical approach, no significant group differences were found for neither MSSD nor entropy. The dimensional approach revealed significant positive correlations between each brain measure, GE, and age. Negative correlations were observed between each brain measure and the severity of ASD behaviors across all participants. These results reveal the nature of variability and complexity of BOLD signals in children and adolescents with and without ASD.
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