Underconnected, But Not Broken? Dynamic Functional Connectivity MRI Shows Underconnectivity in Autism Is Linked to Increased Intra-Individual Variability Across Time

Abstract

Autism spectrum disorder (ASD) is characterized by core sociocommunicative impairments. Atypical intrinsic functional connectivity (iFC) has been reported in numerous studies of ASD. A majority of findings has indicated long-distance underconnectivity. However, fMRI studies have thus far exclusively examined static iFC across several minutes of scanning. We examined temporal variability of iFC, using sliding window analyses in selected high-quality (low-motion) consortium datasets from 76 ASD and 76 matched typically developing (TD) participants (Study 1) and in-house data from 32 ASD and 32 TD participants. Mean iFC and standard deviation of the sliding window correlation (SD-iFC) were computed for regions of interest (ROIs) from default mode and salience networks, as well as amygdala and thalamus. In both studies, ROI pairings with significant underconnectivity (ASD<TD) were identified. Mediation analyses showed that decreased mean iFC in the ASD groups was significantly affected by increased SD-iFC. Our study is the first to identify temporal variability across time as a significant contributing factor to the common finding of static underconnectivity in ASD. Since peak connectivity across time was not significantly reduced in ASD, static underconnectivity findings may have to be reinterpreted, suggesting that connections are not actually ''broken'' in ASD, but subject to greater intra-individual variability across time. Our findings indicate the need for dynamic approaches to iFC in clinical functional connectivity MRI (fcMRI) investigations.

Altered inter‐ and intrahemispheric functional connectivity dynamics in autistic children

“…It is thus imperative to consider topological location and anatomical distance effects on functional connectivity in future studies exploring brain network abnormalities in ASD (Anderson et al, ; Long, Duan, Mantini, & Chen, ). More importantly, the present study revealed time‐varying abnormalities of intrinsic functional connectivity patterns in children with ASD, which is consistent with previous reports of altered communication dynamics of brain networks in ASD (Chen et al, ; Falahpour et al, ). Therefore, dynamic functional connectome analyses or a combination of static and dynamic functional connectome approaches may serve as a promising way for future research to advance our understanding of this condition (Liao et al, ).…”

“…Investigations of dynamic functional connectivity in ASD have revealed aberrant dynamics of functional connectivity (Chen, Nomi, Uddin, Duan, & Chen, ; Guo et al, ; He et al, ). For example, enhanced temporal variability of intrinsic functional connectivity was observed in individuals with ASD, implying increased intra‐individual variance of brain networks across time (Falahpour et al, ). Moreover, such hypervariant dynamics of the functional connectivity were associated with ASD symptom severity (Chen et al, ).…”

Partially impaired functional connectivity states between right anterior insula and default mode network in autism spectrum disorder

“…Similar dFC studies in epilepsy revealed state‐specific impairments of functional connectivity patterns in participants with epilepsy compared with healthy controls (Liao, Zhang, et al, ; Liu et al, ). Individuals with ASD were also confirmed to exhibit abnormal temporal variability in functional architecture at rest (Falahpour et al, ; He et al, ; Zhang et al, ). Several studies have examined functional connectivity profiles of the rAI at rest in ASD (Abbott et al, ; Ebisch et al, ; von dem Hagen et al, ).…”

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

“…We anticipate that higher DFC variability might reflect abnormal state configuration, and their relationship might provide new insight into ASD studies. To avoid the potential interference of age [Uddin, Supekar, & Menon, ] and keep the ASD scale consistent (i.e., children or adult), we excluded adults in our criteria, unlike prior multisite studies [Chen et al, ; de Lacy et al, ; Falahpour et al, ; Guo et al, ]. Furthermore, to ensure consistency of the temporal scale, we chose data collected with the same repetition time (TR) and adjusted for time points for all subjects.…”