Intracortical Somatosensory Stimulation to Elicit Fingertip Sensations in an Individual With Spinal Cord Injury

Neurology ◽  
2021 ◽  
pp. 10.1212/WNL.0000000000013173
Author(s):  
Matthew Stephen Fifer ◽  
David P McMullen ◽  
Luke E Osborn ◽  
Tessy M Thomas ◽  
Breanne P Christie ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Pulse Amplitude ◽  
Electrode Arrays ◽  
Somatosensory Stimulation ◽  
Cord Injury ◽  
Human Participant ◽  
The Subject ◽  
Tactile Sensations ◽  
Clinical Trial Information

Background and Objectives:The restoration of touch to fingers and fingertips is critical to achieving dexterous neuroprosthetic control for individuals with sensorimotor dysfunction. However, localized fingertip sensations have not been evoked via intracortical microstimulation (ICMS).Methods:Using a novel intraoperative mapping approach, we implanted electrode arrays in the finger areas of left and right somatosensory cortex and delivered ICMS over a 2-year period in a human participant with spinal cord injury.Results:Stimulation evoked tactile sensations in 8 fingers, including fingertips, spanning both hands. Evoked percepts followed expected somatotopic arrangements. The subject was able to reliably identify up to 7 finger-specific sites spanning both hands in a finger discrimination task. The size of the evoked percepts was on average 33% larger than a fingerpad, as assessed via manual markings of a hand image. The size of the evoked percepts increased modestly with increased stimulation intensity, growing 21% as pulse amplitude increased from 20µA to 80µA. Detection thresholds were estimated on a subset of electrodes, with estimates of 9.2-35µA observed, roughly consistent with prior studies.Discussion:These results suggest that ICMS can enable the delivery of consistent and localized fingertip sensations during object manipulation by neuroprostheses for individuals with somatosensory deficits.Clinical Trial Information:This study is registered on ClinicalTrials.gov with identifier NCT03161067.

scholarly journals Neural stimulation and recording performance in human somatosensory cortex over 1500 days

2020 ◽  
Author(s):  
Christopher L. Hughes ◽  
Sharlene N. Flesher ◽  
Jeffrey M. Weiss ◽  
John E. Downey ◽  
Jennifer L. Collinger ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Somatosensory Cortex ◽  
Microelectrode Arrays ◽  
High Amplitude ◽  
Detection Thresholds ◽  
Cord Injury ◽  
Human Participant ◽  
Tactile Sensations ◽  
Over Time

AbstractObjectiveIntracortical microstimulation (ICMS) in somatosensory cortex can restore sensation to people who have lost it due to spinal cord injury or other conditions. One potential challenge for chronic ICMS is whether neural recording and stimulation can remain stable over many years. This is particularly relevant since the recording quality of implanted microelectrode arrays frequently experience degradation over time and stimulation safety has been considered a potential barrier to the clinical use of ICMS. Our objective is to evaluate stability of recordings on intracortical stimulated and non-stimulated electrodes in a human participant across a long period of implantation. Additionally, we would like to assess the ability to evoke sensations with ICMS over time.ApproachIn a study investigating intracortical implants for a bidirectional brain-computer interface, we implanted microelectrode arrays with sputtered iridium oxide tips in the somatosensory cortex of a human participant with a cervical spinal cord injury. We regularly stimulated through electrodes on these microelectrode arrays to evoke tactile sensations on the hand. Here, we quantify the stability of these electrodes in comparison to non-stimulated electrodes implanted in motor cortex over 1500 days in two ways: recorded signal quality and electrode impedances. Additionally, we quantify the perceptual stability of ICMS-evoked sensations with detection thresholds.Main resultsWe found that recording quality, as assessed by the number of electrodes with high-amplitude waveform recordings (> 100 µV), peak-to-peak voltage, noise, and signal-to-noise ratio, generally decreased over time on stimulated and non-stimulated electrodes. However, stimulated electrodes were much more likely to continue to record high-amplitude signals than non-stimulated electrodes. Interestingly, the detection thresholds for stimulus-evoked tactile sensations decreased over time from a median of 31.5 μA at Day 100 to 10.4 μA at Day 1500, with the most substantial changes occurring between Day 100 and Day 500.SignificanceThese results provide evidence that ICMS in human somatosensory cortex can be provided over long periods of time without deleterious effects on recording or stimulation capabilities. In fact, psychophysical sensitivity to stimulation improves over time and stimulation itself may promote more robust long-term neural recordings.

scholarly journals Intraspinal pressure and spinal cord perfusion pressure after spinal cord injury: an observational study

2015 ◽  
Vol 23 (6) ◽  
pp. 763-771 ◽  
Author(s):  
Georgios V. Varsos ◽  
Melissa C. Werndle ◽  
Zofia H. Czosnyka ◽  
Peter Smielewski ◽  
Angelos G. Kolias ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Observational Study ◽  
Morphological Characteristics ◽  
Pulse Amplitude ◽  
Waveform Analysis ◽  
Arterial Blood ◽  
Cord Injury ◽  
Pressure Volume Relationship ◽  
Pulse Waves

OBJECT In contrast to intracranial pressure (ICP) in traumatic brain injury (TBI), intraspinal pressure (ISP) after traumatic spinal cord injury (TSCI) has not received the same attention in terms of waveform analysis. Based on a recently introduced technique for continuous monitoring of ISP, here the morphological characteristics of ISP are observationally described. It was hypothesized that the waveform analysis method used to assess ICP could be similarly applied to ISP. METHODS Data included continuous recordings of ISP and arterial blood pressure (ABP) in 18 patients with severe TSCI. RESULTS The morphology of the ISP pulse waveform resembled the ICP waveform shape and was composed of 3 peaks representing percussion, tidal, and dicrotic waves. Spectral analysis demonstrated the presence of slow, respiratory, and pulse waves at different frequencies. The pulse amplitude of ISP was proportional to the mean ISP, suggesting a similar exponential pressure-volume relationship as in the intracerebral space. The interaction between the slow waves of ISP and ABP is capable of characterizing the spinal autoregulatory capacity. CONCLUSIONS This preliminary observational study confirms morphological and spectral similarities between ISP in TSCI and ICP. Therefore, the known methods used for ICP waveform analysis could be transferred to ISP analysis and, upon verification, potentially used for monitoring TSCI patients.

scholarly journals In Vitro Assay for the Detection of Network Connectivity in Embryonic Stem Cell-Derived Cultures

2018 ◽  
Author(s):  
Jeffrey R Gamble ◽  
Eric T Zhang ◽  
Nisha Iyer ◽  
Shelly Sakiyama-Elbert ◽  
Dennis L Barbour
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Stem Cell ◽  
High Throughput ◽  
Embryonic Stem ◽  
Network Connectivity ◽  
Electrode Arrays ◽  
Functional Connections ◽  
Cord Injury

ABSTRACTStem cell transplantation holds great promise as a repair strategy following spinal cord injury. Embryonic stem cell (ESC) transplantation therapies have elicited encouraging though limited improvement in motor and sensory function with the use of heterogeneous mixtures of spinal cord neural progenitors and ESCs. Recently, transgenic lines of ESCs have been developed to allow for purification of specific candidate populations prior to transplantation, but the functional network connectivity of these populations and its relationship to recovery is difficult to examine with current technological limitations. In this study, we combine an ESC differentiation protocol, multi-electrode arrays (MEAs), and previously developed neuronal connectivity detection algorithms to develop an in vitro high-throughput assay of network connectivity in ESC-derived populations of neurons. Neuronal aggregation results in more consistent detection of individual neuronal activity than dissociated cultures. Both aggregated and dissociated culture types exhibited synchronized bursting behaviors at days 17 and 18 on MEAs, and thousands of statistically significance functional connections were detected in both culture types. Aggregate cultures, however, demonstrate a tight linear relationship between the inter-neuron distance of neuronal pairs and the time delay of the neuronal pair functional connections, whereas dissociated cultures do not. These results suggest that ESC-derived aggregated cultures may reflect some of the spatiotemporal connectivity characteristics of in vivo tissue and prove to be useful models of investigating potentially therapeutic populations of ESC-derived neurons in vitro.NOVELTY AND SIGNIFICANCEPrevious investigations of stem cell-derived network connectivity on multi-electrode arrays (MEAs) have been limited to characterizations of bursting activity or broad averages of overall temporal network correlations, both of which overlook neuronal level interactions. The use of spike-sorting and short-time cross-correlation histograms along with statistical techniques developed specifically for MEAs allows for the characterization of functional connections between individual stem cell-derived neurons. This high-throughput connectivity assay will open doors for future examinations of the differences in functional network formation between various candidate stem cell-derived populations for spinal cord injury transplantation therapies—a critical inquiry into their therapeutic viability.

scholarly journals Predicting the effects of epidural stimulation to improve hand function in patients with spinal cord injury: An active learning-based solution using dynamic sample weighting

2018 ◽  
Author(s):  
Mohammad Kachuee ◽  
Haydn Hoffman ◽  
Lisa D. Moore ◽  
Hamidreza Ghasemi Damavandi ◽  
Tali Homsey ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Active Learning ◽  
Motor Function ◽  
Electrode Arrays ◽  
Epidural Stimulation ◽  
Learning Framework ◽  
Stimulation Parameters ◽  
Cord Injury ◽  
Active Learning Method

AbstractIn patients with chronic spinal cord injury (SCI), few therapies are available to improve neurological function. Neuromodulation of the spinal cord with epidural stimulation (EDS) has shown promise enabling the voluntary activation of motor pools caudal to the level of the injury. EDS is performed with multiple electrode arrays in which several stimulation variables such as the frequency, amplitude, and location of the stimulation significantly affect the type and amplitude of motor responses. This paper presents a novel technique to predict the final functionality of a patient with SCI after cervical EDS within a deep learning framework. Additionally, we suggest a committee-based active learning method to reduce the number of clinical experiments required to optimize EDS stimulation variables by exploring the stimulation configuration space more efficiently. We also developed a novel method to dynamically weight the results of different experiments using neural networks to create an optimal estimate of the quantity of interest. The essence of our approach was to use machine learning methods to predict the hand contraction force in a patient with chronic SCI based on different EDS parameters. The accuracy of the prediction of stimulation outcomes was evaluated based on three measurements: mean absolute error, standard deviation, and correlation coefficient. The results show that the proposed method can be used to reliably predict the outcome of cervical EDS on maximum voluntary contraction force of the hand with a prediction error of approximately 15%. This model could allow scientists to establish stimulation parameters more efficiently for SCI patients to produce enhanced motor responses in this novel application.Author SummarySpinal cord injury (SCI) can lead to permanent sensorimotor deficits that have a major impact on quality of life. In patients with a motor complete injury, there is no therapy available to reliably improve motor function. Recently, neuromodulation of the spinal cord with epidural stimulation (EDS) has allowed patients with motor-complete SCI regain voluntary movement below the level of injury in the cervical and thoracic spine. EDS is performed using multi-electrode arrays placed in the dorsal epidural space spanning several spinal segments. There are numerous stimulation parameters that can be modified to produce different effects on motor function. Previously, defining these parameters was based on observation and empiric testing, which are time-consuming and inefficient processes. There is a need for an automated method to predict motor and sensory function based on a given combination of EDS settings. We developed a novel method to predict the gripping function of a patient with SCI undergoing cervical EDS based on a set of stimulation parameters within a deep learning framework. We also addressed a limiting factor in machine learning methods in EDS, which is a general lack of training measurements for the learning model. We proposed a novel active learning method to minimize the number of training measurements required. The model for predicting responses to EDS could be used by scientists and clinicians to efficiently determine a set of stimulation parameters that produce a desired effect on motor function.

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