Printable microscale interfaces for long-term peripheral nerve mapping and precision control

The nascent field of bioelectronic medicine seeks to decode and modulate peripheral nervous system signals to obtain therapeutic control of targeted end organs and effectors. Current approaches rely heavily on electrode-based devices, but size scalability, material and microfabrication challenges, limited surgical accessibility, and the biomechanically dynamic implantation environment are significant impediments to developing and deploying advanced peripheral interfacing technologies. Here, we present a microscale implantable device – the nanoclip – for chronic interfacing with fine peripheral nerves in small animal models that begins to meet these constraints. We demonstrate the capability to make stable, high-resolution recordings of behaviorally-linked nerve activity over multi-week timescales. In addition, we show that multi-channel, current-steering-based stimulation can achieve a high degree of functionally-relevant modulatory specificity within the small scale of the device. These results highlight the potential of new microscale design and fabrication techniques for the realization of viable implantable devices for long-term peripheral interfacing.https://www.biorxiv.org/node/801468.fullFirst author draf

Doctor of Philosophy

dissertationHands are so central to the human experience, yet we often take for granted the capacity to maneuver objects, to form a gesture, or to caress a loved-one’s hand. The effects of hand amputation can be severe, including functional disabilities, chronic phantom pain, and a profound sense of loss which can lead to depression and anxiety. In previous studies, peripheral-nerve interfaces, such as the Utah Slanted Electrode Array (USEA), have shown potential for restoring a sense of touch and prosthesis movement control. This dissertation represents a substantial step forward in the use of the USEAs for clinical careâ€"ultimately providing human amputees with widespread hand sensation that is functionally useful and psychologically meaningful. In completion of this ultimate objective, we report on three major advances. First, we performed the first dual-USEA implantations in human amputees; placing one USEA in the residual median nerve and another USEA in the residual ulnar nerve. Chapter 2 of this dissertation shows that USEAs provided full-hand sensory coverage, and that movement of the implant site to the upper arm in the second subject, proximal to nerve branch-points to extrinsic hand muscles, enabled activation of both proprioceptive sensory percepts and cutaneous percepts. Second, in Chapter 3, we report on successful use of USEA-evoked sensory percepts for functional discrimination tasks. We provide a comprehensive report of functional discrimination among USEA-evoked sensory percepts from three human subjects, including discrimination among multiple proprioceptive or cutaneous sensory percepts with different hand locations, sensory qualities, and/or intensities. Finally, in Chapter 4, we report on the psychological value of multiple degree of freedom prosthesis control, multisensor prosthesis sensation, and closed-loop control. This chapter represents the first report of prosthesis embodiment during closed-loop and open-loop prosthesis control by an amputee, as well as the most sophisticated closed-loop prosthesis control reported in literature to-date, including 5-degree-of-freedom motor control and sensory feedback from 4 hand locations. Ultimately, we expect that USEA-evoked hand sensations may be used as part of a take-home prosthesis system which will provide users with both advanced functional capabilities and a meaningful sense of embodiment and limb restoration

Implantable Neural Interfaces for Direct Control of Hand Prostheses

State-of-the art robotic hands can mimic many functions of the human hand. These devices are capable of actuating individual finger and multi-joint movements while providing adequate gripping force for daily activities. However, for patients with spinal cord injuries or amputations, there are few options to control these functions seamlessly or intuitively. A common barrier to restoring hand function to both populations is a lack of high-fidelity control signals. Non-invasive electrophysiological techniques record global summations of activity and lack the spatial or temporal resolution to extract or “decode” precise movement commands. The ability to decode finger movements from the motor system would allow patients to directly control hand functions and provide intuitive and scalable prosthetic solutions. This thesis investigates the capabilities of implantable devices to provide finger-specific commands for prosthetic hands. We adapt existing reasoning algorithms to two different sensing technologies. The first is intracortical electrode arrays implanted into primary motor cortex of two non-human primates. Both subjects controlled a virtual hand with a regression algorithm that decoded brain activity into finger kinematics. Performance was evaluated with single degree of freedom target matching tasks. Bit rate is a throughput metric that accounts for task difficulty and movement precision. A state-of-the-art re-calibration approach improved throughputs by an average of 33.1%. Notably, decoding performance was not dependent on subjects moving their intact hands. In future research, this approach can improve grasp precision for patients with spinal cord injuries. The second sensing technology is intramuscular electrodes implanted into residual muscles and Regenerative Peripheral Nerve Interfaces of two patients with transradial amputations. Both participants used a high-speed pattern recognition system to switch between 10 individual finger and wrist postures in a virtual environment with an average completion rate of 96.3% and a movement delay of 0.26 seconds. When the set was reduced to five grasp postures, average metrics improved to 100% completion and a 0.14 second delay. These results are a significant improvement over previous studies which report average completion rates ranging from 53.9% to 86.9% and delays of 0.45 to 0.86 seconds. Furthermore, grasp performance remained reliable across arm positions and both participants used this controller to complete a functional assessment with robotic prostheses. For a more dexterous solution, we combined the high-speed pattern recognition system with a regression algorithm that enabled simultaneous position control of both the index finger and middle-ring-small finger group. Both patients used this system to complete a virtual two degree of freedom target matching task with throughputs of 1.79 and 1.15 bits per second each. The controllers in this study used only four and five differentiated inputs, which can likely be processed with portable or implantable hardware. These results demonstrate that implantable sensors can provide patients with fluid and precise control of hand prostheses. However, clinically translatable implantable electronics need to be developed to realize the potential of these sensing and reasoning approaches. Further advancement of this technology will likely increase the utility and demand of robotic prostheses.PHDRoboticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169798/1/akvaskov_1.pd

Development of novel neurophysiological investigations for age-related muscle weakness

Ph. D. Thesis.No Abstract AvailableNIHR Newcastle Biomedical Research Centr

Mechanisms of Impaired Motor Unit Firing Behavior in the Vastus Lateralis Muscle after Stroke

The purpose of this dissertation research project was to examine the role of impaired motor unit firing behavior on force generation after a stroke. We studied the relationship between intrinsic motoneuron properties and inhibitory sensory pathways to deficient motoneuron activity in the vastus lateralis muscle after a stroke. Individuals with stroke often have deficits with force generation and volitional relaxation. Current models of impaired force output after a stroke focus primarily on the pathology within the corticospinal pathway because of decreased descending drive. Though this is an important aspect of deficient motoneuron output, it is incomplete because motoneurons receive other inputs that can shape motor output. Because the motoneuron is the last site of signal integration for muscle contractions, using methods that study motor unit activity can provide a window to the activity in the spinal circuitry. This research study utilized a novel algorithm that decomposed electromyography (EMG) signals into the contributions of the individual motor units. This provided the individual firing instances for a large number of concurrently active motor units during isometric contractions of the knee extensors. In the first aim, the association between the hyperemic response and motor unit firing rate modulation to intermittent, fatiguing contractions was investigated. It was found that the magnitude of blood flow was lower for individuals with stroke compared to healthy controls, but both groups increased blood flow similarly in response to fatiguing contractions. This did not relate to changes in muscle fiber contractibility for the participants with stroke; rather, participants better able to increase blood flow showed greater modulation in motor unit firing rates. To further investigate how ischemic conditions impact motor unit output, the second aim used a blood pressure cuff to completely occlude blood flow through the femoral artery with the intent of activating inhibitory afferent pathways. We found that ischemic conditions had a greater inhibitory impact on motor unit output for individuals with stroke compared to healthy controls, possibly because of hyper-excitable group III/IV afferent pathways. The final aim investigated how stroke related changes in the intrinsic excitability of the motoneurons impacted prolonged motor unit firing during voluntary relaxation. A serotonin reuptake inhibitor was administered to quantify motoneuron sensitivity to neuromodulatory inputs. This study found that the serotonin reuptake inhibitor increased muscle relaxation and may have reduced persistent inward current contributions to prolonged motor unit firing. In conclusion, while damage to the corticospinal tract is a major component to poor functionality, the intrinsic properties of the motoneuron and sensory pathways to the motoneuron pool are essential for understanding deficient motor control after a stroke

A non-invasive human-machine interfacing framework for investigating dexterous control of hand muscles

The recent fast development of virtual reality and robotic assistive devices enables to augment the capabilities of able-body individuals as well as to overcome the motor missing functions of neurologically impaired or amputee individuals. To control these devices, movement intentions can be captured from biological structures involved in the process of motor planning and execution, such as the central nervous system (CNS), the peripheral nervous system (in particular the spinal motor neurons) and the musculoskeletal system. Thus, human-machine interfaces (HMI) enable to transfer neural information from the neuro-muscular system to machines. To prevent any risks due to surgical operations or tissue damage in implementing these HMIs, a non-invasive approach is proposed in this thesis. In the last five decades, surface electromyography (sEMG) has been extensively explored as a non-invasive source of neural information. EMG signals are constituted by the mixed electrical activity of several recruited motor units, the fundamental components of muscle contraction. High-density sEMG (HD-sEMG) with the use of blind source separation methods enabled to identify the discharge patterns of many of these active motor units. From these decomposed discharge patterns, the net common synaptic input (CSI) to the corresponding spinal motor neurons was quantified with cross-correlation in the time and frequency domain or with principal component analysis (PCA) on one or few muscles. It has been hypothesised that this CSI would result from the contribution of spinal descending commands sent by supra-spinal structures and afferences integrated by spinal interneurons. Another motor strategy implying the integration of descending commands at the spinal level is the one regarding the coordination of many muscles to control a large number of articular joints. This neurophysiological mechanism was investigated by measuring a single EMG amplitude per muscle, thus without the use of HD-sEMG and decomposition. In this case, the aim was to understand how the central nervous system (CNS) could control a large set of muscles actuating a vast set of combinations of degrees of freedom in a modular way. Thus, time-invariant patterns of muscle coordination, i.e. muscle synergies , were found in animals and humans from EMG amplitude of many muscles, modulated by time-varying commands to be combined to fulfil complex movements. In this thesis, for the first time, we present a non-invasive framework for human-machine interfaces based on both spinal motor neuron recruitment strategy and muscle synergistic control for unifying the understanding of these two motor control strategies and producing control signals correlated to biomechanical quantities. This implies recording both from many muscles and using HD-sEMG for each muscle. We investigated 14 muscles of the hand, 6 extrinsic and 8 intrinsic. The first two studies, (in Chapters 2 and 3, respectively) present the framework for CSI quantification by PCA and the extraction of the synergistic organisation of spinal motor neurons innervating the 14 investigated muscles. For the latter analysis, in Chapter 3, we proposed the existence of what we named as motor neuron synergies extracted with non-negative matrix factorisation (NMF) from the identified motor neurons. In these first two studies, we considered 7 subjects and 7 grip types involving differently all the four fingers in opposition with the thumb. In the first study, we found that the variance explained by the CSI among all motor neuron spike trains was (53.0 ± 10.9) % and its cross-correlation with force was 0.67 ± 0.10, remarkably high with respect to previous findings. In the second study, 4 motor neuron synergies were identified and associated with the actuation of one finger in opposition with the thumb, finding even higher correlation values with force (over 0.8) for each synergy associated with a finger during the actuation of the relative finger. In Chapter 4, we then extended the set of analysed movements in a vast repertoire of gestures and repeated the analysis of Chapter 3 by finding a different synergistic organisation during the execution of tens of tasks. We divided the contribution among extrinsic and intrinsic muscles and we found that intrinsic better enable single-finger spatial discrimination, while no difference was found in regression of joint angles by dividing the two groups of muscles. Finally, in Chapter 5 we proposed the techniques of the previous chapters for cases of impairment due both to amputation and stroke. We analysed one case of pre and post rehabilitation sessions of a trans-humeral amputee, the case of a post-stroke trans-radial amputee and three cases of acute stroke, i.e. less than one month from the stroke event. We present future perspectives (Chapter 6) aimed to design and implement a platform for both rehabilitation monitoring and myoelectric control. Thus, this thesis provides a bridge between two extensively studied motor control mechanisms, i.e. motor neuron recruitment and muscle synergies, and proposes this framework as suitable for rehabilitation monitoring and control of assistive devices.Open Acces

Multimodal Investigation of the Efficiency and Stability of Microstimulation using Electrodes Coated with PEDOT/CNT and Iridium Oxide

Electrical microstimulation is an invaluable tool in neuroscience research to dissect neural circuits, relate brain areas, and identify relationships between brain structure and behavior. In the clinic, electrical microstimulation has enabled partial restoration of vision, movement, sensation and autonomic functions. Recently, novel materials and new fabrication techniques of traditional metals have emerged such as iridium oxide and the conducting polymer PEDOT/CNT. These materials have demonstrated particular promise in the improvement in electrical efficiency. However, the in vivo stimulation efficiency and the in vivo stability of these materials have not been thoroughly characterized. In this dissertation, we use a multimodal approach to study the efficiency and stability of electrode-tissue interface using novel materials in microstimulation