The overall goal of this collaborative project is to use state-of-art experimental studies of spinal neurons and neural circuits in combination with computational modeling to dissect the organization and operating mechanisms of the spinal locomotor CPG. The central issues addressed in this study include understanding the rhythm-generating mechanisms operating in the spinal cord as well as the organization of flexor-extensor interactions. We propose to (a) investigate recently identified spinal interneurons that are considered to belong to rhythm-generating circuits, (b) identify their connectivity pattern, an (c) determine the functional links between these neurons and other key components in the spinal locomotor CPG. The project brings together two female scientists with complementary expertise in experimental (Dr. Dougherty) and computational (Dr. Shevtsova) neuroscience. The project has the following three objectives: OBJECTIVE 1: Determine and investigate the cellular basis of rhythmic bursting in Shox2 neurons and their mutual interactions. Investigate potential differences between these neurons with flexor- vs. extensor-related activity. OBJECTIVE 2: Investigate inhibitory interactions between the flexor- and extensor-related rhythm-generating neurons and the role of genetically-identified V2b and V1 neurons in these interactions. OBJECTIVE 3: Investigate properties of neuronal and network organization leading to the frequency-dependent flexor-extensor asymmetry and study interactions between flexor-extensor and left-right coordinating networks The model will be progressively developed by continuous interaction with the experimental studies and will serve both as a testbed for working concepts on the organization of the rhythm generating circuits in the spinal cord and as a source of predictions for subsequent experimental validation. Intellectual Merit: This collaborative study will use state-of-art genetic, molecular and physiological methods in combination with computational modeling to address the most fundamental questions on the neuronal and network organization in the mammalian spinal circuits allowing them to generate rhythmic activity and perform flexor-extensor coordination at different speeds to control locomotion and other motor behaviors. The results of this study will provide valuable insights into general principles of CPG organization and CPG-based motor control. Broader Impacts of the Project: (a) Integrating research and education: The experimental approaches and computational models developed in this project will be included in the core Neuroengineering course for students of the multi-departmental Neuroengineering Program at Drexel and in the core Advanced Neuroscience course for medical students of the College of Medicine. The project will provide a platform for short-term rotation of graduate students allowing them to gain both experimental and computational modelling skills. 2 PhD students and one postdoc researcher will be supported by this project. (b) Underrepresented groups: Both PI (Dougherty) and Co-PI (Shevtsova) are female scientists. Dr. Dougherty is a young scientist at the beginning of her scientific carrier, and this project will help her to further develop her research at Drexel and establish her future career in science. Minority students will be encouraged by both PIs to do lab rotations under their supervision with the possibility to extend the rotation work to a thesis project. (c) Enhance infrastructure for research and education: Two laboratories with mostly non-overlapping technical expertise will collaborate during this project. This collaboration will allow for the combination of genetic, molecular, physiological, electrophysiological, and computational modeling approaches to study the locomotor neural circuits participating in locomotor rhythm generation. The simulation package NSM 3.0 and all models developed in this project will be made available to other research groups via a specially developed website at Drexel University. (d) Medical Impact: As demonstrated in rodents (Orsal et al. 2002; Tillakaratne et al. 2010) and cats (Rossignol and Frigon, 2011), activation of the spinal locomotor CPG leads to the restoration of locomotion after upper spinal cord injury. The proposed study will provide an important theoretical basis for the future development of new, effective methods for restoring locomotor function after spinal cord injury and various degenerative disorders affecting normal locomotion.

National Institute of Health (NIH)
National Institute of Neurological Disorders and Stroke (NINDS)
Research Project (R01)
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Special Emphasis Panel (ZRG1)
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Jakeman, Lyn B
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Drexel University
Anatomy/Cell Biology
Schools of Medicine
United States
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Zholudeva, Lyandysha V; Qiang, Liang; Marchenko, Vitaliy et al. (2018) The Neuroplastic and Therapeutic Potential of Spinal Interneurons in the Injured Spinal Cord. Trends Neurosci 41:625-639
Ausborn, Jessica; Snyder, Abigail C; Shevtsova, Natalia A et al. (2018) State-dependent rhythmogenesis and frequency control in a half-center locomotor CPG. J Neurophysiol 119:96-117
Danner, Simon M; Shevtsova, Natalia A; Frigon, Alain et al. (2017) Computational modeling of spinal circuits controlling limb coordination and gaits in quadrupeds. Elife 6:
Zholudeva, Lyandysha V; Karliner, Jordyn S; Dougherty, Kimberly J et al. (2017) Anatomical Recruitment of Spinal V2a Interneurons into Phrenic Motor Circuitry after High Cervical Spinal Cord Injury. J Neurotrauma 34:3058-3065
Shevtsova, Natalia A; Rybak, Ilya A (2016) Organization of flexor-extensor interactions in the mammalian spinal cord: insights from computational modelling. J Physiol 594:6117-6131
Danner, Simon M; Wilshin, Simon D; Shevtsova, Natalia A et al. (2016) Central control of interlimb coordination and speed-dependent gait expression in quadrupeds. J Physiol 594:6947-6967
Rybak, Ilya A; Dougherty, Kimberly J; Shevtsova, Natalia A (2015) Organization of the Mammalian Locomotor CPG: Review of Computational Model and Circuit Architectures Based on Genetically Identified Spinal Interneurons(1,2,3). eNeuro 2: