Atypical sensory-based behaviors are a ubiquitous feature of autism spectrum disorders (ASD). In this article, we review the neural underpinnings of sensory processing in autism by reviewing the literature on neurophysiological responses to auditory, tactile, and visual stimuli in autistic individuals. We review studies of unimodal sensory processing and multi-sensory integration that use a variety of neuroimaging techniques, including: electroencephalography (EEG), magnetoencephalography (MEG), and functional Magnetic Resonance Imaging (fMRI). We then explore the impact of covert and overt attention on sensory processing. With additional characterization, neurophysiologic profiles of sensory processing in ASD may serve as valuable biomarkers for diagnosis and monitoring of therapeutic interventions for autism and reveal potential strategies and target brain regions for therapeutic interventions.

Lay Abstract Autism spectrum disorders are reported to affect nearly one out of every one hundred children, with over 90% of these children showing behavioral disturbances related to the processing of basic sensory information. Behavioral sensitivity to light touch, such as profound discomfort with clothing tags and physical contact, is a ubiquitous finding in children on the autism spectrum. In this study, we investigate the strength and timing of brain activity in response to simple, light taps to the fingertip. Our results suggest that children with autism show a diminished early response in the primary somatosensory cortex (S1). This finding is most evident in the left hemisphere. In exploratory analysis, we also show that tactile sensory behavior, as measured by the Sensory Profile, may be a better predictor of the intensity and timing of brain activity related to touch than a clinical autism diagnosis. We report that children with atypical tactile behavior have significantly lower amplitude somatosensory cortical responses in both hemispheres. Thus sensory behavioral phenotype appears to be a more powerful strategy for investigating neural activity in this cohort. This study provides evidence for atypical brain activity during sensory processing in autistic children and suggests that our sensory behavior based methodology may be an important approach to investigating brain activity in people with autism and neurodevelopmental disorders. Scientific Abstract The neural underpinnings of sensory processing differences in autism remain poorly understood. This prospective magnetoencephalography (MEG) study investigates whether children with autism show atypical cortical activity in the primary somatosensory cortex (S1) in comparison to matched controls. Tactile stimuli were clearly detectable, painless taps applied to the distal phalanx of the second (D2) and third (D3) fingers of the right and left hands. Three tactile paradigms were administered: an oddball paradigm (standard taps to D3 at an inter-stimulus interval (ISI) of 0.33 and deviant taps to D2 with ISI ranging from 1.32–1.64s); a slow-rate paradigm (D2) with an ISI matching the deviant taps in the oddball paradigm; and a fast-rate paradigm (D2) with an ISI matching the standard taps in the oddball. Study subjects were boys (age 7–11 years) with and without autism disorder. Sensory behavior was quantified using the Sensory Profile questionnaire. Boys with autism exhibited smaller amplitude left hemisphere S1 response to slow and deviant stimuli during the right hand paradigms. In post-hoc analysis, tactile behavior directly correlated with the amplitude of cortical response. Consequently, the children were re-categorized by degree of parent-report tactile sensitivity. This regrouping created a more robust distinction between the groups with amplitude diminution in the left and right hemispheres and latency prolongation in the right hemisphere in the deviant and slow-rate paradigms for the affected children. This study suggests that children with aut...

The relationship between the brain's structural wiring and the functional patterns of neural activity is of fundamental interest in computational neuroscience. We examine a hierarchical, linear graph spectral model of brain activity at mesoscopic and macroscopic scales. The model formulation yields an elegant closed‐form solution for the structure–function problem, specified by the graph spectrum of the structural connectome's Laplacian, with simple, universal rules of dynamics specified by a minimal set of global parameters. The resulting parsimonious and analytical solution stands in contrast to complex numerical simulations of high dimensional coupled nonlinear neural field models. This spectral graph model accurately predicts spatial and spectral features of neural oscillatory activity across the brain and was successful in simultaneously reproducing empirically observed spatial and spectral patterns of alpha‐band (8–12 Hz) and beta‐band (15–30 Hz) activity estimated from source localized magnetoencephalography (MEG). This spectral graph model demonstrates that certain brain oscillations are emergent properties of the graph structure of the structural connectome and provides important insights towards understanding the fundamental relationship between network topology and macroscopic whole‐brain dynamics. .

Autism spectrum disorders (ASD) have numerous etiologies, including structural brain malformations such as agenesis of the corpus callosum (AgCC). We sought to directly measure the occurrence of autism traits in a cohort of individuals with AgCC and to investigate the neural underpinnings of this association. We screened a large AgCC cohort (n = 106) with the Autism Spectrum Quotient (AQ) and found that 45% of children, 35% of adolescents, and 18% of adults exceeded the predetermined autism-screening cut-off. Interestingly, performance on the AQ’s imagination domain was inversely correlated with magnetoencephalography measures of resting-state functional connectivity in the right superior temporal gyrus. Individuals with AgCC should be screened for ASD and disorders of the corpus callosum should be considered in autism diagnostic evaluations as well.

Schizophrenia is characterized by dysfunction in basic auditory processing, as well as higher-order operations of verbal learning and executive functions. We investigated whether targeted cognitive training of auditory processing improves neural responses to speech stimuli, and how these changes relate to higher-order cognitive functions. Patients with schizophrenia performed an auditory syllable identification task during magnetoencephalography before and after 50 hours of either targeted cognitive training or a computer games control. Healthy comparison subjects were assessed at baseline and after a 10 week no-contact interval. Prior to training, patients (N = 34) showed reduced M100 response in primary auditory cortex relative to healthy participants (N = 13). At reassessment, only the targeted cognitive training patient group (N = 18) exhibited increased M100 responses. Additionally, this group showed increased induced high gamma band activity within left dorsolateral prefrontal cortex immediately after stimulus presentation, and later in bilateral temporal cortices. Training-related changes in neural activity correlated with changes in executive function scores but not verbal learning and memory. These data suggest that computerized cognitive training that targets auditory and verbal learning operations enhances both sensory responses in auditory cortex as well as engagement of prefrontal regions, as indexed during an auditory processing task with low demands on working memory. This neural circuit enhancement is in turn associated with better executive function but not verbal memory.