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.

Neuro-fuzzy decoding of sensory information from ensembles of simultaneously recorded dorsal root ganglion neurons for functional electrical stimulation applications.

Functional electrical stimulation (FES) is used to improve motor function after injury to the central nervous system. Some FES systems use artificial sensors to switch between finite control states. To optimize FES control of the complex behavior of the musculo-skeletal system in activities of daily life, it is highly desirable to implement feedback control. In theory, sensory neural signals could provide the required control signals. Recent studies have demonstrated the feasibility of deriving limb-state estimates from the firing rates of primary afferent neurons recorded in dorsal root ganglia (DRG). These studies used multiple linear regression (MLR) methods to generate estimates of limb position and velocity based on a weighted sum of firing rates in an ensemble of simultaneously recorded DRG neurons. The aim of this study was to test whether the use of a neuro-fuzzy (NF) algorithm (the generalized dynamic fuzzy neural networks (GD-FNN)) could improve the performance, robustness and ability to generalize from training to test sets compared to the MLR technique. NF and MLR decoding methods were applied to ensemble DRG recordings obtained during passive and active limb movements in anesthetized and freely moving cats. The GD-FNN model provided more accurate estimates of limb state and generalized better to novel movement patterns. Future efforts will focus on implementing these neural recording and decoding methods in real time to provide closed-loop control of FES using the information extracted from sensory neurons.

Activities on PNS neural interfaces for the control of hand prostheses.

The development of interfaces linking the human nervous system with artificial devices is an important area of research. Several groups are working on the development of devices able to restore sensory-motor function in subjects affected by neurological disorders, injuries or amputations. Neural electrodes implanted in peripheral nervous system, and in particular intrafascicular electrodes, seem to be a promising approach for the control of hand prosthesis thanks to the possibility to selectively access motor and sensory fibers for decoding motor commands and delivering sensory feedback. In this paper, activities on the use of PNS interfaces for the control of hand prosthesis are presented. In particular, the design and feasibility study of a self-opening neural interface is presented together with the decoding of ENG signals in one amputee to control a dexterous hand prosthesis.

On the control of a robot hand by extracting neural signals from the PNS: preliminary results from a human implantation.

The development of hybrid neuroprosthetic systems (HBSs) linking the human nervous system with artificial devices is an important area of research that is currently addressed by several groups to restore sensorimotor function in people affected by different disabilities. It is particularly important to establish a fast, intuitive, bidirectional flow of information between the nervous system of the user and the smart robotic device. Among the possible solutions to achieve this goal, interfaces with the peripheral nervous system and in particular intraneural electrodes can represent an interesting choice. In the present study, thin-film longitudinal intra-fascicular electrodes were implanted in the median and ulnar nerves of an amputee. The possibility of restoring the bidirectional link between the subject and the external world was investigated during a 4 week trial. The result showed that both the extraction of motor information and the restoration of sensory function are possible.