Dataset Information

Atypical functional connectome hierarchy in autism.

ABSTRACT: One paradox of autism is the co-occurrence of deficits in sensory and higher-order socio-cognitive processing. Here, we examined whether these phenotypical patterns may relate to an overarching system-level imbalance-specifically a disruption in macroscale hierarchy affecting integration and segregation of unimodal and transmodal networks. Combining connectome gradient and stepwise connectivity analysis based on task-free functional magnetic resonance imaging (fMRI), we demonstrated atypical connectivity transitions between sensory and higher-order default mode regions in a large cohort of individuals with autism relative to typically-developing controls. Further analyses indicated that reduced differentiation related to perturbed stepwise connectivity from sensory towards transmodal areas, as well as atypical long-range rich-club connectivity. Supervised pattern learning revealed that hierarchical features predicted deficits in social cognition and low-level behavioral symptoms, but not communication-related symptoms. Our findings provide new evidence for imbalances in network hierarchy in autism, which offers a parsimonious reference frame to consolidate its diverse features.

SUBMITTER: Hong SJ

PROVIDER: S-EPMC6399265 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Atypical functional connectome hierarchy in autism.

Hong Seok-Jun SJ Vos de Wael Reinder R Bethlehem Richard A I RAI Lariviere Sara S Paquola Casey C Valk Sofie L SL Milham Michael P MP Di Martino Adriana A Margulies Daniel S DS Smallwood Jonathan J Bernhardt Boris C BC

Nature communications 20190304 1

One paradox of autism is the co-occurrence of deficits in sensory and higher-order socio-cognitive processing. Here, we examined whether these phenotypical patterns may relate to an overarching system-level imbalance-specifically a disruption in macroscale hierarchy affecting integration and segregation of unimodal and transmodal networks. Combining connectome gradient and stepwise connectivity analysis based on task-free functional magnetic resonance imaging (fMRI), we demonstrated atypical con ...[more]

PMID: 30833582

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Project description:BACKGROUND:Functional magnetic resonance imaging research on autism spectrum disorders (ASDs) has been largely limited to individuals with near-average intelligence. Although cognitive impairment is common in ASDs, functional network connectivity in this population remains poorly understood. Specifically, it remains unknown whether lower-functioning individuals exhibit exacerbated connectivity abnormalities similar to those previously detected in higher-functioning samples or specific divergent patterns of connectivity. METHODS:Resting-state functional magnetic resonance imaging data from 88 children (44 ASD, 44 typically developing; average age: 11 years) were included. Based on IQ, individuals with ASDs were assigned to either a lower-functioning group (mean IQ = 77 ± 6) or a higher-functioning group (mean IQ = 123 ± 8). Two typically developing comparison groups were matched to these groups on head motion, handedness, and age. Seeds in the medial prefrontal cortex, posterior cingulate cortex, posterior superior temporal sulcus, insula, and amygdala were used to contrast whole-brain functional connectivity across groups. RESULTS:Lower-functioning ASD participants (compared with higher-functioning ASD participants) showed significant underconnectivity within the default mode network and the ventral visual stream. Higher-functioning ASD participants (compared with matched typically developing participants) showed significantly decreased anticorrelations among default mode, salience, and task-positive regions. Effect sizes of detected differences were large (Cohen's d > 1.46). CONCLUSIONS:Lower- and higher-functioning individuals with ASDs demonstrated distinct patterns of atypical connectivity. Findings suggest a gross pattern of predominantly reduced network integration in lower-functioning ASDs (affecting default mode and visual networks) and predominantly reduced network segregation in higher-functioning ASDs. Results indicate the need for stratification by general functional level in studies of functional connectivity in ASDs.

Project description:BackgroundAutism spectrum disorder (autism) is a complex neurodevelopmental condition with pronounced behavioral, cognitive, and neural heterogeneities across individuals. Here, our goal was to characterize heterogeneity in autism by identifying patterns of neural diversity as reflected in BOLD fMRI in the way individuals with autism engage with a varied array of cognitive tasks.MethodsAll analyses were based on the EU-AIMS/AIMS-2-TRIALS multisite Longitudinal European Autism Project (LEAP) with participants with autism (n = 282) and typically developing (TD) controls (n = 221) between 6 and 30 years of age. We employed a novel task potency approach which combines the unique aspects of both resting state fMRI and task-fMRI to quantify task-induced variations in the functional connectome. Normative modelling was used to map atypicality of features on an individual basis with respect to their distribution in neurotypical control participants. We applied robust out-of-sample canonical correlation analysis (CCA) to relate connectome data to behavioral data.ResultsDeviation from the normative ranges of global functional connectivity was greater for individuals with autism compared to TD in each fMRI task paradigm (all tasks p < 0.001). The similarity across individuals of the deviation pattern was significantly increased in autistic relative to TD individuals (p < 0.002). The CCA identified significant and robust brain-behavior covariation between functional connectivity atypicality and autism-related behavioral features.ConclusionsIndividuals with autism engage with tasks in a globally atypical way, but the particular spatial pattern of this atypicality is nevertheless similar across tasks. Atypicalities in the tasks originate mostly from prefrontal cortex and default mode network regions, but also speech and auditory networks. We show how sophisticated modeling methods such as task potency and normative modeling can be used toward unravelling complex heterogeneous conditions like autism.

Dataset Information

Atypical functional connectome hierarchy in autism.

Publications

Atypical functional connectome hierarchy in autism.

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