Bayesian optimization of peripheral intraneural stimulation protocols to evoke distal limb movements.

Objective.Motor neuroprostheses require the identification of stimulation protocols that effectively produce desired movements. Manual search for these protocols can be very time-consuming and often leads to suboptimal solutions, as several stimulation parameters must be personalized for each subject for a variety of target motor functions. Here, we present an algorithm that efficiently tunes peripheral intraneural stimulation protocols to elicit functionally relevant distal limb movements.Approach.We developed the algorithm using Bayesian optimization (BO) with multi-output Gaussian Processes (GPs) and defined objective functions based on coordinated muscle recruitment. We applied the algorithm offline to data acquired in rats for walking control and in monkeys for hand grasping control and compared different GP models for these two systems. We then performed a preliminary online test in a monkey to experimentally validate the functionality of our method.Main results.Offline, optimal intraneural stimulation protocols for various target motor functions were rapidly identified in both experimental scenarios. Using the model that performed best, the algorithm converged to stimuli that evoked functionally consistent movements with an average number of actions equal to 20% of the search space size in both the rat and monkey animal models. Online, the algorithm quickly guided the observations to stimuli that elicited functional hand gestures, although more selective motor outputs could have been achieved by refining the objective function used.Significance.These results demonstrate that BO can reliably and efficiently automate the tuning of peripheral neurostimulation protocols, establishing a translational framework to configure peripheral motor neuroprostheses in clinical applications. The proposed method can also potentially be applied to optimize motor functions using other stimulation modalities.

Neglected physical human-robot interaction may explain variable outcomes in gait neurorehabilitation research.

During gait neurorehabilitation, many factors influence the quality of gait patterns, particularly the chosen body-weight support (BWS) device. Consequently, robotic BWS devices play a key role in gait rehabilitation of people with neurological disorders. The device transparency, support force vector direction, and attachment to the harness vary widely across existing robotic BWS devices, but the influence of these factors on the production of gait remains unknown. Because this information is key to designing an optimal BWS, we systematically studied these determinants in this work. We report that with a highly transparent device and a conventional harness, healthy participants select a small backward force when asked for optimal BWS conditions. This unexpected finding challenges the view that during human-robot interactions, humans predominantly optimize energy efficiency. Instead, they might seek to increase their feeling of stability and safety. We also demonstrate that the location of the attachment points on the harness strongly affects gait patterns, yet harness attachment is hardly reported in literature. Our results establish principles for the design of BWS devices and personalization of BWS settings for gait neurorehabilitation.

Long-term usability and bio-integration of polyimide-based intra-neural stimulating electrodes.

Stimulation of peripheral nerves has transiently restored lost sensation and has the potential to alleviate motor deficits. However, incomplete characterization of the long-term usability and bio-integration of intra-neural implants has restricted their use for clinical applications. Here, we conducted a longitudinal assessment of the selectivity, stability, functionality, and biocompatibility of polyimide-based intra-neural implants that were inserted in the sciatic nerve of twenty-three healthy adult rats for up to six months. We found that the stimulation threshold and impedance of the electrodes increased moderately during the first four weeks after implantation, and then remained stable over the following five months. The time course of these adaptations correlated with the progressive development of a fibrotic capsule around the implants. The selectivity of the electrodes enabled the preferential recruitment of extensor and flexor muscles of the ankle. Despite the foreign body reaction, this selectivity remained stable over time. These functional properties supported the development of control algorithms that modulated the forces produced by ankle extensor and flexor muscles with high precision. The comprehensive characterization of the implant encapsulation revealed hyper-cellularity, increased microvascular density, Wallerian degeneration, and infiltration of macrophages within the endoneurial space early after implantation. Over time, the amount of macrophages markedly decreased, and a layer of multinucleated giant cells surrounded by a capsule of fibrotic tissue developed around the implant, causing an enlargement of the diameter of the nerve. However, the density of nerve fibers above and below the inserted implant remained unaffected. Upon removal of the implant, we did not detect alteration of skilled leg movements and only observed mild tissue reaction. Our study characterized the interplay between the development of foreign body responses and changes in the electrical properties of actively used intra-neural electrodes, highlighting functional stability of polyimide-based implants over more than six months. These results are essential for refining and validating these implants and open a realistic pathway for long-term clinical applications in humans.

Decoding bipedal locomotion from the rat sensorimotor cortex.

OBJECTIVE: Decoding forelimb movements from the firing activity of cortical neurons has been interfaced with robotic and prosthetic systems to replace lost upper limb functions in humans. Despite the potential of this approach to improve locomotion and facilitate gait rehabilitation, decoding lower limb movement from the motor cortex has received comparatively little attention. Here, we performed experiments to identify the type and amount of information that can be decoded from neuronal ensemble activity in the hindlimb area of the rat motor cortex during bipedal locomotor tasks. APPROACH: Rats were trained to stand, step on a treadmill, walk overground and climb staircases in a bipedal posture. To impose this gait, the rats were secured in a robotic interface that provided support against the direction of gravity and in the mediolateral direction, but behaved transparently in the forward direction. After completion of training, rats were chronically implanted with a micro-wire array spanning the left hindlimb motor cortex to record single and multi-unit activity, and bipolar electrodes into 10 muscles of the right hindlimb to monitor electromyographic signals. Whole-body kinematics, muscle activity, and neural signals were simultaneously recorded during execution of the trained tasks over multiple days of testing. Hindlimb kinematics, muscle activity, gait phases, and locomotor tasks were decoded using offline classification algorithms. MAIN RESULTS: We found that the stance and swing phases of gait and the locomotor tasks were detected with accuracies as robust as 90% in all rats. Decoded hindlimb kinematics and muscle activity exhibited a larger variability across rats and tasks. SIGNIFICANCE: Our study shows that the rodent motor cortex contains useful information for lower limb neuroprosthetic development. However, brain-machine interfaces estimating gait phases or locomotor behaviors, instead of continuous variables such as limb joint positions or speeds, are likely to provide more robust control strategies for the design of such neuroprostheses.

[Neuronal control of posture and locomotion in decerebrated and spinalized animals].

We have found that the brainstem-spinal cord circuitry of decerebrated cats actively maintain the equilibrium during standing, walking and imposed mechanical perturbations similar to that observed in intact animals. The corrective hindlimb motor responses during standing included redistribution of the extensor activity ipsilateral and contralateral to perturbation. The postural corrections in walking cats were due to considerable modification of EMG pattern in the limbs as well as changing of the swing-stance phases of the step cycle and ground reaction forces depending of perturbation side. Thus the basic mechanisms for balance control of decerebrated animals in these two forms of motor behavior are different. Balance-related adjustments relied entirely on the integration of somatosensory information arising from the moving hindquarters because of the suppression of vestibular, visual, and head-neck-trunk sensory input. We propose that the somatosensory input from the hindquarters in concert with the lumbosacral spinal circuitry can control the dynamics of the hindquarters sufficient to sustain balance. We found that, after isolation from the brainstem or forebrain, lumbosacral circuits receiving tonic epidural electrical stimulation can effectively control equilibrium during standing and stepping. Detailed analyses of the relationships among muscle activity, trunk kinematics, and limb kinetics indicate that spinal motor systems utilize a combination of feedback and feedforward strategies to maintain dynamic equilibrium during walking. The unexpected ability of spinal circuitries to exert efficient postural control in the presence of epidural electrical stimulation in decerebrated and spinal cats have significant implications for the potential of humans with a severe spinal cord injury to regain a significant level of functional standing and walking capacities.

Plasticity of functional connectivity in the adult spinal cord.

This paper emphasizes several characteristics of the neural control of locomotion that provide opportunities for developing strategies to maximize the recovery of postural and locomotor functions after a spinal cord injury (SCI). The major points of this paper are: (i) the circuitry that controls standing and stepping is extremely malleable and reflects a continuously varying combination of neurons that are activated when executing stereotypical movements; (ii) the connectivity between neurons is more accurately perceived as a functional rather than as an anatomical phenomenon; (iii) the functional connectivity that controls standing and stepping reflects the physiological state of a given assembly of synapses, where the probability of these synaptic events is not deterministic; (iv) rather, this probability can be modulated by other factors such as pharmacological agents, epidural stimulation and/or motor training; (v) the variability observed in the kinematics of consecutive steps reflects a fundamental feature of the neural control system and (vi) machine-learning theories elucidate the need to accommodate variability in developing strategies designed to enhance motor performance by motor training using robotic devices after an SCI.

Continuous, bilateral Achilles' tendon vibration is not detrimental to human walk.

Sensory feedback from the moving limbs contributes to the regulation of animal and human locomotion. However, the question of the specific role of the various modalities is still open. Further, functional loss of leg afferent fibres due to peripheral neuropathy does not always lead to major alteration in the gait pattern. In order to gain further insight on proprioceptive control of human gait, we applied vibratory tendon stimulation, known to recruit spindle primary afferent fibres, to both triceps surae muscles during normal floor walk. This procedure would disturb organisation and execution of walking, especially if spindles fire continuously and subjects are blindfolded. Vibration induced significant, though minor, changes in duration and length of stance and swing phase, and on speed of walking and kinematics of lower limb segments. No effect was induced on angular displacement of the ankle joint or trunk and head kinematics. This paucity of effects was at variance with the perception of the subjects, who reported illusion of leg stiffness and gait imbalance. These findings would speak for a selective gating of Ia input during locomotion and emphasise the notion that the central nervous system can cope with an unusual continuous input along the Ia fibres from a key muscle like the soleus.

[Vibration after effect during human walking]. / Rémanence de l'effet vibratoire durant la marche humaine.

Muscular vibration effects could usually persist after the end of the stimulation. The extinction of this after-effect was studied during human walk. Six subjects performed a locomotor task (six successive steps) under control, and after bilateral Achilles' tendon vibration (70 Hz). The step frequency was enhanced (diminution of the stance phase duration) whereas the stride length tended to decrease. The relative duration of the stance phase reached back normal values with repetitions. These results demonstrated that vibration-induced effects persevere after the end of the stimulation. In addition, owing to the dynamic of the re-adaptation process, they suggested that the muscular proprioceptive input could participate in both maintaining and regulating the locomotor rhythm.