Recording Spinal Neural Activity Across Genetic Classes During Hindlimb Motor Behaviors - Project Summary/Abstract: The spinal cord is comprised of many genetically and functionally heterogenous cell types that are both interconnected and intermingled to form complex circuits for computing limb movements. From a computational perspective, motor control represents an enormous challenge because even the simplest motor actions require precise coordination of muscle contraction timing and force across joints that have multiple degrees of freedom. The goal of this grant is to characterize the firing patterns of spinal neurons during motor behaviors while characterizing their spatial relationships, functional-connectivity, and genetic profile in order to better understand how the spinal cord processes motor commands for meaningful limb movements. The experiments in this grant are based on a technical breakthrough in which highly-flexible nano-electronic thread (NET) probes with 32, 64x2, and 128 recording sites have been optimized for monitoring neuronal activity in the spinal cord of awake behaving mice. This grant is a multi-PI collaboration that builds on the strengths of three laboratories with expertise in engineering, physiology, and neurogenetics that have a record of productive collaboration. Models of spinal motor circuitry often conceptualize the system as modules, with components dedicated for rhythmicity (central pattern generation, CPG), pattern, and/or extensor-flexor regulation. Preliminary studies have uncovered evidence that individual spinal neurons participate in controlling multiple distinct motor actions. Moreover across different motor behaviors the functional-connectivity between the same active neurons changes. These observations have led us to hypothesize that the spinal neural network operates as a multi- functional system using overlapping neuronal sets to generate different motor commands. Thus, motor information appears to be encoded by the relative pattern of neuronal activity in the ensemble rather than dedicated separate circuits for each muscle. Defining how spinal circuits compute limb movements has remained challenging because the relationship between the activity, connectivity, and genetics of locomotor neurons remains very fragmentary. To address this Aim 1 will record and map lumbar spinal neuron activity and position during a range of hindlimb movements to determine if (1) neurons display multi-functional properties across behaviors, and (2) determine whether there are focal or diffuse spatial distributions of cells linked to specific features of motor control. Aim 2 will use innovative multi-shank electrodes to record spinal interneurons and motor neurons and define the dynamical functional-connectivity relationships within the network during different behaviors. Aim 3 will use mouse genetics to record genetically-defined spinal interneurons (Satb2+ MSE neurons; En1+ V1 neurons; and Chx10+ V2a neurons) identified using optotagging, in order to examine the heterogeneity within each class and define whether there are common properties shared by genetically-related cells. These studies will expand current understanding of how spinal circuits transform descending and sensory inputs into ethological motor behaviors.
