Sensory-to-Cognitive Systems Integration Is Associated With Clinical Severity in Autism Spectrum Disorder

doi:10.1016/j.jaac.2019.05.033

Journal of the American Academy of Child & Adolescent Psychiatry

Volume 59, Issue 3, March 2020, Pages 422-433

https://doi.org/10.1016/j.jaac.2019.05.033 Get rights and content

Objective

Impaired multisensory integration in autism spectrum disorder (ASD) may arise from functional dysconnectivity among brain systems. Our study examines the functional connectivity integration between primary modal sensory regions and heteromodal processing cortex in ASD, and whether abnormalities in network integration relate to clinical severity.

Method

We studied a sample of 55 high-functioning ASD and 64 healthy control (HC) male children and adolescents (total n = 119, age range 7−18 years). Stepwise functional connectivity analysis (SFC) was applied to resting state functional magnetic resonance images (rsfMRI) to characterize the connectivity paths that link primary sensory cortices to higher-order brain cognitive functional circuits and to relate alterations in functional connectivity integration with three clinical scales: Social Communication Questionnaire, Social Responsiveness Scale, and Vineland Adaptive Behavior Scales.

Results

HC displayed typical functional connectivity transitions from primary sensory systems to association areas, but the ASD group showed altered patterns of multimodal sensory integration to heteromodal systems. Specifically, compared to the HC group, the ASD group showed the following: (1) hyperconnectivity in the visual cortex at initial link step distances; (2) hyperconnectivity between sensory unimodal regions and regions of the default mode network; and (3) hypoconnectivity between sensory unimodal regions and areas of the fronto-parietal and attentional networks. These patterns of hyper- and hypoconnectivity were associated with increased clinical severity in ASD.

Conclusion

Networkwise reorganization in high-functioning ASD individuals affects strategic regions of unimodal-to-heteromodal cortical integration predicting clinical severity. In addition, SFC analysis appears to be a promising approach for studying the neural pathophysiology of multisensory integration deficits in ASD.

Section snippets

Sample Description

We examined a subsample of the aggregated multisite dataset provided by the ABIDE I (http://fcon_1000.projects.nitrc.org/indi/abide/abide_I.html) and ABIDE II (http://fcon_1000.projects.nitrc.org/indi/abide/abide_II.html) initiatives. The ABIDE I repository consists of 1,112 data sets including 539 patients with ASD and 573 HC. ABIDE II was established to further promote discovery science on the brain connectome in ASD. The ABIDE II repository consists of 1,114 data sets including 521 patients

Stepwise Functional Connectivity Maps in HC and ASD

Figure 2 shows the right hemisphere SFC maps for the HC and ASD groups (Figure S2, available online, includes left hemispheres SFC maps). Overall, HC and ASD displayed similar connectivity streams at early link-step distances. At one and two link-step distances, both groups showed functional connectivity among unimodal sensory systems. However, there was a qualitative difference at the third link-step distance between the statistical maps computed for the ASD and HC groups. Compared to the HC

Discussion

In the current study, we used stepwise functional connectivity analysis to characterize the connectivity paths that link primary sensory cortices to higher-order brain cognitive functional circuits in ASD and evaluate whether abnormalities in network integration relate to clinical severity. We found atypical functional transitions from unimodal to multimodal cortical areas in high-functioning male children and adolescents with ASD compared to HC individuals. Specifically, abnormal functional

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Sensory differences are common and often challenging for autistic children. Furthermore, atypical sensory processing is associated with autistic traits and other autism-related behaviors, such as intolerance of uncertainty (IU). Such traits and their relatedness vary continuously across autistic and non-autistic children alike. However, the underlying neural correlates of these continuous variables, and their associations, are not well understood. Therefore, this study examined relationships between sensory processing, IU, autistic traits, and associated resting state brain connectivity, across a sample of both autistic (n = 30) and non-autistic (n = 26) children. In addition to computing behavioral correlations between these factors, we carried out independent component network functional connectivity analysis to investigate associations between cortical and cerebellar networks and behavioral results between groups and across our entire sample. Across-group correlations between sensory processing, autistic traits, and IU were significant. In addition, data demonstrated overlapping sensory processing and intolerance of uncertainty scores, spanning the groups. Brain (rs-fMRI)—behavioral relationships revealed strong associations between sensory, large-scale resting state, and cerebellar networks and behavioral scores. Overall, our findings suggest that sensory differences are related to IU and autistic traits across the population. Neurophysiologic data pointed to functional connectivity between sensory cortices and supramodal brain networks. These findings provide evidence for the continuous variation of behaviors common to autism throughout the entire population and their neurobiological correlates.
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Citation Excerpt :
First, which neuroimaging features would capture the main biological variability of autism is unclear, especially for those in functional magnetic resonance imaging (fMRI). Indeed, while numerous features have been proposed to reveal FC patterns specific to ASD (Maximo et al., 2013; Martínez et al., 2020; Cardinale et al., 2013), our understanding of atypical organization of functional brain systems in this condition remains incomplete. Notably, however, an emerging literature has reported a utility of dimensionality reduction techniques to represent large-scale FC as a series of low-dimensional spatial axes, each visualizing smoothly changing connectome transition along the cortical mantle (Margulies et al., 2016).
Clinical heterogeneity has been one of the main barriers to develop effective biomarkers and therapeutic strategies in autism spectrum disorder (ASD). Recognizing this challenge, much effort has been made in recent neuroimaging studies to find biologically more homogeneous subgroups (called ‘neurosubtypes’) in autism. However, most approaches have rarely evaluated how much the employed features in subtyping represent the core anomalies of ASD, obscuring its utility in actual clinical diagnosis. To address this, we combined two data-driven methods, ‘connectome-based gradient’ and ‘functional random forest’, collectively allowing to discover reproducible neurosubtypes based on resting-state functional connectivity profiles that are specific to ASD. Indeed, the former technique provides the features (as input for subtyping) that effectively summarize whole-brain connectome variations in both normal and ASD conditions, while the latter leverages a supervised random forest algorithm to inform diagnostic labels to clustering, which makes neurosubtyping driven by the features of ASD core anomalies. Applying this framework to the open-sharing Autism Brain Imaging Data Exchange repository data (discovery, n = 103/108 for ASD/typically developing [TD]; replication, n = 44/42 for ASD/TD), we found three dominant subtypes of functional gradients in ASD and three subtypes in TD. The subtypes in ASD revealed distinct connectome profiles in multiple brain areas, which are associated with different Neurosynth-derived cognitive functions previously implicated in autism studies. Moreover, these subtypes showed different symptom severity, which degree co-varies with the extent of functional gradient changes observed across the groups. The subtypes in the discovery and replication datasets showed similar symptom profiles in social interaction and communication domains, confirming a largely reproducible brain-behavior relationship. Finally, the connectome gradients in ASD subtypes present both common and distinct patterns compared to those in TD, reflecting their potential overlap and divergence in terms of developmental mechanisms involved in the manifestation of large-scale functional networks. Our study demonstrated a potential of the diagnosis-informed subtyping approach in developing a clinically useful brain-based classification system for future ASD research.

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: Dr. Martínez and Ms. Martínez-García are co-first authors of this article. Drs. Sepulcre and Carmona are co-last authors of this article.

: This work was supported by the Spanish Ministry of Science, Innovation and Universities, Instituto de Salud Carlos III (PI14/0210; PIE16/00055; PI17/00819; PI17/01997; FI18/00255; CP16/00096; PI17/00064), co-financed by ERDF Funds from the European Commission, “A way of making Europe”, CIBERSAM, European Union Structural Funds and European Union Seventh Framework Program and H2020 Program under the Innovative Medicines Initiative 2 Joint Undertaking (grant agreement No 777394, Project AIMS-2-TRIALS), ERA-NET NEURON (Network of European Funding for Neuroscience Research), Fundación Familia Alonso, Fundación Alicia Koplowitz, and Fundación Mutua Madrileña.

: Disclosure: Drs. Martínez, Janssen, Castellanos, Pretus, Villarroya, Pina-Camacho, Díaz-Caneja, Parellada, Arango, Desco, Sepulcre, and Carmona, Ms. Martínez-García, and Mr. Marcos-Vidal have reported no biomedical financial interests or potential conflicts of interest.

View full text

New researchSensory-to-Cognitive Systems Integration Is Associated With Clinical Severity in Autism Spectrum Disorder

Objective

Method

Results

Conclusion

Section snippets

Sample Description

Stepwise Functional Connectivity Maps in HC and ASD

Discussion

Neurosci Biobehav Rev

J Am Acad Child Adolesc Psychiatry

Neuroimage

Behav Brain Res

Neuron

Neuroimage

Brain Res

Brain Cogn

Neuroimage

Neuron

Neurosci Biobehav Rev

Cell Rep

Diagnostic and Statistical Manual of Mental Disorders: DSM-IV-TR

Sensory processing in autism: a review of neurophysiologic findings

Pediatr Res

Autism as a selective disorder of complex information processing and underdevelopment of neocortical systems

Mol Psychiatry

Describing the sensory abnormalities of children and adults with autism

J Autism Dev Disord

Multisensory processing in children with autism: high-density electrical mapping of auditory-somatosensory integration

Autism Res

The development of multisensory integration in high-functioning autism: high-density electrical mapping and psychophysical measures reveal impairments in the processing of audiovisual inputs

Cereb Cortex

The impact of multisensory integration deficits on speech perception in children with autism spectrum disorders

Front Psychol

Radial cytoarchitecture and patterns of cortical connectivity in autism

Philos Trans R Soc B Biol Sci

Increased functional connectivity between subcortical and cortical resting-state networks in Autism spectrum disorder

JAMA Psychiatry

New research
Sensory-to-Cognitive Systems Integration Is Associated With Clinical Severity in Autism Spectrum Disorder