Multi-modal sensory feedback mechanisms of fine and gross motor control in autism spectrum disorders - PROJECT SUMMARY The PI’s long-term goal is to become an independent researcher characterizing neurodevelopmental and phys- iologic mechanisms of sensorimotor integration in autism spectrum disorder (ASD) and their relation to clinical and cognitive outcomes. In pursuit of this goal, the PI has assembled a multidisciplinary mentorship team (Drs. Mosconi, Brumberg, Schmitt, Veatch, and Wang) to support critical training in sensorimotor physiology and de- velopment in typical development (TD) and ASD; electroencephalography (EEG); computational analysis of physiologic and clinical data; and assessment of persons with intellectual disability (ID). The proposed studies were designed to scaffold the training activities and establish the PI’s independent line of research. Sensorimotor deficits are prevalent in ASD and are associated with poorer social-communication and cognitive outcomes, signifying their pivotal role in the development of ASD. Sensorimotor deficits are also common in ID and may be physiologically distinct from those specific to ASD, but individuals with ID, which affects about a third of the autistic population, are often excluded from studies of ASD. Studies of sensorimotor physiology that include autistic individuals with ID are needed to identify physiologic mechanisms contributing to varied clinical and cog- nitive expression in ASD and develop interventions that improve outcomes for autistic individuals. The objective of the proposed project is to clarify sensory feedback and brain mechanisms associated with deficient control of sustained motor behaviors in autistic individuals with and without ID and assess their relation to clinical and cognitive traits. Forty typically developing (TD) controls (aged 8-17yrs), 40 age-, sex-, and IQ-matched autistic individuals and 40 age- and sex-matched autistic individuals with ID will complete tests of precision gripping (fine motor) and postural control (gross motor) with and without EEG. We will manipulate the quality of visual (gain) and somatosensory (tendon vibration; without EEG only) feedback to assess their contributions to each motor behavior. Based on preliminary evidence, we hypothesize that disrupting either sensory input will lead to poorer control of both behaviors in TD controls, but autistic individuals will show decrements only when the primary sensory input (vision for gripping, somatosensory for posture) is disrupted, and this will be associated with re- duced coherence within parietal-motor networks. We also predict greater postural control deficits in autistic indi- viduals with ID when somatosensory feedback is unperturbed, suggesting reduced responsiveness to soma- tosensory feedback during gross motor control in ID, and reduced frontal-parietal coherence during both behav- iors, consistent with reduced cognitive engagement during sustained motor control in individuals with ID. We also will exploit the power of supervised machine learning to identify patterns of sensorimotor physiology that predict clinical and cognitive traits. These studies hold promise for informing neurodevelopmental models of ASD and identifying targets for the development of novel interventions to improve quality of life for autistic individuals.
