Interfacing With Alpha Motor Neurons in Spinal Cord Injury Patients Receiving Trans-spinal Electrical Stimulation

Abstract

Trans-spinal direct current stimulation (tsDCS) provides a non-invasive, clinically viable approach to potentially restore physiological neuromuscular function after neurological impairment, e.g., spinal cord injury (SCI). Use of tsDCS has been hampered by the inability of delivering stimulation patterns based on the activity of neural targets responsible to motor function, i.e., α-motor neurons (α-MNs). State of the art modeling and experimental techniques do not provide information about how individual α-MNs respond to electrical fields. This is a major element hindering the development of neuro-modulative technologies highly tailored to an individual patient. For the first time, we propose the use of a signal-based approach to infer tsDCS effects on large α-MNs pools in four incomplete SCI individuals. We employ leg muscles spatial sampling and deconvolution of high-density fiber electrical activity to decode accurate α-MNs discharges across multiple lumbosacral segments during isometric plantar flexion sub-maximal contractions. This is done before, immediately after and 30 min after sub-threshold cathodal stimulation. We deliver sham tsDCS as a control measure. First, we propose a new algorithm for removing compromised information from decomposed α-MNs spike trains, thereby enabling robust decomposition and frequency-domain analysis. Second, we propose the analysis of α-MNs spike trains coherence (i.e., frequency-domain) as an indicator of spinal response to tsDCS. Results showed that α-MNs spike trains coherence analysis sensibly varied across stimulation phases. Coherence analyses results suggested that the common synaptic input to α-MNs pools decreased immediately after cathodal tsDCS with a persistent effect after 30 min. Our proposed non-invasive decoding of individual α-MNs behavior may open up new avenues for the design of real-time closed-loop control applications including both transcutaneous and epidural spinal electrical stimulation where stimulation parameters are adjusted on-the-fly.

Closing the loop between wearable technology and human biology: A new paradigm for steering neuromuscular form and function

“…This information could be directly used in closed-loop controllers (Figs 1 and 4) to modify external electromechanical stimuli to the human body and shape remodelling in both nervous and muscular tissues to ultimately provide a neuro-mechanical benefit for the user, i.e. reduction in tissues peak loads to prevent tearing, preservation of tissue tension to prevent atrophy, reduction of muscle spasticity in patients to enhance voluntary limb control during rehabilitation [23], [107], [108]. with and adapt to human limbs soft tissues, thereby always assuring electrode-to-skin contact [119].…”

“…We propose to employ HD-EMG-based techniques (Section 2.1) to determine changes in motor neuron behavior and how these reflect spinal circuit organization [18], [23]. In a first instance, this information can be inferred by applying dimensionality reduction techniques to alpha motor neuron spike trains in the time-domain (i.e., NMF) [103].…”

“…Alternatively, spinal circuitries organization can be inferred by applying frequency-domain analysis to HD-EMG-decomposed motor neuron spike trains [23]. In this context, we propose to use inter-spike coherence analysis to infer how synaptic input from spinal and supraspinal centers is projected onto alpha motor neuron pools [23], [104]. In this context, common and independent synaptic input can be inferred via coherence analysis, which is a measure of linear correlation (i.e., commonality) in frequency domain.…”

Effective Stimulation Type and Waveform for Force Control of the Motor Unit System: Implications for Intraspinal Microstimulation

“…In addition, the multielectrode array interface developed for spinal cord stimulation ( Meacham et al, 2011 ) and nerve cuff and flexible split ring electrode developed for selective stimulation of the motor nerve ( Deurloo et al, 2003 ; Lee et al, 2017 ) could also be employed to test the stimulation waveforms required for force control predicted at the motor unit level in the present study. It should be noted that further analysis is needed for the indirect control of spinal motoneurons through current stimulation via the skin on the back ( Gogeascoechea et al, 2020 ) or the epidural portion ( Ahmed, 2016 ) of the spinal cord, which typically involves a variety of interneurons and afferents.…”

“…Finally, further investigation is required in terms of the stimulation waveforms to control the force production with the whole muscle, considering the organization of spinal motoneurons exhibiting different anatomical and electrical properties ( Zengel et al, 1985 ; Capogrosso et al, 2013 ). In addition, the influence of spinal interneurons and peripheral afferents should be considered, particularly in the case of skin or epidural stimulation of the spinal cord ( Harkema et al, 2011 ; Takei and Seki, 2013 ; Gogeascoechea et al, 2020 ).…”