Chad E. Bouton

Restoring cortical control of functional movement in a human with quadriplegia

Millions of people worldwide suffer from diseases that lead to paralysis through disruption of signal pathways between the brain and the muscles. Neuroprosthetic devices are designed to restore lost function and could be used to form an electronic ‘neural bypass’ to circumvent disconnected pathways in the nervous system. It has previously been shown that intracortically recorded signals can be decoded to extract information related to motion, allowing non-human primates and paralysed humans to control computers and robotic arms through imagined movements. In non-human primates, these types of signal have also been used to drive activation of chemically paralysed arm muscles. Here we show that intracortically recorded signals can be linked in real-time to muscle activation to restore movement in a paralysed human. We used a chronically implanted intracortical microelectrode array to record multiunit activity from the motor cortex in a study participant with quadriplegia from cervical spinal cord injury. We applied machine-learning algorithms to decode the neuronal activity and control activation of the participant’s forearm muscles through a custom-built high-resolution neuromuscular electrical stimulation system. The system provided isolated finger movements and the participant achieved continuous cortical control of six different wrist and hand motions. Furthermore, he was able to use the system to complete functional tasks relevant to daily living. Clinical assessment showed that, when using the system, his motor impairment improved from the fifth to the sixth cervical (C5–C6) to the seventh cervical to first thoracic (C7–T1) level unilaterally, conferring on him the critical abilities to grasp, manipulate, and release objects. This is the first demonstration to our knowledge of successful control of muscle activation using intracortically recorded signals in a paralysed human. These results have significant implications in advancing neuroprosthetic technology for people worldwide living with the effects of paralysis.

Using an Artificial Neural Bypass to Restore Cortical Control of Rhythmic Movements in a Human with Quadriplegia

Neuroprosthetic technology has been used to restore cortical control of discrete (non-rhythmic) hand movements in a paralyzed person. However, cortical control of rhythmic movements which originate in the brain but are coordinated by Central Pattern Generator (CPG) neural networks in the spinal cord has not been demonstrated previously. Here we show a demonstration of an artificial neural bypass technology that decodes cortical activity and emulates spinal cord CPG function allowing volitional rhythmic hand movement. The technology uses a combination of signals recorded from the brain, machine-learning algorithms to decode the signals, a numerical model of CPG network, and a neuromuscular electrical stimulation system to evoke rhythmic movements. Using the neural bypass, a quadriplegic participant was able to initiate, sustain, and switch between rhythmic and discrete finger movements, using his thoughts alone. These results have implications in advancing neuroprosthetic technology to restore complex movements in people living with paralysis.

Big data challenges in decoding cortical activity in a human with quadriplegia to inform a brain computer interface

Recent advances in Brain Computer Interfaces (BCIs) have created hope that one day paralyzed patients will be able to regain control of their paralyzed limbs. As part of an ongoing clinical study, we have implanted a 96-electrode Utah array in the motor cortex of a paralyzed human. The array generates almost 3 million data points from the brain every second. This presents several big data challenges towards developing algorithms that should not only process the data in real-time (for the BCI to be responsive) but are also robust to temporal variations and non-stationarities in the sensor data. We demonstrate an algorithmic approach to analyze such data and present a novel method to evaluate such algorithms. We present our methodology with examples of decoding human brain data in real-time to inform a BCI.Recent advances in Brain Computer Interfaces (BCIs) have created hope that one day paralyzed patients will be able to regain control of their paralyzed limbs. As part of an ongoing clinical study, we have implanted a 96-electrode Utah array in the motor cortex of a paralyzed human. The array generates almost 3 million data points from the brain every second. This presents several big data challenges towards developing algorithms that should not only process the data in real-time (for the BCI to be responsive) but are also robust to temporal variations and non-stationarities in the sensor data. We demonstrate an algorithmic approach to analyze such data and present a novel method to evaluate such algorithms. We present our methodology with examples of decoding human brain data in real-time to inform a BCI.

Standardization of methods to record Vagus nerve activity in mice

BackgroundThe vagus nerve plays an important role in the regulation of organ function, including reflex pathways that regulate immunity and inflammation. Recent studies using genetically modified mice have improved our understanding of molecular mechanisms in the neural control of immunity. However, mapping neural signals transmitted in the vagus nerve in mice has been limited by technical challenges. Here, we have standardized an experimental protocol to record compound action potentials transmitted in the vagus nerve.MethodsThe vagus nerve was isolated in Balb/c and B6.129S mice, and placed either on a hook or cuff electrode. The electrical signals from the vagus nerve were digitized using either a Neuralynx or Plexon data acquisition system. Changes in the vagus nerve activity in response to anesthesia, feeding and administration of bacterial endotoxin were analyzed.ResultsWe have developed an electrophysiological recording system to record compound action potentials from the cervical vagus nerve in mice. Cuff electrodes significantly reduce background noise and increase the signal to noise ratio as compared to hook electrodes. Baseline vagus nerve activity varies in response to anesthesia depth and food intake. Analysis of vagus neurograms in different mouse strains (Balb/c and C57BL/6) reveal no significant differences in baseline activity. Importantly, vagus neurogramactivity in wild type and TLR4 receptor knock out mice exhibits receptor dependency of endotoxin mediated signals.ConclusionsThese methods for recording vagus neurogram in mice provide a useful tool to further delineate the role of vagus neural pathways in a standardized murine disease model.

A new 3D self-adaptive nerve electrode for high density peripheral nerve stimulation and recording

We present a novel 3D self-adaptive nerve electrode for high density nerve signal recording and site-specific stimulation. Specifically, a new pre-shaped flexible spiral structure has been developed in order to achieve tight contact with small nerves without any additional mechanical locking structure or force. This unique structure enables the nerve electrode to adapt and maintain close contact with the nerve without compressing it or restricting its movement. The spiral nerve electrodes (inner diameter = 310 μm) with 8 recording channels (electrode diameter = 50 μm) were fabricated and successfully applied to the rat vagus nerve (approximate diameter of 350 μm) in order to record compound action potentials.

Neuroprotective Effects of Trigeminal Nerve Stimulation in Severe Traumatic Brain Injury

Following traumatic brain injury (TBI), ischemia and hypoxia play a major role in further worsening of the damage, a process referred to as ‘secondary injury’. Protecting neurons from causative factors of secondary injury has been the guiding principle of modern TBI management. Stimulation of trigeminal nerve induces pressor response and improves cerebral blood flow (CBF) by activating the rostral ventrolateral medulla. Moreover, it causes cerebrovasodilation through the trigemino-cerebrovascular system and trigemino-parasympathetic reflex. These effects are capable of increasing cerebral perfusion, making trigeminal nerve stimulation (TNS) a promising strategy for TBI management. Here, we investigated the use of electrical TNS for improving CBF and brain oxygen tension (PbrO2), with the goal of decreasing secondary injury. Severe TBI was produced using controlled cortical impact (CCI) in a rat model, and TNS treatment was delivered for the first hour after CCI. In comparison to TBI group, TBI animals with TNS treatment demonstrated significantly increased systemic blood pressure, CBF and PbrO2 at the hyperacute phase of TBI. Furthermore, rats in TNS-treatment group showed significantly reduced brain edema, blood-brain barrier disruption, lesion volume, and brain cortical levels of TNF-α and IL-6. These data provide strong early evidence that TNS could be an effective neuroprotective strategy.

A wrappable microwire electrode for awake, chronic interfacing with small diameter autonomic peripheral nerves

Bioelectronic medicine requires the ability to monitor and modulate nerve activity in awake patients over time. The vagus nerve is a promising stimulation target, and preclinical models often use mice. However, an awake, chronic mouse vagus nerve interface has yet to be demonstrated. Here, we developed a functional wrappable microwire electrode to chronically interface with the small diameter mouse cervical vagus nerve (∼100 μm). In an acute setting, the wrappable microwire had similar recording performance to commercially available electrodes. A chronic, awake mouse model was then developed to record spontaneous compound action potentials (CAPs). Viable signal-to-noise ratios (SNRs) were obtained from the wrappable microwires between 30 and 60 days (n = 8). Weekly impedance measurements showed no correlation between SNR or time. The wrappable microwires successfully interfaced with small diameter nerves and has been validated in a chronic, awake preclinical model, which can better facilitate clinical translation for bioelectronic medicine.

Identification of cytokine-specific sensory neural signals by decoding murine vagus nerve activity

Significance Evolution conferred animals with molecular sensors that monitor cellular and organ function to detect changes in the environment. These activate sensory neural responses that drive the action of reflexes that maintain cellular and physiological homeostasis. Recent advances reveal that neural reflexes modulate the immune system, but it was previously unknown whether cytokine mediators of immunity mediate specific neural signals. Here we develop methods to isolate and decode specific neural signals recorded from the vagus nerve to discriminate between the cytokines IL-1β and TNF. This methodological waveform successfully detects and discriminates between specific cytokine exposures using neural signals. The nervous system maintains physiological homeostasis through reflex pathways that modulate organ function. This process begins when changes in the internal milieu (e.g., blood pressure, temperature, or pH) activate visceral sensory neurons that transmit action potentials along the vagus nerve to the brainstem. IL-1β and TNF, inflammatory cytokines produced by immune cells during infection and injury, and other inflammatory mediators have been implicated in activating sensory action potentials in the vagus nerve. However, it remains unclear whether neural responses encode cytokine-specific information. Here we develop methods to isolate and decode specific neural signals to discriminate between two different cytokines. Nerve impulses recorded from the vagus nerve of mice exposed to IL-1β and TNF were sorted into groups based on their shape and amplitude, and their respective firing rates were computed. This revealed sensory neural groups responding specifically to TNF and IL-1β in a dose-dependent manner. These cytokine-mediated responses were subsequently decoded using a Naive Bayes algorithm that discriminated between no exposure and exposures to IL-1β and TNF (mean successful identification rate 82.9 ± 17.8%, chance level 33%). Recordings obtained in IL-1 receptor-KO mice were devoid of IL-1β–related signals but retained their responses to TNF. Genetic ablation of TRPV1 neurons attenuated the vagus neural signals mediated by IL-1β, and distal lidocaine nerve block attenuated all vagus neural signals recorded. The results obtained in this study using the methodological framework suggest that cytokine-specific information is present in sensory neural signals within the vagus nerve.

Sensing and Decoding Neural Signals for Closed-Loop Neuromodulation and Advanced Diagnostics in Chronic Disease and Injury

Abstract Many neuromodulation devices used to treat disease and injury are “open-loop” in nature and lack sensing and the algorithms required to automatically adjust or provide stimulation based on a measured input. This chapter describes new sensing, neural decoding, and closed-loop technologies that can provide responsive or adaptive stimulation. Furthermore, neural signals in the human brain, and in the peripheral nervous system, carry a tremendous amount of information regarding current health status and can be used for diagnostic purposes. Current and potential neural sensing/decoding methods that could be used for advanced and real-time diagnostics are also discussed.

Advances in Invasive Brain–Computer Interface Technology and Decoding Methods for Restoring Movement and Future Applications

Abstract Many advances have been made in the field of invasive brain–computer interface (BCI) technology in recent years, including improved implantable microelectrodes, better-performing neural decoding algorithms, and the development of invasive BCI systems that have helped restore functional movement in paralyzed clinical study participants. This chapter describes historical developments that have paved the way for recent achievements in the invasive BCI field. Critical technology components of an invasive BCI system are described, and future applications and directions for the field are discussed.