BOLD signal variability and complexity in children and adolescents with and without autism spectrum disorder

Amanda K Easson,Anthony R Mcintosh

doi:10.1016/j.dcn.2019.100630

Amanda K Easson, Anthony R Mcintosh

Open Access

https://doi.org/10.1016/j.dcn.2019.100630

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Abstract

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.

Highlights

Two key components of healthy brain functioning are variability of neural signaling and complexity of these signals
Based on previous work examining correlations between global efficiency (GE) and age that controlled for effects of head motion (Rudie et al, 2012), we examined the correlation between GE and mean framewise displacement (FD) that was calculated for the Diffusion weighted imaging (DWI) scans, and found that this relationship was significant, r(35) = −0.39, p = 0.02
To ensure that any group differences in mean square successive difference (MSSD) and entropy in the gray matter ROIs were not confounded by residual effects of head motion, we first performed a behavioral Partial least squares (PLS) using mean FD as the “behaviour” variable

Summary

Introduction

Two key components of healthy brain functioning are variability of neural signaling and complexity of these signals. Variability changes in response to task demands: BOLD variability has been shown to be lowest in the resting-state, increased during internally focused tasks, and highest during externally focused tasks (Grady and Garrett, 2018). It has been suggested that variability allows for greater environmental uncertainty during externally-directed compared to internally-directed tasks, and variable, flexible neural signaling allows the brain to adapt to such uncertainty (Grady and Garrett, 2018). Several studies have examined age related changes in brain signal variability. Using fMRI, Nomi et al (2017) found that MSSD decreased from ages 6 to 85 in the majority of brain regions examined. In attention deficit hyperactivity disorder (ADHD), positive correlations have been reported between symptom severity and MSSD in default mode regions (Nomi et al, 2018)

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