Heterogeneity of dynamic synergetic configurations of salience network in children with autism spectrum disorder.
ASD kids fall into two brain-based subtypes that link to either communication or repetitive behavior issues.
01Research in Context
What this study did
The team scanned the kids with ASD and 100 typical kids during rest.
They tracked how the salience network talked to other brain areas over time.
Math tools grouped kids by the strength and direction of these talks.
What they found
Two clear ASD clusters popped out.
In cluster 1, the salience network was extra chatty; these kids had worse communication scores.
In cluster 2, the network was unusually quiet; these kids showed more repetitive behaviors.
How this fits with other research
Li et al. (2024) adds a sex lens. They found girls with ASD show tighter global brain links than boys. This suggests the two clusters here might split further when you look at boys versus girls.
Zhao et al. (2024) used a different math model but also saw ASD brains stuck in a hyper-connected state. Their result lines up with cluster 1’s extra-chatter pattern.
Mazurek et al. (2019) looked deeper into cortico-subcortical wires. They saw over-connected sensory links and under-connected higher-order links. These patterns match the two opposite directions found here, giving the clusters a wiring explanation.
Why it matters
You can’t scan every child, but you can watch for signs. If a child shows strong sensory seeking and poor language, think cluster 1. If a child shows rigid routines with milder language issues, think cluster 2. Tailor your goals: boost communication for cluster 1, build flexibility for cluster 2.
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02At a glance
03Original abstract
Atypical functional connectivity (FC) patterns have been identified in autism spectrum disorders (ASD), especially within salience network (SN) and between SN and default mode network (DMN) and central executive network (CEN). But whether the dynamic configuration of intra-SN and inter-SN (SN with DMN and CEN) FC in ASD is also heterogeneous remains unknown. Based on the resting-state functional magnetic resonance imaging data from 105 ASD and 102 typically-developing controls (TC), we calculated the time-varying FC of intra-SN and inter-SN (SN with DMN and CEN). Then, the joint recurrence features for the time-varying FC were calculated to assess how the SN dynamically recruits different configurations of network segregation and integration in ASD, that is, synergies, from the dynamical systems perspective. We analyzed the differences in synergetic patterns between ASD subtypes obtained by k-means clustering algorithm based on the synergy of SN and TC, and investigated the relationships between synergy of SN and severity of clinical symptoms of ASD for ASD subtypes. Two ASD subtypes were revealed, where the synergy of SN in ASD subtype 1 has lower stability and periodicity compared to the TC, and ASD subtype 2 exhibits the opposite alteration. Synergy of SN for ASD subtype 1 and 2 was found to predict the severity of communication impairments and restricted and repetitive behaviors in ASD, respectively. These results suggest the existence of subtypes with distinct patterns of the synergy of SN in ASD, and provide insight into the complex pathophysiological mechanism of clinical manifestations of ASD.
Autism research : official journal of the International Society for Autism Research, 2023 · doi:10.1002/aur.3037