Generation of Motor Cortical Dynamics Controlling Skilled Locomotion

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PROJECT SUMMARY Walking over natural terrain with skill and flexibility requires the nervous system to adapt limb movements to environmental demands on each step. To drive the limbs over an obstacle without stumbling, the brain must generate commands to modulate the appropriate muscle synergies at a specific phase of the ongoing locomotor rhythm. The loss or impairment of these commands in disease can result in falls, which are common in older adults and impose a significant burden on the healthcare system. While previous studies have demonstrated that the motor cortex is critical for skilled locomotion, two key gaps currently impede progress in developing models of cortical control. First, because gait modification is controlled by coordinated patterns of activity across the motor cortical population, it is necessary to measure these population-level patterns in behaving animals, and to identify how these patterns relate to specific aspects of movement. Second, because motor cortex generates descending commands by integrating multiple sources of input from other brain regions, it is critical to determine how these inputs influence motor cortical dynamics along specific, behaviorally-relevant dimensions. Our long-term goal is to identify the dynamical principles governing the interactions across distributed neural populations, and to determine how these principles enable the adaptation of the locomotor pattern in a complex environment. The overall objective of this proposal is to determine how neural population dynamics in motor cortex are generated during skilled locomotion by identifying the impact of cerebellar and posterior parietal inputs on specific motor cortical dimensions. Our central hypothesis is that the cerebellum selectively drives step-entrained dimensions of motor cortical population activity that are synchronized with the rhythm of lower motor centers, while the posterior parietal cortex selectively drives motor commands for gait modification in obstacle-modulated dimensions. To directly test this hypothesis, we will first record from motor cortical ensembles in unrestrained mice performing skilled locomotion and use computational techniques to isolate step-entrained and obstacle-modulated dimensions of neural population activity (Aim 1). Next, we will use optogenetic perturbations to identify the effect of disrupting inputs from the cerebellum (Aim 2) and posterior parietal cortex (Aim 3) on activity in these dimensions. The proposed research is significant because the identification of how inputs to motor cortex generate its dynamics in healthy animals is expected to provide a foundation for future studies of how these dynamics degrade in neurodegenerative disease and aging, and to support the improvement of closed-loop deep brain stimulation strategies for movement disorders. The proposed research is innovative because it integrates the dynamical systems framework for the analysis and interpretation of data with the optogenetic toolkit for neural circuit perturbations, enabling a transition beyond the measurement of cortical population trajectories toward a definition of the underlying dynamical principles that generate them.