Case study: persistent recovery of hand movement and tactile sensation in peripheral nerve injury using targeted transcutaneous spinal cord stimulation

Peripheral nerve injury can lead to chronic pain, paralysis, and loss of sensation, severely affecting quality of life. Spinal cord stimulation has been used in the clinic to provide pain relief arising from peripheral nerve injuries, however, its ability to restore function after peripheral nerve injury have not been explored. Neuromodulation of the spinal cord through transcutaneous spinal cord stimulation (tSCS), when paired with activity-based training, has shown promising results towards restoring volitional limb control in people with spinal cord injury. We show, for the first time, the effectiveness of targeted tSCS in restoring strength (407% increase from 1.79 ± 1.24 N to up to 7.3 ± 0.93 N) and significantly increasing hand dexterity in an individual with paralysis due to a peripheral nerve injury (PNI). Furthermore, this is the first study to document a persisting 3-point improvement during clinical assessment of tactile sensation in peripheral injury after receiving 6 weeks of tSCS. Lastly, the motor and sensory gains persisted for several months after stimulation was received, suggesting tSCS may lead to long-lasting benefits, even in PNI. Non-invasive spinal cord stimulation shows tremendous promise as a safe and effective therapeutic approach with broad applications in functional recovery after debilitating injuries.

Targeted transcutaneous spinal cord stimulation promotes persistent recovery of upper limb strength and tactile sensation in spinal cord injury: a pilot study

Long-term recovery of limb function is a significant unmet need in people with paralysis. Neuromodulation of the spinal cord through epidural stimulation, when paired with intense activity-based training, has shown promising results toward restoring volitional limb control in people with spinal cord injury. Non-invasive neuromodulation of the cervical spinal cord using transcutaneous spinal cord stimulation (tSCS) has shown similar improvements in upper-limb motor control rehabilitation. However, the motor and sensory rehabilitative effects of activating specific cervical spinal segments using tSCS have largely remained unexplored. We show in two individuals with motor-complete SCI that targeted stimulation of the cervical spinal cord resulted in up to a 1,136% increase in exerted force, with weekly activity-based training. Furthermore, this is the first study to document up to a 2-point improvement in clinical assessment of tactile sensation in SCI after receiving tSCS. Lastly, participant gains persisted after a one-month period void of stimulation, suggesting that targeted tSCS may lead to persistent recovery of motor and sensory function.

Case Study: Mapping Evoked Fields in Primary Motor and Sensory Areas via Magnetoencephalography in Tetraplegia

Devices interfacing with the brain through implantation in cortical or subcortical structures have great potential for restoration and rehabilitation in patients with sensory or motor dysfunction. Typical implantation surgeries are planned based on maps of brain activity generated from intact function. However, mapping brain activity for planning implantation surgeries is challenging in the target population due to abnormal residual function and, increasingly often, existing MRI-incompatible implanted hardware. Here, we present methods and results for mapping impaired somatosensory and motor function in an individual with paralysis and an existing brain–computer interface (BCI) device. Magnetoencephalography (MEG) was used to directly map the neural activity evoked during transcutaneous electrical stimulation and attempted movement of the impaired hand. Evoked fields were found to align with the expected anatomy and somatotopic organization. This approach may be valuable for guiding implants in other applications, such as cortical stimulation for pain and to improve implant targeting to help reduce the craniotomy size.

Historical perspectives, challenges, and future directions of implantable brain-computer interfaces for sensorimotor applications

Almost 100 years ago experiments involving electrically stimulating and recording from the brain and the body launched new discoveries and debates on how electricity, movement, and thoughts are related. Decades later the development of brain-computer interface technology began, which now targets a wide range of applications. Potential uses include augmentative communication for locked-in patients and restoring sensorimotor function in those who are battling disease or have suffered traumatic injury. Technical and surgical challenges still surround the development of brain-computer technology, however, before it can be widely deployed. In this review we explore these challenges, historical perspectives, and the remarkable achievements of clinical study participants who have bravely forged new paths for future beneficiaries.

Evoking highly focal percepts in the fingertips through targeted stimulation of sulcal regions of the brain for sensory restoration

Background:

Paralysis and neuropathy, affecting millions of people worldwide, can be accompanied by significant loss of somatosensation. With tactile sensation being central to achieving dexterous movement, brain-computer interface (BCI) researchers have used intracortical and cortical surface electrical stimulation to restore somatotopically-relevant sensation to the hand. However, these approaches are restricted to stimulating the gyral areas of the brain. Since representation of distal regions of the hand extends into the sulcal regions of human primary somatosensory cortex (S1), it has been challenging to evoke sensory percepts localized to the fingertips.

Objective/hypothesis:

Targeted stimulation of sulcal regions of S1, using stereoelectroencephalography (SEEG) depth electrodes, can evoke focal sensory percepts in the fingertips.

Methods:

Two participants with intractable epilepsy received cortical stimulation both at the gyri via high-density electrocorticography (HD-ECoG) grids and in the sulci via SEEG depth electrode leads. We characterized the evoked sensory percepts localized to the hand.

Results:

We show that highly focal percepts can be evoked in the fingertips of the hand through sulcal stimulation. fMRI, myelin content, and cortical thickness maps from the Human Connectome Project elucidated specific cortical areas and sub-regions within S1 that evoked these focal percepts. Within-participant comparisons showed that percepts evoked by sulcal stimulation via SEEG electrodes were significantly more focal (80% less area; p = 0.02) and localized to the fingertips more often, than by gyral stimulation via HD-ECoG electrodes. Finally, sulcal locations with consistent modulation of high-frequency neural activity during mechanical tactile stimulation of the fingertips showed the same somatotopic correspondence as cortical stimulation.

Conclusions:

Our findings indicate minimally invasive sulcal stimulation via SEEG electrodes could be a clinically viable approach to restoring sensation.

Merging brain-computer interface and functional electrical stimulation technologies for movement restoration

BCI (brain-computer interface) and functional electrical stimulation (FES) technologies have advanced significantly over the last several decades. Recent efforts have involved the integration of these technologies with the goal of restoring functional movement in paralyzed patients. Implantable BCIs have provided neural recordings with increased spatial resolution and have been combined with sophisticated neural decoding algorithms and increasingly capable FES systems to advance efforts toward this goal. This chapter reviews historical developments that have occurred as the exciting fields of BCI and FES have evolved and now overlapped to allow new breakthroughs in medicine, targeting restoration of movement and lost function in users with disabilities.

Restoring Movement in Paralysis with a Bioelectronic Neural Bypass Approach: Current State and Future Directions

Bioelectronic medicine is a rapidly growing field that explores targeted neuromodulation in new treatment options addressing both disease and injury. New bioelectronic methods are being developed to monitor and modulate neural activity directly. The therapeutic benefit of these approaches has been validated in recent clinical studies in various conditions, including paralysis. By using decoding and modulation strategies together, it is possible to restore lost function to those living with paralysis and other debilitating conditions by interpreting and rerouting signals around the affected portion of the nervous system. This, in effect, creates a bioelectronic "neural bypass" to serve the function of the damaged/degenerated network. By learning the language of neurons and using neural interface technology to tap into critical networks, new approaches to repairing or restoring function in areas impacted by disease or injury may become a reality.

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

BACKGROUND

Glucose is a crucial energy source. In humans, it is the primary sugar for high energy demanding cells in brain, muscle and peripheral neurons. Deviations of blood glucose levels from normal levels for an extended period of time is dangerous or even fatal, so regulation of blood glucose levels is a biological imperative. The vagus nerve, comprised of sensory and motor fibres, provides a major anatomical substrate for regulating metabolism. While prior studies have implicated the vagus nerve in the neurometabolic interface, its specific role in either the afferent or efferent arc of this reflex remains elusive.

METHODS

Here we use recently developed methods to isolate and decode specific neural signals acquired from the surface of the vagus nerve in BALB/c wild type mice to identify those that respond robustly to hypoglycemia. We also attempted to decode neural signals related to hyperglycemia. In addition to wild type mice, we analyzed the responses to acute hypo- and hyperglycemia in transient receptor potential cation channel subfamily V member 1 (TRPV1) cell depleted mice. The decoding algorithm uses neural signals as input and reconstructs blood glucose levels.

RESULTS

Our algorithm was able to reconstruct the blood glucose levels with high accuracy (median error 18.6 mg/dl). Hyperglycemia did not induce robust vagus nerve responses, and deletion of TRPV1 nociceptors attenuated the hypoglycemia-dependent vagus nerve signals.

CONCLUSION

These results provide insight to the sensory vagal signaling that encodes hypoglycemic states and suggest a method to measure blood glucose levels by decoding nerve signals.

TRIAL REGISTRATION

Not applicable.

A High Definition Noninvasive Neuromuscular Electrical Stimulation System for Cortical Control of Combinatorial Rotary Hand Movements in a Human With Tetraplegia

OBJECTIVE

Paralysis resulting from spinal cord injury (SCI) can have a devastating effect on multiple arm and hand motor functions. Rotary hand movements, such as supination and pronation, are commonly impaired by upper extremity paralysis, and are essential for many activities of daily living. In this proof-of-concept study, we utilize a neural bypass system (NBS) to decode motor intention from motor cortex to control combinatorial rotary hand movements elicited through stimulation of the arm muscles, effectively bypassing the SCI of the study participant. We describe the NBS system architecture and design that enabled this functionality.

METHODS

The NBS consists of three main functional components: 1) implanted intracortical microelectrode array, 2) neural data processing using a computer, and, 3) a noninvasive neuromuscular electrical stimulation (NMES) system.

RESULTS

We address previous limitations of the NBS, and confirm the enhanced capability of the NBS to enable, in real-time, combinatorial hand rotary motor functions during a functionally relevant object manipulation task.

CONCLUSION

This enhanced capability was enabled by accurate decoding of multiple movement intentions from the participant's motor cortex, interleaving NMES patterns to combine hand movements, and dynamically switching between NMES patterns to adjust for hand position changes during movement.

SIGNIFICANCE

These results have implications for enabling complex rotary hand functions in sequence with other functionally relevant movements for patients suffering from SCI, stroke, and other sensorimotor dysfunctions.

Extracting wavelet based neural features from human intracortical recordings for neuroprosthetics applications

Background

Understanding the long-term behavior of intracortically-recorded signals is essential for improving the performance of Brain Computer Interfaces. However, few studies have systematically investigated chronic neural recordings from an implanted microelectrode array in the human brain.

Methods

In this study, we show the applicability of wavelet decomposition method to extract and demonstrate the utility of long-term stable features in neural signals obtained from a microelectrode array implanted in the motor cortex of a human with tetraplegia. Wavelet decomposition was applied to the raw voltage data to generate mean wavelet power (MWP) features, which were further divided into three sub-frequency bands, low-frequency MWP (lf-MWP, 0–234 Hz), mid-frequency MWP (mf-MWP, 234 Hz–3.75 kHz) and high-frequency MWP (hf-MWP, >3.75 kHz). We analyzed these features using data collected from two experiments that were repeated over the course of about 3 years and compared their signal stability and decoding performance with the more standard threshold crossings, local field potentials (LFP), multi-unit activity (MUA) features obtained from the raw voltage recordings.

Results

All neural features could stably track neural information for over 3 years post-implantation and were less prone to signal degradation compared to threshold crossings. Furthermore, when used as an input to support vector machine based decoding algorithms, the mf-MWP and MUA demonstrated significantly better performance, respectively, in classifying imagined motor tasks than using the lf-MWP, hf-MWP, LFP, or threshold crossings.

Conclusions

Our results suggest that using MWP features in the appropriate frequency bands can provide an effective neural feature for brain computer interface intended for chronic applications.

Trial registration

This study was approved by the U.S. Food and Drug Administration (Investigational Device Exemption) and the Ohio State University Medical Center Institutional Review Board (Columbus, Ohio). The study conformed to institutional requirements for the conduct of human subjects and was filed on ClinicalTrials.gov (Identifier NCT01997125).

Electronic supplementary material

The online version of this article (10.1186/s42234-018-0011-x) contains supplementary material, which is available to authorized users.

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

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.

Neuroprosthetic-enabled control of graded arm muscle contraction in a paralyzed human

Neuroprosthetics that combine a brain computer interface (BCI) with functional electrical stimulation (FES) can restore voluntary control of a patients’ own paralyzed limbs. To date, human studies have demonstrated an “all-or-none” type of control for a fixed number of pre-determined states, like hand-open and hand-closed. To be practical for everyday use, a BCI-FES system should enable smooth control of limb movements through a continuum of states and generate situationally appropriate, graded muscle contractions. Crucially, this functionality will allow users of BCI-FES neuroprosthetics to manipulate objects of different sizes and weights without dropping or crushing them. In this study, we present the first evidence that using a BCI-FES system, a human with tetraplegia can regain volitional, graded control of muscle contraction in his paralyzed limb. In addition, we show the critical ability of the system to generalize beyond training states and accurately generate wrist flexion states that are intermediate to training levels. These innovations provide the groundwork for enabling enhanced and more natural fine motor control of paralyzed limbs by BCI-FES neuroprosthetics.

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 User-Configurable Headstage for Multimodality Neuromonitoring in Freely Moving Rats

Multimodal monitoring of brain activity, physiology, and neurochemistry is an important approach to gain insight into brain function, modulation, and pathology. With recent progress in micro- and nanotechnology, micro-nano-implants have become important catalysts in advancing brain research. However, to date, only a limited number of brain parameters have been measured simultaneously in awake animals in spite of significant recent progress in sensor technology. Here we have provided a cost and time effective approach to designing a headstage to conduct a multimodality brain monitoring in freely moving animals. To demonstrate this method, we have designed a user-configurable headstage for our micromachined multimodal neural probe. The headstage can reliably record direct-current electrocorticography (DC-ECoG), brain oxygen tension (PbrO₂), cortical temperature, and regional cerebral blood flow (rCBF) simultaneously without significant signal crosstalk or movement artifacts for 72 h. Even in a noisy environment, it can record low-level neural signals with high quality. Moreover, it can easily interface with signal conditioning circuits that have high power consumption and are difficult to miniaturize. To the best of our knowledge, this is the first time where multiple physiological, biochemical, and electrophysiological cerebral variables have been simultaneously recorded from freely moving rats. We anticipate that the developed system will aid in gaining further insight into not only normal cerebral functioning but also pathophysiology of conditions such as epilepsy, stroke, and traumatic brain injury.

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.

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.

Cytokine-specific Neurograms in the Sensory Vagus Nerve

The axons of the sensory, or afferent, vagus nerve transmit action potentials to the central nervous system in response to changes in the body's metabolic and physiological status. Recent advances in identifying neural circuits that regulate immune responses to infection, inflammation and injury have revealed that vagus nerve signals regulate the release of cytokines and other factors produced by macrophages. Here we record compound action potentials in the cervical vagus nerve of adult mice and reveal the specific activity that occurs following administration of the proinflammatory cytokines tumor necrosis factor (TNF) and interleukin 1β (IL-1β). Importantly, the afferent vagus neurograms generated by TNF exposure are abolished in double knockout mice lacking TNF receptors 1 and 2 (TNF-R1/2KO), whereas IL-1β-specific neurograms are eliminated in knockout mice lacking IL-1β receptor (IL-1RKO). Conversely, TNF neurograms are preserved in IL-1RKO mice, and IL-1β neurograms are unchanged in TNF-R1/2KO mice. Analysis of the temporal dynamics and power spectral characteristics of afferent vagus neurograms for TNF and IL-1β reveals cytokine-selective signals. The nodose ganglion contains the cell bodies of the sensory neurons whose axons run through the vagus nerve. The nodose neurons express receptors for TNF and IL-1β, and we show that exposing them to TNF and IL-1β significantly stimulates their calcium uptake. Together these results indicate that afferent vagus signals in response to cytokines provide a basic model of nervous system sensing of immune responses.

Characterization and DNA sequence of the b6w2 allotype of the rabbit immunoglobulin kappa 1 light chain (b locus)

The b6w2 allotype of the constant region of the rabbit immunoglobulin kappa 1 (K1) light chain (b locus) was discovered in wild populations from northern Spain. At the serological level, the b6w2 allotype is characterized by the presentation of all b6-specific epitopes, while an allotypic determinant which is shared between the nominal b5 and b6 allotypes is lacking. The DNA fragment encoding the b6w2 allotype was amplified by means of the polymerase chain reaction, and sequenced directly by dideoxy-DNA-sequencing. When compared with the sequence of the nominal b6 allele, the b6w2 sequence differs at eleven nucleotide positions (96.5% similarity). This variation corresponds to amino acid replacements at 1) the three positions C-terminal to the peptidyl junction with the variable region (amino acid positions 109-111); 2) the four positions N-terminal to the interdomain disulfide bond (167-170); and 3) two positions in the vicinity of the interchain disulfide bond (190 and 210). The nature and distribution of the observed nucleotide substitutions strongly suggest a possible role of the extra interdomain disulfide bond in the unusual evolutionary dynamics of the rabbit K1 light chain.