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.

Focused ultrasound neuromodulation of the spleen activates an anti-inflammatory response in humans

Focused ultrasound stimulation (FUS) activates mechanosensitive ion channels and is emerging as a method of noninvasive neuromodulation. In preclinical studies, FUS of the spleen (sFUS) activates an anti-inflammatory neural pathway which suppresses acute and chronic inflammation. However, the relevance of sFUS for regulating inflammatory responses in humans is unknown. Here, we used a modified diagnostic ultrasound imaging system to target the spleen of healthy human subjects with 3 min of continuously swept or stationary focused pulsed ultrasound, delivered at three different energy levels within allowable safety exposure limits. Potential anti-inflammatory effects of sFUS were assessed by measuring sFUS-elicited changes in endotoxin-induced tumor necrosis factor (TNF) production in whole blood samples from insonified subjects. We found that stimulation with either continuously swept or focused pulsed ultrasound has an anti-inflammatory effect: sFUS lowers TNF production for >2 h, with TNF returning to baseline by 24 h following sFUS. This response is independent of anatomical target (i.e., spleen hilum or parenchyma) or ultrasound energy level. No clinical, biochemical, or hematological parameters are adversely impacted. This is the first demonstration that sFUS suppresses the normal inflammatory response in humans, with potential implications for noninvasive bioelectronic therapy of inflammatory disorders.

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.

Decoding Neural Activity in Sulcal and White Matter Areas of the Brain to Accurately Predict Individual Finger Movement and Tactile Stimuli of the Human Hand

Millions of people worldwide suffer motor or sensory impairment due to stroke, spinal cord injury, multiple sclerosis, traumatic brain injury, diabetes, and motor neuron diseases such as ALS (amyotrophic lateral sclerosis). A brain-computer interface (BCI), which links the brain directly to a computer, offers a new way to study the brain and potentially restore impairments in patients living with these debilitating conditions. One of the challenges currently facing BCI technology, however, is to minimize surgical risk while maintaining efficacy. Minimally invasive techniques, such as stereoelectroencephalography (SEEG) have become more widely used in clinical applications in epilepsy patients since they can lead to fewer complications. SEEG depth electrodes also give access to sulcal and white matter areas of the brain but have not been widely studied in brain-computer interfaces. Here we show the first demonstration of decoding sulcal and subcortical activity related to both movement and tactile sensation in the human hand. Furthermore, we have compared decoding performance in SEEG-based depth recordings versus those obtained with electrocorticography electrodes (ECoG) placed on gyri. Initial poor decoding performance and the observation that most neural modulation patterns varied in amplitude trial-to-trial and were transient (significantly shorter than the sustained finger movements studied), led to the development of a feature selection method based on a repeatability metric using temporal correlation. An algorithm based on temporal correlation was developed to isolate features that consistently repeated (required for accurate decoding) and possessed information content related to movement or touch-related stimuli. We subsequently used these features, along with deep learning methods, to automatically classify various motor and sensory events for individual fingers with high accuracy. Repeating features were found in sulcal, gyral, and white matter areas and were predominantly phasic or phasic-tonic across a wide frequency range for both HD (high density) ECoG and SEEG recordings. These findings motivated the use of long short-term memory (LSTM) recurrent neural networks (RNNs) which are well-suited to handling transient input features. Combining temporal correlation-based feature selection with LSTM yielded decoding accuracies of up to 92.04 ± 1.51% for hand movements, up to 91.69 ± 0.49% for individual finger movements, and up to 83.49 ± 0.72% for focal tactile stimuli to individual finger pads while using a relatively small number of SEEG electrodes. These findings may lead to a new class of minimally invasive brain-computer interface systems in the future, increasing its applicability to a wide variety of conditions.

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.

Determining grasp selection from arm trajectories via deep learning to enable functional hand movement in tetraplegia

Background

Cervical spinal cord injury severely affects grasping ability of its survivors. Fortunately, many individuals with tetraplegia retain residual arm movements that allow them to reach for objects. We propose a wearable technology that utilizes arm movement trajectory information and deep learning methods to determine grasp selection. Furthermore, we combined this approach with neuromuscular stimulation to determine if self-driven functional hand movement could be enabled in spinal cord injury participants.

Methods

Two cervical SCI participants performed arbitrary and natural reaching movements toward target objects in three-dimensional space, which were recorded using an inertial sensor worn on their wrist. Time series classifiers were trained to recognize the trajectories using either a Dynamic Time Warping (DTW) algorithm or a Long Short-Term Memory (LSTM) recurrent neural network. As an initial proof-of-concept, we demonstrate real-time classification of the arbitrary movements using DTW only (due to its implementation simplicity), which when used in combination with a high density neuromuscular stimulation sleeve with textile electrodes, enabled participants to perform functional grasping.

Results

Participants were able to consistently perform arbitrary two-dimensional and three-dimensional arm movements which could be classified with high accuracy. Furthermore, it was found that natural reaching trajectories for two different target objects (requiring two different grasp types) were distinct and also discriminable with high accuracy. In offline comparisons, LSTM (mean accuracies 99%) performed significantly better than DTW (mean accuracies 86 and 83%) for both arbitrary and natural reaching movements, respectively. Type I and II errors occurred more frequently for DTW (up to 60 and 15%, respectively), whereas it stayed under 5% for LSTM. Also, DTW achieved online accuracy of 79%.

Conclusions

We demonstrate the feasibility of utilizing arm trajectory information to determine grasp selection using a wearable inertial sensor along with DTW and deep learning methods. Importantly, this technology can be successfully used to control neuromuscular stimulation and restore functional independence to individuals living with paralysis.

Trial registration

NCT, NCT03385005. Registered September 26, 2017.

Closed-loop neuromuscular electrical stimulation using feedforward-feedback control and textile electrodes to regulate grasp force in quadriplegia

BACKGROUND

Transcutaneous neuromuscular electrical stimulation is routinely used in physical rehabilitation and more recently in brain-computer interface applications for restoring movement in paralyzed limbs. Due to variable muscle responses to repeated or sustained stimulation, grasp force levels can change significantly over time. Here we develop and assess closed-loop methods to regulate individual finger forces to facilitate functional movement. We combined this approach with custom textile-based electrodes to form a light-weight, wearable device and evaluated in paralyzed study participants.

METHODS

A textile-based electrode sleeve was developed by the study team and Myant, Corp. (Toronto, ON, Canada) and evaluated in a study involving three able-body participants and two participants with quadriplegia. A feedforward-feedback control structure was designed and implemented to accurately maintain finger force levels in a quadriplegic study participant.

RESULTS

Individual finger flexion and extension movements, along with functional grasping, were evoked during neuromuscular electrical stimulation. Closed-loop control methods allowed accurate steady state performance (< 15% error) with a settling time of 0.67 s (SD = 0.42 s) for individual finger contact force in a participant with quadriplegia.

CONCLUSIONS

Textile-based electrodes were identified to be a feasible alternative to conventional electrodes and facilitated individual finger movement and functional grasping. Furthermore, closed-loop methods demonstrated accurate control of individual finger flexion force. This approach may be a viable solution for enabling grasp force regulation in quadriplegia.

TRIAL REGISTRATION

NCT, NCT03385005. Registered Dec. 28, 2017.