Emily Kilroy PhD

Difficulty processing sensory information may impede progress in school for students with autism spectrum disorder (ASD). We explore the relationship between sensory processing and school performance in 26 high‐functioning youths with ASD and 26 controls (age 8–14) using measures of sensory, social, cognitive, and academic functioning. In the ASD group, bivariate Pearson correlations indicated a significant positive relationship between intelligence quotient (IQ) and the School Competence Scale (SCS) of the Child Behavior Checklist (CBCL), and a significant negative relationship between Dunn's Sensory Processing Framework and SCS scores. Final hierarchical multiple linear regression model accounting for SCS scores in ASD included IQ, ADHD symptoms, and sensory features. An interaction between increased sensory sensitivity with reduced sensory avoidance behaviors explained the greatest amount of variance in SCS, meaning school performance is lowest for children with greater hypersensitivity and fewer avoidance behaviors. Results indicate a strong impact of sensory processing on school performance in ASD.

Recent research has reported motor impairment similarities between children with developmental coordination disorder (DCD) and a subgroup of individuals with autism spectrum disorder (ASD). However, there is a debate as to whether DCD is a co-occurring diagnosis in individuals with ASD and motor impairments (ASDd), or if motor impairments in ASD are distinct from DCD. However, the etiology of motor impairments is not well understood in either disorder. Clarifying comorbidities in ASD is important to determine different etiopathological phenotyping clusters in ASD and to understand the variety of genetic and environmental factors that contribute to the disorder. Furthermore, this distinction has important therapeutic relevance. Here we explore the current neuroimaging findings in ASD and DCD and discusses possible neural mechanisms that underlie similarities and differences between the disorders.

Keywords: Autism spectrum disorder (ASD); developmental coordination disorder (DCD); action observation network (AON); functional magnetic resonance imaging (fMRI); resting state; diffusion weighted imaging (DWI)

Abnormal sensory-based behaviors are a defining feature of autism spectrum disorders (ASD). Dr. A. Jean Ayres was the first occupational therapist to conceptualize Sensory Integration (SI) theories and therapies to address these deficits. Her work was based on neurological knowledge of the 1970s. Since then, advancements in neuroimaging techniques make it possible to better understand the brain areas that may underlie sensory processing deficits in ASD. In this article, we explore the postulates proposed by Ayres (i.e., registration, modulation, motivation) through current neuroimaging literature. To this end, we review the neural underpinnings of sensory processing and integration in ASD by examining the literature on neurophysiological responses to sensory stimuli in individuals with ASD as well as structural and network organization using a variety of neuroimaging techniques. Many aspects of Ayres’ hypotheses about the nature of the disorder were found to be highly consistent with current literature on sensory processing in children with ASD but there are some discrepancies across various methodological techniques and ASD development. With additional characterization, neurophysiological profiles of sensory processing in ASD may serve as valuable biomarkers for diagnosis and monitoring of therapeutic interventions, such as SI therapy.

Keywords: Autism Spectrum Disorder (ASD); Ayres Sensory Integration (ASI); sensory processing; functional magnetic resonance imaging (fMRI)

Over the past decade many studies indicate that we utilize our own motor system to understand the actions of other people. This mirror neuron system (MNS) has been proposed to be involved in social cognition and motor learning. However, conflicting findings regarding the underlying mechanisms that drive these shared circuits make it difficult to decipher a common model of their function. Here we propose adapting a “value-driven” model to explain discrepancies in the human mirror system literature and to incorporate this model with existing models. We will use this model to explain discrepant activation patterns in multiple shared circuits in the human data, such that a unified model may explain reported activation patterns from previous studies as a function of value.