Executive Dysfunction in Autism Spectrum Disorder Is Associated With a Failure to Modulate Frontoparietal-insular Hub Architecture

Abstract

BACKGROUND Comorbid executive dysfunction in autism spectrum disorder (ASD) is a barrier to adaptive functioning, despite remittance of core social-communication symptoms. Network models of ASD address core symptoms but not comorbid executive dysfunction. Following recent demonstrations in healthy adults that, with increasing executive demands, hubs embedded within frontoparietal-insular control networks interact with a more diverse set of networks, we hypothesized that the capability of hubs to do so is perturbed in ASD and predicts executive behavior. METHODS Seventy-five 7- to 13-year-old children with ASD (n = 35) and age- and IQ-matched typically developing control subjects (n = 40) completed both a resting-state and a selective attention task functional magnetic resonance imaging session. We assessed changes in the participation coefficient, a graph theory metric indexing hubness, of 264 brain regions comprising 12 functional networks between the two sessions. Parent reported executive impairment in everyday life was measured using the Behavior Rating Inventory of Executive Function. RESULTS The participation coefficient of the frontoparietal-insular cortex, including core nodes of the frontoparietal control and salience networks, significantly increased in typically developing children but not in children with ASD during the task relative to rest. Change in frontoparietal-insular participation coefficient predicted Behavior Rating Inventory of Executive Function scores indexing the ability to attend to task-oriented output, plan and organize, and sustain working memory. CONCLUSIONS Our results suggest that executive impairments in ASD emerge from a failure of frontoparietal-insular control regions to function as adaptive and integrative hubs in the brain’s functional network architecture. Our results also demonstrate the utility of examining dynamic network function for elucidating potential biomarkers for disorders with comorbid executive dysfunction.

Dysregulation of temporal dynamics of synchronous neural activity in adolescents on autism spectrum

“…The present analysis extends the findings to the temporal aspect of synchronization: we demonstrate that average fronto-parietal synchronization is higher in ASD, but with more short periods of desynchronization. Research on neuroanatomical structure changes in ASD has previously connected the difficulty of modulating executive control in high-functioning adolescents on autism spectrum to failure of fronto-parietal regions to function as integrative hubs within the brain's network architecture (Lynch et al, 2017). Although the relationships between behavior and oscillatory activity were not tested directly in the present study, some relationships might be hypothesized from prior work, where decreased theta and alpha coherence were shown to lead to impairment in working memory and between-network binding (particularly as related to executive processing, inhibition, and conscious attention), while beta frequency synchrony has been related to successful higher-order cognitive processing (cf.…”

Deterioro Cognitivo y Demencias en Adultos con Trastorno del Espectro Autista.

“…95 Diversos estudios concuerdan con que estos síntomas neuropsiquiátricos en adultos con TEA tienen un impacto significativo sobre la función adaptativa y cognitiva, produciendo mayores limitaciones en las AVD. [96][97][98][99] Curiosamente, esta premisa ha sido estudiada en la población general sin TEA, donde la evidencia indica que la depresión promueve el deterioro cognitivo y cuadros demenciales de manera precoz a lo largo del ciclo vital. 100…”

The Development of Brain Network Hubs

“…These changes may emerge early on, given evidence that children and neonates at risk or diagnosed with one of these disorders have dysfunctional hub connectivity (Collin et al, 2017;Lynch et al, 2017;Ray et al, 2014;Shi et al, 2012;Xia et al, 2014). One study using generative network modelling found that differences in functional network topology between patients with childhood onset schizophrenia and healthy controls could be reproduced by tuning the parameters of a generative network model such that the penalty on forming long-range connections was reduced (Vértes et al, 2012).…”