The relationships between dynamic resting-state networks and social behavior in autism spectrum disorder revealed by fuzzy entropy–based temporal variability analysis of large-scale network

Abstract

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder characterized by a core deficit in social processes. However, it is still unclear whether the core clinical symptoms of the disorder can be reflected by the temporal variability of resting-state network functional connectivity (FC). In this article, we examined the large-scale network FC temporal variability at the local region, within-network, and between-network levels using the fuzzy entropy technique. Then, we correlated the network FC temporal variability to social-related scores. We found that the social behavior correlated with the FC temporal variability of the precuneus, parietal, occipital, temporal, and precentral. Our results also showed that social behavior was significantly negatively correlated with the temporal variability of FC within the default mode network, between the frontoparietal network and cingulo-opercular task control network, and the dorsal attention network. In contrast, social behavior correlated significantly positively with the temporal variability of FC within the subcortical network. Finally, using temporal variability as a feature, we construct a model to predict the social score of ASD. These findings suggest that the network FC temporal variability has a close relationship with social behavioral inflexibility in ASD and may serve as a potential biomarker for predicting ASD symptom severity.

Identification and analysis of autism spectrum disorder via large‐scale dynamic functional network connectivity

“…However, the choice of window length is an unavoidable problem in assessing the dFNC (Zhuang et al, 2020). A smaller window length could capture temporal transients but at the cost of increased sensitivity to noise and the introduction of spurious fluctuations (Savva et al, 2019), while a larger window length could produce stable results but may miss valuable short‐term fluctuations (Feng et al, 2022). To accurately determine the optimal window length, we set a window length range of the 20–150s (10–75 TRs), which is in line with previous studies (Shirer et al, 2012).…”

Altered default mode network causal connectivity patterns in autism spectrum disorder revealed by Liang information flow analysis

“…The DMN is a higher‐order cognitive network that shows substantial overlap with the “social brain” network (Blakemore, 2008 ). Many studies have reported that abnormal functional network patterns within‐ and between‐DMN were closely associated with social deficits in ASD (Feng et al, 2022 ; Lynch et al, 2013 ; Padmanabhan et al, 2017 ). The FC alteration in DMN could be a potential endophenotype for social deficits in ASD (Feng et al, 2022 ) because the DMN architecture has an important impact on the information integration of the brain during rest and task performance (Smallwood et al, 2021 ).…”

“…Many studies have reported that abnormal functional network patterns within‐ and between‐DMN were closely associated with social deficits in ASD (Feng et al, 2022 ; Lynch et al, 2013 ; Padmanabhan et al, 2017 ). The FC alteration in DMN could be a potential endophenotype for social deficits in ASD (Feng et al, 2022 ) because the DMN architecture has an important impact on the information integration of the brain during rest and task performance (Smallwood et al, 2021 ). Thirty years of brain imaging research have converged to uncover that the DMN is a heterogeneous brain system network that can be further fractionated into multiple dissociated “subsystems” and/or “subnetworks” (Andrews‐Hanna et al, 2010 ).…”

“…Monk et al (2009) found that the functional connectivity (FC) between the PCC and superior frontal gyrus was decreased, while the FC between the PCC and the right temporal lobe and right parahippocampal gyrus were increased in ASD by comparing with the control group. In our previous study, we also found that low intra-DMN FC variability was associated with social deficits in ASD (Feng et al, 2022). However, these studies are mainly based on FC analysis, which cannot capture the direction of information interaction.…”

“…Yet, the pathophysiology of ASD remains unknown. Most previous studies have reported that the abnormal functional connectivity patterns within and between the default mode network (DMN) are highly related to the clinical symptoms of ASD (Assaf et al, 2010 ; Feng et al, 2022 ; Lombardo et al, 2019 ). However, the causal connectivity pattern within the DMN in ASD, which is believed to provide an important clue to understanding the underlying neuro‐mechanism of ASD, remains largely unclear.…”