Proprioceptive models for control of movement

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 DESCRIPTION (provided by applicant): Crucial to controlling movements is our bodies' sense of limb state arising from mechanically gated neurons located within the musculotendon, called proprioceptors. Understanding the mechanical encoding of proprioceptors is critical to understanding their roles in sensorimotor behaviors such as balance control. Proprioceptive loss due to aging, diabetes, as well as chemotherapy-induced peripheral neuropathy (CIPN) and other disorders can increase the risk for falls, which is the leading cause of morbidity and mortality in older adults. Neuromechanical models are essential for predicting the impact of sensory loss on movement because proprioceptors are difficult to access and measure from during actual movements. Here, the goal is to develop a parsimonious model of proprioceptive function appropriate for predictive modeling of sensorimotor control in healthy and neuropathic conditions. Specifically, this work aims to directly test what information is encoded in the instantaneous firing rates and aggregate firing activity of proprioceptors in healthy cat (Specific Aim 1) and in healthy and CIPN rat (Specific Aim 2). Preliminary data suggest that group Ia proprioceptors encode information related to musculotendon kinetics (i.e. passive tension and its first time derivative), but not kinematics (i.e. length and velocity) as previously thought. Usng a combination of previously collected and new datasets with simple musculotendon and spiking neuron model, the proposed work will explicitly test hypotheses about the relationship between firing rates and aggregate activity of group Ia, Ib, and II proprioceptors and musculotendon kinetics in anesthetized cat (healthy) and rat (healthy and neuropathic).