Context-dependent turning of muscle spindles

Project Summary Muscle spindles provide sensory information critical for our balance and movement, yet their firing during active conditions remains poorly understood. This lack of understanding of muscle spindle function in voluntary conditions creates both scientific and clinical barriers to understanding the role of muscle spindles in healthy and impaired control of balance and movement. While the efferent drives to the gamma motor neurons (gamma drive) that innervate the muscle spindle are known to modulate the sensory signals from the muscle spindle according to the internal state (including attention, emotion, and task-goal), much of the studies are done using passive imposed movements. We propose a novel approach combining a computational biophysical model of muscle spindles with direct recordings from human leg muscle spindles using microneurography and muscle fascicles using ultrasound during voluntary isolated-joint and standing balance tasks. PI Ting and Co-I Simha have recently developed a computational model of muscle spindle that simulates the intrafusal crossbridge dynamics, allowing it to be generalized to a variety of movement conditions. The model predicts that the muscle spindle firing follows muscle fascicle length changes during passively imposed movements, including an initial burst at the beginning of the first stretch. Collaborator Bent is one of the handful of people in the world who can obtain microneurography measurements from human lower limbs and has recently published on the relationship between muscle fascicle length and muscle spindle firing in the human leg muscles in response to imposed sinusoidal movements during seated rest conditions. In Aim 1, we propose to measure muscle spindle firing in response to similar sinusoidal movements performed voluntarily and to use our model to understand the observed muscle spindle firing in the context of differing gamma drives. In Aim 2, we will extend our model to understand muscle spindle firing during natural and robotically-assisted postural sway. We will use the expertise of Collaborator Blouin, who has designed a unique robotic device that can decouple body part movements during human standing balance to identify sensorimotor control mechanisms. This unique combination of recent developments in computational modelling and robotic technology with the delicate and increasingly rare microneurography method allows us to understand muscle spindle function in the lower limbs during voluntary behavior in humans. The only data from human muscle spindles during voluntary movement are from many decades ago when technological limitations prevented measurements of muscle fascicle kinematics, application of decoupled body part movements during standing balance, and using computational models to infer the role of gamma drive, all combined in one experiment. The results from this proposal will significantly advance our basic understanding of human sensorimotor control of balance and movement, as well as provide a mechanistic framework for understanding neuromotor impairments such as spasticity that may arise from the dysregulation of gamma drive in chronic motor impairments in conditions such as cerebral palsy, stroke or spinal cord injury.