Novel Activity Detection Algorithm to Characterize Spontaneous Stepping During Multimodal Spinal Neuromodulation After Mid-Thoracic Spinal Cord Injury in Rats

Abstract

A mid-thoracic spinal cord injury (SCI) severely impairs activation of the lower limb sensorimotor spinal networks, leading to paralysis. Various neuromodulatory techniques including electrical and pharmacological activation of the spinal networks have been successful in restoring locomotor function after SCI. We hypothesized that the combination of self-training in a natural environment with epidural stimulation (ES), quipazine (Quip), and strychnine (Strych) would result in greater activity in a cage environment after paralysis compared to either intervention alone. To assess this, we developed a method measuring and characterizing the chronic EMG recordings from tibialis anterior (TA) and soleus (Sol) muscles while rats were freely moving in their home cages. We then assessed the relationship between the change in recorded activity over time and motor-evoked potentials (MEPs) in animals receiving treatments. We found that the combination of ES, Quip, and Strych (sqES) generated the greatest level of recovery followed by ES + Quip (qES) while ES + Strych (sES) and ES alone showed least improvement in recorded activity. Further, we observed an exponential relationship between late response (LR) component of the MEPs and spontaneously generated step-like activity. Our data demonstrate the feasibility and potential importance of quantitatively monitoring mechanistic factors linked to activity-dependence in response to combinatorial interventions compared to individual therapies after SCI.