Spatiotemporal neuromodulation therapies engaging muscle synergies improve motor control after spinal cord injury

Electrical neuromodulation of lumbar segments improves motor control after spinal cord injury in animal models and humans. However, the physiological principles underlying the effect of this intervention remain poorly understood, which has limited the therapeutic approach to continuous stimulation applied to restricted spinal cord locations. Here we developed stimulation protocols that reproduce the natural dynamics of motoneuron activation during locomotion. For this, we computed the spatiotemporal activation pattern of muscle synergies during locomotion in healthy rats. Computer simulations identified optimal electrode locations to target each synergy through the recruitment of proprioceptive feedback circuits. This framework steered the design of spatially selective spinal implants and real-time control software that modulate extensor and flexor synergies with precise temporal resolution. Spatiotemporal neuromodulation therapies improved gait quality, weight-bearing capacity, endurance and skilled locomotion in several rodent models of spinal cord injury. These new concepts are directly translatable to strategies to improve motor control in humans.

Personalizable computational models of electrical spinal cord stimulation to restore function after neurological disorders

Andreas Rowald

Spinal Cord Injury (SCI) disrupts the communication between the brain and spinal circuits below the lesion, leading to a plethora of neurological impairments, including the loss of motor function. At present, the only medical practices to enhance recovery after paralysis are activity-based therapies. In severe cases, SCI-patients fail to produce active movements voluntarily and are therefore unable to fully benefit from these therapies. Epidural Electrical Stimulation (EES) applied over the lumbosacral spinal cord has demonstrated to enable locomotion in preclinical animal models and humans with SCI. EES may therefore play a pivotal role in the recovery of locomotion after SCI.However, neither has EES reached the same level of efficacy in humans as in preclinical animal models, nor is there consensus on the definition of clinically meaningful stimulation protocols. In the absence of clear understanding on how EES promotes the formation of motor patterns, stimulation protocols have been largely based on empirical observations. Instead, hypothesis-driven definition of stimulation parameters has demonstrated superior efficacy in other neuromodulation therapies, such as deep brain stimulation.In this thesis, I outline a computational approach to inform EES strategies for the recovery of neurological function after SCI. For this purpose, I leveraged a combination of finite element methods, neurophysical and neuromusculoskeletal models to refine our understanding on how EES promotes locomotion after SCI, inform the design of neuromodulation technologies and develop personalized EES treatments in humans with SCI.In the first part of this thesis, I provide evidence that EES recruits proprioceptive and cutaneous afferents in the dorsal roots. I suggest that the recruitment of proprioceptive feedback circuits promotes the formation of motor patterns. In contrary, the continuous recruitment of cutaneous afferents may disrupt the production of locomotion. In the next chapter, I study interspecies difference of EES. I argue that these differences necessitate the adaption of stimulation protocols to enable translation of EES as a therapy from preclinical models to humans. I propose the application of spatiotemporal protocols with low-amplitude, high-frequency bursts to improve the efficacy of EES in humans. In the following chapter, I describe a technological framework that enables the implementation of such stimulation paradigms in people with SCI. I outline how personalized computational modeling can be used for treatment planning. I then summarize how I advanced this rudimentary computational tool into a computational framework for the rapid elaboration of highly realistic personalizable computational models. I explain how I leveraged this framework to inform the arrangements of electrodes on a paddle lead to enable locomotion in large and diversified patient-cohorts, perform preoperative treatment planning and validate the efficacy of both the lead and treatment planning protocol in individuals with severe, chronic SCI. Finally, I summarize how I translated my computational framework for other use-cases including the control of hemodynamics and the evaluation of an optoelectronic system to enable locomotion in preclinical models.

EPFL2021

Spatiotemporal stimulation strategies in neuroprostheses to improve locomotion after spinal cord injury

Jérôme Gandar

Spinal cord injury (SCI) disrupts communication within central nervous system and lead to range of neurological disorders including paralysis. Current rehabilitation strategies to restore locomotion are poorly effective in people with severe SCI. Epidural electrical stimulation (EES) showed promising results in animal models and humans to improve recovery. However, EES protocols have remained empirical, which has limited the efficacy of this paradigm. In this thesis, I report my contribution to the development of EES related software and hardware that were driven by the under- standing of the mechanisms underlying EES. These neurotechnologies showed a remarkable efficacy to reestablish locomotion in animal models of leg paralysis. EES protocols have primarily been delivered with continuous stimulations applied over the middle of the spinal cord, independently of current limb positions. However the natural activity of the spinal cord does not correspond to this limited monotone modulation. In the first part of this thesis, we developed spatiotemporal stimulation protocols that seek to reproduce the natural activity of the spinal cord during walking. Using computational models, we identified optimal electrode locations that target individual posterior roots. These simulations steered the design of spatially selective spinal implants. Control software triggered stimulation trains in real-time to engage extensor and flexor synergies according to limb positions. This spatiotemporal neuro- modulation therapy enhanced locomotor performances in rats with severe SCI. However, these spatiotemporal neuromodulation protocols were controlled via an external computer. The animal had no control over the occurrence of the stimulation. To remedy this limitation, we designed a brain-spine interface. We linked motor states decoded from leg motor cortex activity to spinal cord stimulation protocols to elicited the intended movements. We implemented this brain-spine interface in a nonhuman primate models of transient unilateral leg paralysis. All the animals immediately regained movements of the paralyzed leg. There is often a mechanical mismatch between current stiff implants and the soft neural tissues of the host. The third part of this thesis is dedicated to the design and fabrication of soft neural implants that present the same elasticity as the dura mater. These implants maintain the ability to deliver electrochemical stimulation while being stretched. Such interfaces can be applied to multiple neuroprosthetic applications, including the restoration of locomotion in paralyzed rats. In the last part of this thesis, I addressed the current limitations of spinal implant specificity. We found that EES activates the large afferent fibers within the dorsal rots and developed novel implants that take advantage of the known trajectories of the dorsal roots to increase the specificity of EES. First, we built a precise anatomical computational model of the lumbosacral roots. We then ran simulations that identi- fied multipolar electrode configurations capable of steering the current specifcally. These results drove the fabrication of soft neural implants that we inserted chronically in rat models of severe SCI. Experiments showed that multipolar EES increases the specificity of the stimulation compared to conventional protocols. All the concepts developed and validated in my thesis are already applied or are steering applications in humans with SCI.

EPFL2019

Personalizable computational models of electrical spinal cord stimulation to restore function after neurological disorders

Andreas Rowald

EPFL2021

Spatiotemporal stimulation strategies in neuroprostheses to improve locomotion after spinal cord injury

Jérôme Gandar

EPFL2019