Transient states of network connectivity are atypical in autism: A dynamic functional connectivity study

Abstract

There is ample evidence of atypical functional connectivity (FC) in autism spectrum disorders (ASDs). However, transient relationships between neural networks cannot be captured by conventional static FC analyses. Dynamic FC (dFC) approaches have been used to identify repeating, transient connectivity patterns (“states”), revealing spatiotemporal network properties not observable in static FC. Recent studies have found atypical dFC in ASDs, but questions remain about the nature of group differences in transient connectivity, and the degree to which states persist or change over time. This study aimed to: (a) describe and relate static and dynamic FC in typical development and ASDs, (b) describe group differences in transient states and compare them with static FC patterns, and (c) examine temporal stability and flexibility between identified states. Resting‐state functional magnetic resonance imaging (fMRI) data were collected from 62 ASD and 57 typically developing (TD) children and adolescents. Whole‐brain, data‐driven regions of interest were derived from group independent component analysis. Sliding window analysis and k‐means clustering were used to explore dFC and identify transient states. Across all regions, static overconnnectivity and increased variability over time in ASDs predominated. Furthermore, significant patterns of group differences emerged in two transient states that were not observed in the static FC matrix, with group differences in one state primarily involving sensory and motor networks, and in the other involving higher‐order cognition networks. Default mode network segregation was significantly reduced in ASDs in both states. Results highlight that dynamic approaches may reveal more nuanced transient patterns of atypical FC in ASDs.

Accurate prediction of individual subject identity and task, but not autism diagnosis, from functional connectomes

“…However, it is possible that scanning individuals in a manner even more closely approaching the behavioral domains of ASD—such as during more complex and subtle social interactions (as in, e.g., Byrge et al, ) than the movie trailers included here, or even during actual social interactions (Redcay et al, , )—may serve to better differentiate the groups. Finally, there are of course existing analytic approaches we have not yet applied to this data set and that could be promising directions for differentiating diagnosis groups, including time‐varying functional connectivity (see, e.g., Falahpour et al, ; Mash et al, ) and inter‐subject functional correlation (Simony et al, ) approaches. Future work will explore these directions.…”

A Review of Default Mode Network Connectivity and Its Association With Social Cognition in Adolescents With Autism Spectrum Disorder and Early-Onset Psychosis

“…This coupling of specific functional networks during various timepoints of a resting-state scan are often referred to as "states" or state-dependency" of neural activity (67,120). While some of these studies have found broader temporal variability of DMN connectivity across states in adolescents with ASD (87,101), others show predominant patterns of underconnectivity between the DMN and salience, attentional, and visual networks, which is state-dependent and may be related to social cognition states (90,99). Since DFC is a relatively new realm of functional connectivity research, additional investigations of dynamic DMN connectivity as it relates to adolescents with ASD is warranted to further delineate such state-dependent patterns.…”

“…Similarly, more work examining the impact of disease progression in EOP on DMN connectivity is needed to understand if abnormal DMN connectivity within this population remains relatively stable across the duration of illness or if further declines are associated with longer-term illness. In the ASD population, imaging studies have generally focused on high-functioning individuals, with only one study so far exploring the differences in DMN connectivity between high-and low-functioning ASD adolescents (101). It would be important to explore the influence of such contributing factors to DMN connectivity anomalies to interpret the divergent findings across studies and develop a potential mechanistic model of how genetics, neural wiring, and environmental factors may cascade into the phenotypic features we observe in these neuropsychiatric conditions.…”

Dynamic Functional Connectivity Reveals Abnormal Variability and Hyper‐connected Pattern in Autism Spectrum Disorder

“…Nevertheless, DFC has not been widely used to assess ASD, and most investigations paid more attention to clustering results [de Lacy, Doherty, King, Rachakonda, & Calhoun, 2017;Guo et al, 2018;He et al, 2018;Mash et al, 2019;Rashid et al, 2018;Yao et al, 2016] instead of metrics such as the SD Falahpour et al, 2016;He et al, 2018]. In our work, we give more interest in these straightforward characteristics, which could provide more insight into neural mechanisms underlying ASD in terms of temporal variability.…”