Search bioRxiv⌕ Search

Biology subjects

Chardon, M. K.

Publications and source records attributed to Chardon, M. K..

2 recordsLinked to original sources

A NEW POSTURAL MOTOR RESPONSE TO SPINAL CORD STIMULATION: POST-STIMULATION REBOUND EXTENSION

Spinal cord stimulation (SCS) has emerged as a therapeutic tool for improving motor function following spinal cord injury. While many studies focus on restoring locomotion, little attention is paid to enabling standing which is a prerequisite of walking. In this study, we fully characterize a new type of response to SCS, a long extension activated post-stimulation (LEAP). LEAP is primarily directed to ankle extensors and hence has great clinical potential to assist postural movements. To characterize this new response, we used the decerebrate cat model to avoid the suppressive effects of anesthesia, and combined EMG and force measurement in the hindlimb with intracellular recordings in the lumbar spinal cord. Stimulation was delivered as five-second trains via bipolar electrodes placed on the cord surface, and multiple combinations of stimulation locations (L4 to S2), amplitudes (50-600 uA), and frequencies (10-40 Hz) were tested. While the optimum stimulation location and frequency differed slightly among animals, the stimulation amplitude was key for controlling LEAP duration and amplitude. To study the mechanism of LEAP, we performed in vivo intracellular recordings of motoneurons. In 70% of motoneurons, LEAP increased at hyperpolarized membrane potentials indicating a synaptic origin. Furthermore, spinal interneurons exhibited changes in firing during LEAP, confirming the circuit origin of this behavior. Finally, to identify the type of afferents involved in generating LEAP, we used shorter stimulation pulses (more selective for proprioceptive afferents), as well as peripheral stimulation of the sural nerve (cutaneous afferents). The data indicates that LEAP primarily relies on proprioceptive afferents and has major differences from pain or withdrawal reflexes mediated by cutaneous afferents. Our study has thus identified and characterized a novel postural motor response to SCS which has the potential to expand the applications of SCS for patients with motor disorders.

neuroscience↗

Supercomputers and Reverse Engineering of Motoneuron Firing Patterns

In this study, we develop new reverse engineering (RE) techniques to identify the organization of the synaptic inputs generating firing patterns of populations of neurons. We tested these techniques in silico to allow rigorous evaluation of their effectiveness, using remarkably extensive parameter searches enabled by massively-parallel computation on supercomputers. We chose spinal motoneurons as our target neural system, since motoneurons process all motor commands and have well established input-output properties. One set of simulated motoneurons was driven by 300,000+ simulated combinations of excitatory, inhibitory, and neuromodulatory inputs. Our goal was to determine if these firing patterns had sufficient information to allow RE identification of the input combinations. Like other neural systems, the motoneuron input-output system is likely non-unique. This non-uniqueness could potentially limit this RE approach, as many input combinations can produce similar outputs. However, our simulations revealed that firing patterns contained sufficient information to sharply restrict the solution space. Thus, our RE approach successfully generated estimates of the actual simulated patterns of excitation, inhibition, and neuromodulation, with variances accounted for ranging from 75% to 90%. It was striking that nonlinearities induced in firing patterns by the neuromodulation inputs did not impede RE, but instead generated distinctive features in firing patterns that aided RE. These simulations demonstrate the potential of this form of RE analysis. It is likely that the ever-increasing capacity of supercomputers will allow increasingly accurate RE of neuron inputs from their firing patterns from many neural systems.

neuroscience↗