and Abstract Interventions that increase plasticity and regeneration after spinal cord injury (SCI) are improving, but little is known about the neural systems that would be most effective to target such interventions. Sensory based rehabilitation suggests a strong link between cutaneous and proprioceptive sensory neuron activity and motor recovery. Previous experiments provide strong support for the intermediate zone (IZ) of the spinal cord (SC) as an important site mediating this recovery. However, few studies have assessed the role of specific IZ neurons in functional recovery. Key barriers to progress include lack of characterization of specific cell types within the IZ and a paucity of tools to visualize circuits and test their functions in motor performance and recovery following SCI. Our lab combines sophisticated mouse genetic approaches with sensitive motor movement tracking to understand how sensory information is encoded by the SC to influence behavior. Using this approach, we uncovered that intermediate zone (IZ) parvalbumin positive interneurons (PVs) are important for tactile motor responses and locomotion. We hypothesize that IZ-PVs process sensory information to activate specific muscle groups during locomotion and that they play a critical role in activity-based functional recovery following SCI. The ability to identify circuits important for functional recovery relies on how accurately we can quantify differences in behavioral outcomes. We are implementing an unsupervised approach using 3-D pose dynamics and artificial intelligence (AI) to characterize both sensitive behavioral biomarkers and uncover key spinal cord circuits important for the recovery process. Interventions that increase plasticity and regeneration are improving, and this project both identifies the neural systems and synaptic mechanisms that would be most effective to target such interventions and establishes an AI-based platform for fast, reliable and unbiased quantification of motor recovery in rodents. Thus, this project makes original and important contributions to the field of spinal cord research in ways that are specifically aligned with central missions of the NINDS. Moreover, our experimental scrutiny at both the neural and behavioral levels establishes a critical foundation for developing a leading research program and securing independent award funding studying the spinal cord circuits important for sensorimotor function and recovery following SCI. To this end, I have developed a thorough and pragmatic career development plan supported by a strong committee of mentors with extensive track records of laboratory and departmental level mentoring and distinguished portfolios of SCI-specific grant support from the NIH, DoD and private foundations. My career development activities will be focused on four aspects of my academic success. 1) Mentorship and guidance focused on laboratory management. 2) Development and growth of my independent research program and award funding, with a focus on SCI research gap-based training. 3) Navigating institutional responsibilities and fulfilling requirements for promotion and tenure. 4) Expanding my scientific network and profile.
Interventions that increase plasticity and regeneration after spinal cord injury (SCI) are improving, but little is known about the spinal cord neural systems that would be most effective to target such interventions. This project both identifies the spinal cord neural cell types and synaptic mechanisms that would be most effective to target such interventions and establishes an artificial intelligence (AI)-based platform for fast, reliable and unbiased quantification of motor recovery in rodents. Our experimental scrutiny at both the neural and behavioral levels establishes a critical foundation for developing a prominent research program and securing independent award funding studying the spinal cord circuits important for sensorimotor function and recovery following SCI.
