Forelimb force direction and magnitude independently controlled by spinal modules in the macaque

腕の自由自在な動きをつくりだす多機能な神経細胞群の発見 --運動の方向と大きさを同時にコントロールする神経メカニズムの解明--. 京都大学プレスリリース. 2020-10-14.Primates aren't quite frogs. 京都大学プレスリリース. 2020-10-19.Modular organization of the spinal motor system is thought to reduce the cognitive complexity of simultaneously controlling the large number of muscles and joints in the human body. Although modular organization has been confirmed in the hindlimb control system of several animal species, it has yet to be established in the forelimb motor system or in primates. Expanding upon experiments originally performed in the frog lumbar spinal cord, we examined whether costimulation of two sites in the macaque monkey cervical spinal cord results in motor activity that is a simple linear sum of the responses evoked by stimulating each site individually. Similar to previous observations in the frog and rodent hindlimb, our analysis revealed that in most cases (77% of all pairs) the directions of the force fields elicited by costimulation were highly similar to those predicted by the simple linear sum of those elicited by stimulating each site individually. A comparable simple summation of electromyography (EMG) output, especially in the proximal muscles, suggested that this linear summation of force field direction was produced by a spinal neural mechanism whereby the forelimb motor output recruited by costimulation was also summed linearly. We further found that the force field magnitudes exhibited supralinear (amplified) summation, which was also observed in the EMG output of distal forelimb muscles, implying a novel feature of primate forelimb control. Overall, our observations support the idea that complex movements in the primate forelimb control system are made possible by flexibly combined spinal motor modules

A brain-spinal interface (BSI) system-on-chip (SoC) for closed-loop cortically-controlled intraspinal microstimulation

This paper reports on a fully miniaturized brain-spinal interface system for closed-loop cortically-controlled intraspinal microstimulation (ISMS). Fabricated in AMS 0.35 µm two-poly four-metal complementary metal–oxide–semiconductor technology, this system-on-chip measures ~ 3.46 mm × 3.46 mm and incorporates two identical 4-channel modules, each comprising a spike-recording front-end, embedded digital signal processing (DSP) unit, and programmable stimulating back-end. The DSP unit is capable of generating multichannel trigger signals for a wide array of ISMS triggering patterns based on real-time discrimination of a programmable number of intracortical neural spikes within a pre-specified time-bin duration via thresholding and user-adjustable time–amplitude windowing. The system is validated experimentally using an anesthetized rat model of a spinal cord contusion injury at the T8 level. Multichannel neural spikes are recorded from the cerebral cortex and converted in real time into electrical stimuli delivered to the lumbar spinal cord below the level of the injury, resulting in distinct patterns of hindlimb muscle activation

Neural Interfacing with Dorsal Root Ganglia: Anatomical Characterization and Electrophysiological Recordings with Novel Electrode Arrays

Dorsal root ganglia (DRG), the hubs of neurons conducting sensory information into the spinal cord, are promising targets for clinical and investigative neural interface technologies. DRG stimulation is currently a tertiary therapy for chronic pain patients, which has an estimated prevalence of 11-40% of adults in the United States. In pre-clinical studies, combined neural recording and stimulation at DRG has been used as part of closed-loop systems to drive activity of the limbs and the urinary system. This suggests a role for clinical DRG interfaces to assist, among other patient groups, the nearly 300,000 spinal cord injured patients in the United States. To maximize the utility of DRG interfaces, however, there remains a strong need to improve our understanding of DRG structure. Neural interface technologies for both stimulation and recording rely heavily on the spatial organization of their neural targets. To record high-fidelity neural signals, a microelectrode must be placed within about 200 µm of a neural cell body. Likewise, effective neural stimulation is believed to act on a subset of DRG axons based on their size and target. The spatial organization of DRG, however, has not been previously quantified. In this thesis, I demonstrate a novel algorithm to transform histological cross-sections of DRG to a normalized circular region for quantifying trends across many samples. Using this algorithm on 26 lumbosacral DRG from felines, a common preclinical DRG model, I found that the highest density of neural cell bodies was in the outer 24% radially, primarily at the dorsal aspect. I extended this analysis to a semi-automated cross-DRG analysis in 33 lower lumbar DRG from 10 human donors. I found that the organization of human DRG was similar to felines, with the highest density of cell bodies found in the outer 20-25% of the DRG, depending on spinal level. I also found a trend toward lower small-axon density at the dorsal aspect of L5 DRG, a key region for stimulation applications. To take advantage of this quantitative knowledge of DRG organization, future neural interfaces with DRG will require more advanced technologies. Standard silicon-based electrode arrays, while useful for short-term DRG recordings, ultimately fail in chronic use after several weeks as a result of mechanical mismatch with neural tissue. In this thesis, I demonstrate sensory recording from the surface and interior of sacral DRG during acute surgery using a variety of flexible polyimide microelectrode arrays 4-μm thick and minimum site separation 25 to 40 μm. Using these arrays, I recorded from bladder and somatic afferents with high fidelity. The high density of sites allowed for neural source localization from surface recordings to depths 25 to 107 µm. This finding supports the anatomical analysis suggesting a high density of cell bodies in the dorsal surface region where the surface array was applied. The high site density also allowed for the use of advanced signal processing to decrease analysis time and track neural sources during movement of the array which may occur during future behavioral experiments. This thesis represents significant advances in our understanding of DRG and how to interface with them, particularly related to the way anatomy can inform development of future technologies. Going forward, it will be important to expand the anatomical maps based on organ function and to test the novel flexible arrays in chronic implant experiments.PHDBiomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/153477/1/zsperry_1.pd

Characterizing motor control signals in the spinal cord

The main goal of this project is to develop a rodent model to study the central command signals generated in the brain and spinal cord for the control of motor function in the forearms. The nature of the central command signal has been debated for many decades with only limited progress. This thesis presents a project that investigated this problem using novel techniques. Rats are instrumented to record the control signals in their spinal cord while they are performing lever press task they are trained in. A haptic interface and wireless neural data amplifier system simultaneously collects dynamic and neural data. Isometric force is predicted from force signal using a combination of time-frequency analysis, Principle component analysis and linear filters. Neural-force mapping obtained at one location are subsequently applied to isometric data recorded at other locations. Prediction errors exhibited negative relationship with the isometric position at upper half of movement range. This suggests the presence of restorative forces which are consistent with positional feedback at spinal level. The animal also appears to become unstable in the lower half of their movement ranges, likely caused by a transition from bipedal to quadruped posture. The presence of local feedback and ability for animals to plan postures that are unstable in absence of external forces suggest that descending signal is a reference trajectory planned using internal models. This has important consequences in design of neuroprosthetic actuators: Inverse dynamic models of patient limbs and local positional feedbacks can improve their performance

Intracortical microstimulation of human somatosensory cortex as a source of cutaneous feedback

The field of brain computer interfaces (BCI) has been making rapid advances in decoding brain activity into control signals capable of operating neural prosthetic devices, such as dexterous robotic arms and computer cursors. Potential users of neural prostheses, including people with amputations or spinal cord injuries, retain intact brain function that can be decoded using BCIs. Recent work has demonstrated simultaneous control over up to 10 degrees-of-freedom, but the current paradigms lack a component crucial to normal motor control: somatosensory feedback. Currently, BCIs are controlled using visual feedback alone, which is important for many reaching movement and identifying target locations. However, as the actuators controlled by BCIs become more complex and include devices approximating the performance of human limbs, visual feedback becomes especially limiting, as it cannot convey information used during object manipulation, such as grip force. The objective of this work is to provide real-time, cutaneous, somatosensory feedback to users of dexterous prosthetic limbs under BCI control by applying intracortical microstimulation (ICMS) to primary somatosensory cortex (S1). Long-term microstimulation of the cortex with microelectrode arrays had never been attempted in a human prior to this work, and while this work is ultimately motivated by efforts to improve BCIs, this general approach also enables INTRACORTICAL MICROSTIMULATION OF HUMAN PRIMARY SOMATOSENSORY CORTEX AS A SOURCE OF CUTANEOUS FEEDBACK Sharlene Nicole Flesher, PhD University of Pittsburgh, 2017 v unprecedented access to the human cortex enabling investigations of more basic scientific issues surrounding cutaneous perception, its conscious components, and its role in motor planning and control. To this end, two microelectrode arrays were placed in human somatosensory cortex of a human participant. I first characterized qualities of sensations evoked via ICMS, such as percept location, modality, intensity and size, over a two-year study period. The sensations were found to be focal to a single digit, and increased in intensity linearly with pulse train amplitude, which suggests that ICMS will be a suitable means of relaying locations of object contact with single-digit precision, and a range of grasp forces can be relayed for each location. Additionally, I found these qualities to be stable over a two-year period, suggesting that delivering ICMS was not damaging the electrode-tissue interface. ICMS was then used as a real-time feedback source during BCI control of a robotic limb during tasks ranging from simple force-matching tasks to functional reach, grasp and carry tasks. Finally, we examined the relationship between pulse train parameters and conscious perception of sensations, an endeavor that until now could not have been undertaken. These results demonstrate that ICMS is a suitable means of relaying somatosensory feedback to BCI users. Adding somatosensory feedback to BCI users has the potential to improve embodiment and control of the devices, bringing this technology closer to restoring upper limb function

A Bidirectional Brain-Machine Interface Featuring a Neuromorphic Hardware Decoder.

Bidirectional brain-machine interfaces (BMIs) establish a two-way direct communication link between the brain and the external world. A decoder translates recorded neural activity into motor commands and an encoder delivers sensory information collected from the environment directly to the brain creating a closed-loop system. These two modules are typically integrated in bulky external devices. However, the clinical support of patients with severe motor and sensory deficits requires compact, low-power, and fully implantable systems that can decode neural signals to control external devices. As a first step toward this goal, we developed a modular bidirectional BMI setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits. On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn to decode neural signals recorded from the brain into motor outputs controlling the movements of an external device. The modularity of the BMI allowed us to tune the individual components of the setup without modifying the whole system. In this paper, we present the features of this modular BMI and describe how we configured the network of spiking neuron circuits to implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm that connects bidirectionally the brain of an anesthetized rat with an external object. We show that the chip learned the decoding task correctly, allowing the interfaced brain to control the object's trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is mature enough for the development of BMI modules that are sufficiently low-power and compact, while being highly computationally powerful and adaptive

Implantable Organic Transistors on Biodegradable Scaffolds for the Treatment of the Spinal Cord Injury

Neural plasticity after severe spinal cord injury (SCI) is promoted by activity stimulating treatments such as specific physiotherapeutic training, injection of pharmaceutical cues and electrical stimulation (ES). However, full or even partial recovery of neuronal functionality is difficult to be achieved with current treatments. Organic bioelectronics provides novel architectures and materials that set the basement of modern neuroprosthetics. In this thesis, an active multifunctional implantable device (AMID) is developed that is highly conformable and biodegradable while being fully biocompatible. AMID integrates a three-fold functionality crucial for future treatments of SCI: a microfluidic channel allows the precise administration of anti-inflammatory pharmaceuticals or plasticity inducing agents; patterned electrodes allow delivering of electric stimuli promoting SC plasticity; organic electrochemical transistors allow to transduce bioelectronic activity providing possible information about the regeneration status. Biodegradability opens to transient neuroprostheses that are bioresporbed within the body after the regeneration process thus reducing both chronic foreign body reaction and the needs of secondary surgeries for the removal of the implant. The work starts with the fabrication and validation of the stimulation and sensing architectures onto biodegradable scaffold. Secondary, the sensing of a relevant bioelectric signal (electrocardiogram) is performed. Then, stimulating capability of biodegradable organic transistors is demonstrated with in vitro experiments onto primary neurons and macrophages. Last, the fabrication of the implantable device is presented and preliminary results about in vivo stimulation (on animal SCI model) and implant compatibility are discussed

Neuroprosthetic system to restore locomotion after neuromotor disorder

Neuromodulation of spinal sensorimotor circuits improves motor control in animal models and humans with Spinal Cord Injury (SCI) and Parkinson disease. Stimulation parameters are tuned manually and remain constant during motor execution which is suboptimal to mediate maximum therapeutic effects. Here, I present a novel neuroprosthetic system that enabled adaptive changes of neuromodulation parameters during locomotion and allowed to restore high-fidelity control over leg movements in paralyzed rats. Beyond the therapeutic potential, these findings provide a conceptual and technical framework to personalize neuromodulation treatments for other neurological disorders. Several limitations have restricted the development of neuroprosthetic systems for closed loop neuromodulation. (1) First, it required a mechanistic understanding of the relationships between stimulation features and the recruitment of specific sensorimotor circuits. I found that electrical neuromodulation primarily recruits afferent reflex pathways that lead to coordinated activity of leg muscles during stepping. Moreover, the specific electrode location on the spinal cord could activate distinct reflex pathways and activate specific leg muscle groups of paralyzed rats. These results have been leveraged for the design of flexible and stretchable multi-electrode arrays for electrical and chemical spinal cord stimulation. (2) Second, it was necessary to perform comprehensive mapping experiments to characterize the effect of neuromodulation parameters on hind limb kinematics in order to establish stable and robust feedback signals for real time control. Step height and ground reaction forces emerged as the primary targets for the control of closed loop neuromodulation after spinal cord injury. (3) Third, implementation and optimization of closed-loop neuromodulation strategies necessitated the development of an advanced technological platform that combined feedback and feed-forward loops that match the natural flow of information in the modulated neural systems. These integrated developments allowed animals with complete spinal cord injury to perform over 1000 successive steps without failure, and to climb staircases of various heights and lengths with precision and fluidity. Moreover, the neuroprosthetic system was able to alleviate locomotor deficits in an alpha-synuclein rodent model of Parkinsonâs disease. Current knowledge of human spinal cord properties in response to electrical neuromodulation suggests that the developed control policies can translate into clinical applications to improve neurorehabilitation therapies. Moreover, the developed neuroprosthetic system can readily be interfaced with control signals from the brain to establish cortico-spinal neuroprostheses that are intended to promote activity-dependent plasticity during recovery from spinal cord injury

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

Doctor of Philosophy

dissertationParalysis due to spinal cord injury or stroke can leave a person with intact peripheral nerves and muscles, but deficient volitional motor control, thereby reducing their health and quality of life. Functional neuromuscular stimulation (FNS) has been widely studied and employed in clinical devices to aid and restore lost or deficient motor function. Strong, selective, and fatigue-resistant muscle forces can be evoked by asynchronously stimulating small independent groups of motor neurons via multiple intrafascicular electrodes on an implanted Utah slanted electrode array (USEA). Determining the parameters of asynchronous intrafascicular multi-electrode stimulation (aIFMS), i.e., the per-electrode stimulus intensities and the interelectrode stimulus phasing, to evoke precise muscle force or joint motion presents unique challenges because this system has multiple-inputs, the n independently stimulated electrodes, but only one measurable output, the evoked endpoint isometric force or joint position. This dissertation presents three studies towards developing robust real-time control of aIFMS. The first study developed an adaptive feedforward algorithm for selecting aIFMS per-electrode stimulus intensities and interelectrode stimulus phasing to evoke a variety of isometric ankle plantar-flexion force trajectories. In simulation and experiments, desired step, sinusoidal, and more-complex time-varying isometric forces were successfully evoked. The second study developed a closed-loop feedback control method for determining aIFMS per-electrode stimulus intensities to evoke precise single-muscle isometric ankle plantar-flexion force trajectories, in real-time. Using a proportional closed-loop force-feedback controller, desired step, sinusoid, and more complex time-varying forces were evoked with good response characteristics, even in the presence of nonlinear system dynamics, such as muscle fatigue. The third study adapted and extended the closed-loop feedback controller to the more demanding task of controlling joint position in the presence of opposing joint torques. A proportional-plus-velocity-plus-integral (PIV) joint-angle feedback controller evoked and held desired steps in position with responses th a t were stable, consistent, and robust to disturbances. The controller evoked smooth ramp-up (concentric) and ramp-down (eccentric) motion, as well as precise slow moving sinusoidal motion. The control methods developed in this dissertation provide a foundation for new lower-limb FNS-based neuroprostheses that can generate sustained and coordinated muscle forces and joint motions that will be desired by paralyzed individuals on a daily basis. proportional-plus-velocity-plus-integral (PIV) joint-angle feedback controller evoked and held desired steps in position with responses th a t were stable, consistent, and robust to disturbances. The controller evoked smooth ramp-up (concentric) and ramp-down (eccentric) motion, as well as precise slow moving sinusoidal motion. The control methods developed in this dissertation provide a foundation for new lower-limb FNS-based neuroprostheses that can generate sustained and coordinated muscle forces and joint motions that will be desired by paralyzed individuals on a daily basis