Epidural stimulation restores muscle synergies by modulating neural drives in participants with sensorimotor complete spinal cord injuries.

Multiple studies have corroborated the restoration of volitional motor control after motor-complete spinal cord injury (SCI) through the use of epidural spinal cord stimulation (eSCS), but rigorous quantitative descriptions of muscle coordination have been lacking. Six participants with chronic, motor and sensory complete SCI underwent a brain motor control assessment (BMCA) consisting of a set of structured motor tasks with and without eSCS. We investigated how muscle activity complexity and muscle synergies changed with and without stimulation. We performed this analysis to better characterize the impact of stimulation on neuromuscular control. We also recorded data from nine healthy participants as controls. Competition exists between the task origin and neural origin hypotheses underlying muscle synergies. The ability to restore motor control with eSCS in participants with motor and sensory complete SCI allows us to test whether changes in muscle synergies reflect a neural basis in the same task. Muscle activity complexity was computed with Higuchi Fractal Dimensional (HFD) analysis, and muscle synergies were estimated using non-negative matrix factorization (NNMF) in six participants with American Spinal Injury Association (ASIA) Impairment Score (AIS) A. We found that the complexity of muscle activity was immediately reduced by eSCS in the SCI participants. We also found that over the follow-up sessions, the muscle synergy structure of the SCI participants became more defined, and the number of synergies decreased over time, indicating improved coordination between muscle groups. Lastly, we found that the muscle synergies were restored with eSCS, supporting the neural hypothesis of muscle synergies. We conclude that eSCS restores muscle movements and muscle synergies that are distinct from those of healthy, able-bodied controls.

Optimization of Spinal Cord Stimulation Using Bayesian Preference Learning and Its Validation.

Epidural spinal cord stimulation has been reported to partially restore volitional movement and autonomic functions after motor and sensory-complete spinal cord injury (SCI). Modern spinal cord stimulation platforms offer significant flexibility in spatial and temporal parameters of stimulation delivered. Heterogeneity in SCI and injury-related symptoms necessitate stimulation personalization to maximally restore functions. However, the large multi-dimensional stimulation space makes exhaustive tests impossible. In this paper, we present a Bayesian optimization strategy for identifying personalized optimal stimulation patterns based on the participant's expressed preference for stimulation settings. We present companion validation protocols for investigating the credibility of learned preference models. The results obtained for five participants in the E-STAND spinal cord stimulation clinical trial are reported. Personalized preference models produced by the proposed learning and optimization algorithm show that there is more similarity in optimal frequency than in pulse width across participants. Across five participants, the average model prediction accuracy is 71.5% in internal cross-validation and 65.6% in prospective validation. Statistical tests of both validation studies show that the ability of the preference models to correctly predict unseen preference data is significantly greater than chance. The personalized preference models are also shown to be significantly correlated with motor task performance across participants. We show that several aspects in participants' quality of life has been improved over the course of the trial. Overall, the results indicate that the Bayesian preference optimization algorithm could assist clinicians in the systematic programming of individualized therapeutic stimulation settings and improve the therapeutic outcomes.

Long-Term Spinal Cord Stimulation After Chronic Complete Spinal Cord Injury Enables Volitional Movement in the Absence of Stimulation.

Background: Chronic spinal cord injury (SCI) portends a low probability of recovery, especially in the most severe subset of motor-complete injuries. Active spinal cord stimulation with or without intensive locomotor training has been reported to restore movement after traumatic SCI. Only three cases have been reported where participants developed restored volitional movement with active stimulation turned off after a period of chronic stimulation and only after intensive rehabilitation with locomotor training. It is unknown whether restoration of movement without stimulation is possible after stimulation alone. Objective: We describe the development of spontaneous volitional movement (SVM) without active stimulation in a subset of participants in the Epidural Stimulation After Neurologic Damage (ESTAND) trial, in which locomotor training is not prescribed as part of the study protocol, and subject's rehabilitation therapies are not modified. Methods: Volitional movement was evaluated with the Brain Motor Control Assessment using sEMG recordings and visual examination at baseline and at follow-up visits with and without stimulation. Additional functional assessment with a motor-assisted bicycle exercise at follow-up with and without stimulation identified generated work with and without effort. Results: The first seven participants had ASIA Impairment Scale (AIS) A or B thoracic SCI, a mean age of 42 years, and 7.7 years post-injury on average. Four patients developed evidence of sustained volitional movement, even in the absence of active stimulation after undergoing chronic epidural spinal cord stimulation (eSCS). Significant increases in volitional power were found between those observed to spontaneously move without stimulation and those unable (p < 0.0005). The likelihood of recovery of spontaneous volitional control was correlated with spasticity scores prior to the start of eSCS therapy (p = 0.048). Volitional power progressively improved over time (p = 0.016). Additionally, cycling was possible without stimulation (p < 0.005). Conclusion: While some SVM after eSCS has been reported in the literature, this study demonstrates sustained restoration without active stimulation after long-term eSCS stimulation in chronic and complete SCI in a subset of participants. This finding supports previous studies suggesting that "complete" SCI is likely not as common as previously believed, if it exists at all in the absence of transection and that preserved pathways are substrates for eSCS-mediated recovery in clinically motor-complete SCI. Clinical Trial Registration: www.ClinicalTrials.gov, identifier NCT03026816.

Glial Fibrillary Acidic Protein (GFAP) Outperforms S100 Calcium-Binding Protein B (S100B) and Ubiquitin C-Terminal Hydrolase L1 (UCH-L1) as Predictor for Positive Computed Tomography of the Head in Trauma Subjects.

OBJECTIVE: Traumatic brain injuries (TBIs) are largely underdiagnosed and may have persistent refractory consequences. Current assessments for acute TBI are limited to physical examination and imaging. Biomarkers such as glial fibrillary acidic protein (GFAP), ubiquitin C-terminal hydrolase L1 (UCH-L1), and S100 calcium-binding protein B (S100B) have shown predictive value as indicators of TBI and potential screening tools. METHODS: In total, 37 controls and 118 unique trauma subjects who received a clinically ordered head computed tomography (CT) in the emergency department of a level 1 trauma center were evaluated. Blood samples collected at 0-8 hours (initial) and 12-32 hours (delayed) postinjury were analyzed for GFAP, UCH-L1, and S100B concentrations. These were then compared in CT-negative and CT-positive subjects. RESULTS: Median GFAP, UCH-L1, and S100B concentrations were greater in CT-positive subjects at both timepoints compared with CT-negative subjects. In addition, median UCH-L1 and S100B concentrations were lower at the delayed timepoint, whereas median GFAP concentrations were increased. As predictors of a positive CT of the head, GFAP outperformed UCH-L1 and S100B at both timepoints (initial: 0.89 sensitivity, 0.62 specificity; delayed: 0.94 sensitivity, 0.67 specificity). GFAP alone also outperformed all possible combinations of biomarkers. CONCLUSIONS: GFAP, UCH-L1, and S100B demonstrated utility for rapid prediction of a CT-positive TBI within 0-8 hours of injury. GFAP exhibited the greatest predictive power at 12-32 hours. Furthermore, these results suggest that GFAP alone has greater utility for predicting a positive CT of the head than UCH-L1, S100B, or any combination of the 3.