Abstract

IntroductionOur flexible and adaptive interactions with the environment are guided by our individual representation of the physical world, estimated through sensation and evaluation of available information against prior knowledge. When linking sensory evidence with higher‐level expectations for action, the central nervous system (CNS) in typically developing (TD) individuals relies in part on distributed and interacting cortical regions to communicate neuronal signals flexibly across the brain. Increasing evidence suggests that the balance between levels of signal and noise during information processing may be disrupted in individuals with Autism Spectrum Disorders (ASD).MethodsParticipants with and without ASD performed a visuospatial interference task while undergoing functional Magnetic Resonance Imaging (fMRI). We empirically estimated parameters characterizing participants’ latencies and their subtle fluctuations (noise accumulation) over the 16‐min scan. We modeled hemodynamic activation and used seed‐based analyses of neural coupling to study dysfunction in interference‐specific connectivity in a subset of ASD participants who were nonparametrically matched to TD participants on age, male‐to‐female ratio, and magnitude of movement during the scan.ResultsStochastic patterns of response fluctuations reveal significantly higher noise‐to‐signal levels and a more random and noisy structure in ASD versus TD participants, and in particular ASD adults who have the greatest clinical autistic deficits. While individuals with ASD show an overall weaker modulation of interference‐specific functional connectivity relative to TD individuals, in particular between the seeds of Anterior Cingulate Cortex (ACC) and Inferior Parietal Sulcus (IPS) and the rest of the brain, we found that in ASD, higher uncertainty during the task is linked to increased interference‐specific coupling between bilateral anterior insula and prefrontal cortex.ConclusionsSubtle and informative differences in the structure of experiencing information exist between ASD and TD individuals. Our findings reveal in ASD an atypical capacity to apply previously perceived information in a manner optimal for adaptive functioning, plausibly revealing suboptimal message‐passing across the CNS.

Highlights

  • Our flexible and adaptive interactions with the environment are guided by our individual representation of the physical world, estimated through sensation and evaluation of available information against prior knowledge

  • We found that Autism Spectrum Disorders (ASD) adults in the high ADOS subgroup had a significantly worse mu parameter, with nonoverlapping 95% Confidence Intervals (CIs) relative to both adult typically developing (TD) controls and adults with ASD in the lower median-­ split group (Figure 4B, right panel)

  • Subtle and informative differences in the structure of experiencing information exist between individuals with ASD and TD controls across multiple levels of inquiry

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Summary

Introduction

Our flexible and adaptive interactions with the environment are guided by our individual representation of the physical world, estimated through sensation and evaluation of available information against prior knowledge. When linking sensory evidence with higher-­level expectations for action, the central nervous system (CNS) in typically developing (TD) individuals relies in part on distributed and interacting cortical regions to communicate neuronal signals flexibly across the brain. Increasing evidence suggests that the balance between levels of signal and noise during information processing may be disrupted in individuals with Autism Spectrum Disorders (ASD). Spontaneous, resting-­state functional connectivity MRI (rs-­fcMRI) studies report evidence for atypicalities in both local-­and global-s­ cale network processing in ASD (e.g., Ecker et al, 2013; Khan et al, 2013), suggesting the presence of compromised communication among brain regions, recent work has questioned the underconnectivity hypothesis, with some researchers finding normal resting-­state patterns in individuals with ASD (e.g., Tyszka, Kennedy, Paul, & Adolphs, 2014)

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