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Bhowmick S, Graham RD, Verma N, Trevathan JK, Franke M, Nieuwoudt S, Fisher LE, Shoffstall AJ, Weber DJ, Ludwig KA, Lempka SF. Computational modeling of dorsal root ganglion stimulation using an Injectrode. J Neural Eng 2024; 21:026039. [PMID: 38502956 PMCID: PMC11007586 DOI: 10.1088/1741-2552/ad357f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 02/23/2024] [Accepted: 03/19/2024] [Indexed: 03/21/2024]
Abstract
Objective.Minimally invasive neuromodulation therapies like the Injectrode, which is composed of a tightly wound polymer-coated Platinum/Iridium microcoil, offer a low-risk approach for administering electrical stimulation to the dorsal root ganglion (DRG). This flexible electrode is aimed to conform to the DRG. The stimulation occurs through a transcutaneous electrical stimulation (TES) patch, which subsequently transmits the stimulation to the Injectrode via a subcutaneous metal collector. However, it is important to note that the effectiveness of stimulation through TES relies on the specific geometrical configurations of the Injectrode-collector-patch system. Hence, there is a need to investigate which design parameters influence the activation of targeted neural structures.Approach.We employed a hybrid computational modeling approach to analyze the impact of Injectrode system design parameters on charge delivery and neural response to stimulation. We constructed multiple finite element method models of DRG stimulation, followed by the implementation of multi-compartment models of DRG neurons. By calculating potential distribution during monopolar stimulation, we simulated neural responses using various parameters based on prior acute experiments. Additionally, we developed a canonical monopolar stimulation and full-scale model of bipolar bilateral L5 DRG stimulation, allowing us to investigate how design parameters like Injectrode size and orientation influenced neural activation thresholds.Main results.Our findings were in accordance with acute experimental measurements and indicate that the minimally invasive Injectrode system predominantly engages large-diameter afferents (Aβ-fibers). These activation thresholds were contingent upon the surface area of the Injectrode. As the charge density decreased due to increasing surface area, there was a corresponding expansion in the stimulation amplitude range before triggering any pain-related mechanoreceptor (Aδ-fibers) activity.Significance.The Injectrode demonstrates potential as a viable technology for minimally invasive stimulation of the DRG. Our findings indicate that utilizing a larger surface area Injectrode enhances the therapeutic margin, effectively distinguishing the desired Aβactivation from the undesired Aδ-fiber activation.
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Affiliation(s)
- Sauradeep Bhowmick
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States of America
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, United States of America
| | - Robert D Graham
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States of America
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, United States of America
| | - Nishant Verma
- Department of Biomedical Engineering, University of Wisconsin–Madison, Madison, WI, United States of America
- Wisconsin Institute for Translational Neuroengineering (WITNe)–Madison, Madison, WI, United States of America
| | - James K Trevathan
- Department of Biomedical Engineering, University of Wisconsin–Madison, Madison, WI, United States of America
- Wisconsin Institute for Translational Neuroengineering (WITNe)–Madison, Madison, WI, United States of America
| | | | | | - Lee E Fisher
- Rehab Neural Engineering Labs (RNEL), Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Andrew J Shoffstall
- Neuronoff Inc., Cleveland, OH, United States of America
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States of America
| | - Douglas J Weber
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States of America
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, United States of America
| | - Kip A Ludwig
- Department of Biomedical Engineering, University of Wisconsin–Madison, Madison, WI, United States of America
- Wisconsin Institute for Translational Neuroengineering (WITNe)–Madison, Madison, WI, United States of America
- Department of Neurosurgery, University of Wisconsin–Madison, Madison, WI, United States of America
| | - Scott F Lempka
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States of America
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, United States of America
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, United States of America
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Tomaselli L, Sciullo M, Fulton S, Yates BJ, Fisher LE, Ventura V, Horn CC. Isoflurane anesthesia suppresses gastric myoelectric power in the ferret. Neurogastroenterol Motil 2024; 36:e14749. [PMID: 38316631 PMCID: PMC10922358 DOI: 10.1111/nmo.14749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 12/14/2023] [Accepted: 01/16/2024] [Indexed: 02/07/2024]
Abstract
BACKGROUND Gastric myoelectric signals have been the focus of extensive research; although it is unclear how general anesthesia affects these signals, and studies have often been conducted under general anesthesia. Here, we explore this issue directly by recording gastric myoelectric signals during awake and anesthetized states in the ferret and explore the contribution of behavioral movement to observed changes in signal power. METHODS Ferrets were surgically implanted with electrodes to record gastric myoelectric activity from the serosal surface of the stomach, and, following recovery, were tested in awake and isoflurane-anesthetized conditions. Video recordings were also analyzed during awake experiments to compare myoelectric activity during behavioral movement and rest. KEY RESULTS A significant decrease in gastric myoelectric signal power was detected under isoflurane anesthesia compared to the awake condition. Moreover, a detailed analysis of the awake recordings indicates that behavioral movement is associated with increased signal power compared to rest. CONCLUSIONS & INFERENCES These results suggest that both general anesthesia and behavioral movement can affect the signal power of gastric myoelectric recordings. In summary, caution should be taken in studying myoelectric data collected under anesthesia. Further, behavioral movement could have an important modulatory role on these signals, affecting their interpretation in clinical settings.
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Affiliation(s)
- Lorenzo Tomaselli
- Department of Statistics & Data Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Michael Sciullo
- UPMC Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Stephanie Fulton
- UPMC Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Bill J. Yates
- Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA
- Dept. of Otolaryngology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Lee E. Fisher
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Physical Medicine & Rehabilitation, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Valérie Ventura
- Department of Statistics & Data Science, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Charles C. Horn
- UPMC Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Medicine, Division of Hematology/Oncology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
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3
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Barra B, Kumar R, Gopinath C, Mirzakhalili E, Lempka SF, Gaunt RA, Fisher LE. High-frequency amplitude-modulated sinusoidal stimulation induces desynchronized yet controllable neural firing. bioRxiv 2024:2024.02.14.580219. [PMID: 38405798 PMCID: PMC10888888 DOI: 10.1101/2024.02.14.580219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Regaining sensory feedback is pivotal for people living with limb amputation. Electrical stimulation of sensory fibers in peripheral nerves has been shown to restore focal percepts in the missing limb. However, conventional rectangular current pulses induce sensations often described as unnatural. This is likely due to the synchronous and periodic nature of activity evoked by these pulses. Here we introduce a fast-oscillating amplitude-modulated sinusoidal (FAMS) stimulation waveform that desynchronizes evoked neural activity. We used a computational model to show that sinusoidal waveforms evoke asynchronous and irregular firing and that firing patterns are frequency dependent. We designed the FAMS waveform to leverage both low- and high-frequency effects and found that membrane non-linearities enhance neuron-specific differences when exposed to FAMS. We implemented this waveform in a feline model of peripheral nerve stimulation and demonstrated that FAMS-evoked activity is more asynchronous than activity evoked by rectangular pulses, while being easily controllable with simple stimulation parameters. These results represent an important step towards biomimetic stimulation strategies useful for clinical applications to restore sensory feedback.
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Affiliation(s)
- Beatrice Barra
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Neuroscience Institute, New York University Langone Health, New York, USA
| | - Ritesh Kumar
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, USA
| | - Chaitanya Gopinath
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ehsan Mirzakhalili
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, USA
| | - Scott F. Lempka
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA
| | - Robert A. Gaunt
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, USA
- Department of Physical Medicine & Rehabilitation, University of Pittsburgh, Pittsburgh, USA
| | - Lee E Fisher
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, USA
- Department of Physical Medicine & Rehabilitation, University of Pittsburgh, Pittsburgh, USA
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4
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Nanivadekar AC, Bose R, Petersen BA, Okorokova EV, Sarma D, Madonna TJ, Barra B, Farooqui J, Dalrymple AN, Levy I, Helm ER, Miele VJ, Boninger ML, Capogrosso M, Bensmaia SJ, Weber DJ, Fisher LE. Publisher Correction: Restoration of sensory feedback from the foot and reduction of phantom limb pain via closed-loop spinal cord stimulation. Nat Biomed Eng 2023:10.1038/s41551-023-01175-2. [PMID: 38155296 DOI: 10.1038/s41551-023-01175-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2023]
Affiliation(s)
- Ameya C Nanivadekar
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Rohit Bose
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Bailey A Petersen
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Elizaveta V Okorokova
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL, USA
| | - Devapratim Sarma
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Tyler J Madonna
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beatrice Barra
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neuroscience and Movement Science, University of Fribourg, Fribourg, Switzerland
| | - Juhi Farooqui
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Ashley N Dalrymple
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
- Department of Physical Medicine and Rehabilitation, University of Utah, Salt Lake City, UT, USA
| | - Isaiah Levy
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Eric R Helm
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Vincent J Miele
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Michael L Boninger
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Marco Capogrosso
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Sliman J Bensmaia
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL, USA
| | - Douglas J Weber
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Lee E Fisher
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA.
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA.
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5
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Nanivadekar AC, Bose R, Petersen BA, Okorokova EV, Sarma D, Madonna TJ, Barra B, Farooqui J, Dalrymple AN, Levy I, Helm ER, Miele VJ, Boninger ML, Capogrosso M, Bensmaia SJ, Weber DJ, Fisher LE. Restoration of sensory feedback from the foot and reduction of phantom limb pain via closed-loop spinal cord stimulation. Nat Biomed Eng 2023:10.1038/s41551-023-01153-8. [PMID: 38097809 DOI: 10.1038/s41551-023-01153-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 10/27/2023] [Indexed: 12/30/2023]
Abstract
Restoring somatosensory feedback in individuals with lower-limb amputations would reduce the risk of falls and alleviate phantom limb pain. Here we show, in three individuals with transtibial amputation (one traumatic and two owing to diabetic peripheral neuropathy), that sensations from the missing foot, with control over their location and intensity, can be evoked via lateral lumbosacral spinal cord stimulation with commercially available electrodes and by modulating the intensity of stimulation in real time on the basis of signals from a wireless pressure-sensitive shoe insole. The restored somatosensation via closed-loop stimulation improved balance control (with a 19-point improvement in the composite score of the Sensory Organization Test in one individual) and gait stability (with a 5-point improvement in the Functional Gait Assessment in one individual). And over the implantation period of the stimulation leads, the three individuals experienced a clinically meaningful decrease in phantom limb pain (with an average reduction of nearly 70% on a visual analogue scale). Our findings support the further clinical assessment of lower-limb neuroprostheses providing somatosensory feedback.
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Affiliation(s)
- Ameya C Nanivadekar
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Rohit Bose
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Bailey A Petersen
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Elizaveta V Okorokova
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL, USA
| | - Devapratim Sarma
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Tyler J Madonna
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beatrice Barra
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neuroscience and Movement Science, University of Fribourg, Fribourg, Switzerland
| | - Juhi Farooqui
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Ashley N Dalrymple
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
- Department of Physical Medicine and Rehabilitation, University of Utah, Salt Lake City, UT, USA
| | - Isaiah Levy
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Eric R Helm
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Vincent J Miele
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Michael L Boninger
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Marco Capogrosso
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Sliman J Bensmaia
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL, USA
| | - Douglas J Weber
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Lee E Fisher
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA.
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA.
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Fisher LE, Gaunt RA, Huang H. Sensory Restoration for Improved Motor Control of Prostheses. Curr Opin Biomed Eng 2023; 28:100498. [PMID: 37860289 PMCID: PMC10583965 DOI: 10.1016/j.cobme.2023.100498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2023]
Abstract
Somatosensory neuroprostheses are devices with the potential to restore the senses of touch and movement from prosthetic limbs for people with limb amputation or paralysis. By electrically stimulating the peripheral or central nervous system, these devices evoke sensations that appear to emanate from the missing or insensate limb, and when paired with sensors on the prosthesis, they can improve the functionality and embodiment of the prosthesis. There have been major advances in the design of these systems over the past decade, although several important steps remain before they can achieve widespread clinical adoption outside the lab setting. Here, we provide a brief overview of somatosensory neuroprostheses and explores these hurdles and potential next steps towards clinical translation.
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Affiliation(s)
- Lee E. Fisher
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA 15213, USA
- Department of Physical Medicine & Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA
- Center for Neural Basis of Cognition, Pittsburgh, PA 15213, USA
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Robert A. Gaunt
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA 15213, USA
- Department of Physical Medicine & Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA
- Center for Neural Basis of Cognition, Pittsburgh, PA 15213, USA
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - He Huang
- UNC/NC State Joint Department of Biomedical Engineering, North Carolina State University, Raleigh, NC 27695, USA
- UNC/NC State Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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7
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Balaguer JM, Prat-Ortega G, Verma N, Yadav P, Sorensen E, de Freitas R, Ensel S, Borda L, Donadio S, Liang L, Ho J, Damiani A, Grigsby E, Fields DP, Gonzalez-Martinez JA, Gerszten PC, Fisher LE, Weber DJ, Pirondini E, Capogrosso M. SUPRASPINAL CONTROL OF MOTONEURONS AFTER PARALYSIS ENABLED BY SPINAL CORD STIMULATION. medRxiv 2023:2023.11.29.23298779. [PMID: 38076797 PMCID: PMC10705627 DOI: 10.1101/2023.11.29.23298779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Spinal cord stimulation (SCS) restores motor control after spinal cord injury (SCI) and stroke. This evidence led to the hypothesis that SCS facilitates residual supraspinal inputs to spinal motoneurons. Instead, here we show that SCS does not facilitate residual supraspinal inputs but directly triggers motoneurons action potentials. However, supraspinal inputs can shape SCS-mediated activity, mimicking volitional control of motoneuron firing. Specifically, by combining simulations, intraspinal electrophysiology in monkeys and single motor unit recordings in humans with motor paralysis, we found that residual supraspinal inputs transform subthreshold SCS-induced excitatory postsynaptic potentials into suprathreshold events. We then demonstrated that only a restricted set of stimulation parameters enables volitional control of motoneuron firing and that lesion severity further restricts the set of effective parameters. Our results explain the facilitation of voluntary motor control during SCS while predicting the limitations of this neurotechnology in cases of severe loss of supraspinal axons.
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Affiliation(s)
- Josep-Maria Balaguer
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, US
- Dept. of Bioengineering, University of Pittsburgh, Pittsburgh, US
| | - Genis Prat-Ortega
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, US
- Dept. of Neurological Surgery, University of Pittsburgh, Pittsburgh, US
| | - Nikhil Verma
- Dept. of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, US
| | - Prakarsh Yadav
- Dept. of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, US
| | - Erynn Sorensen
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, US
- Dept. of Bioengineering, University of Pittsburgh, Pittsburgh, US
| | - Roberto de Freitas
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, US
- Dept. of Neurological Surgery, University of Pittsburgh, Pittsburgh, US
| | - Scott Ensel
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, US
- Dept. of Bioengineering, University of Pittsburgh, Pittsburgh, US
| | - Luigi Borda
- Dept. of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, US
| | - Serena Donadio
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, US
| | - Lucy Liang
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, US
- Dept. of Bioengineering, University of Pittsburgh, Pittsburgh, US
| | - Jonathan Ho
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, US
- School of Medicine, University of Pittsburgh, Pittsburgh, US
| | - Arianna Damiani
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, US
- Dept. of Bioengineering, University of Pittsburgh, Pittsburgh, US
| | - Erinn Grigsby
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, US
- Dept. of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, US
| | - Daryl P. Fields
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, US
- Dept. of Neurological Surgery, University of Pittsburgh, Pittsburgh, US
| | | | - Peter C. Gerszten
- Dept. of Neurological Surgery, University of Pittsburgh, Pittsburgh, US
| | - Lee E. Fisher
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, US
- Dept. of Bioengineering, University of Pittsburgh, Pittsburgh, US
- Dept. of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, US
- Dept. of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, US
| | - Douglas J. Weber
- Dept. of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, US
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, US
| | - Elvira Pirondini
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, US
- Dept. of Bioengineering, University of Pittsburgh, Pittsburgh, US
- Dept. of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, US
| | - Marco Capogrosso
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, US
- Dept. of Bioengineering, University of Pittsburgh, Pittsburgh, US
- Dept. of Neurological Surgery, University of Pittsburgh, Pittsburgh, US
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8
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Bhowmick S, Graham RD, Verma N, Trevathan JK, Franke M, Nieuwoudt S, Fisher LE, Shoffstall AJ, Weber DJ, Ludwig KA, Lempka SF. Computational modeling of dorsal root ganglion stimulation using an Injectrode. bioRxiv 2023:2023.09.20.558675. [PMID: 37790562 PMCID: PMC10542492 DOI: 10.1101/2023.09.20.558675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Objective Minimally invasive neuromodulation therapies like the Injectrode, which is composed of a tightly wound polymer-coated platinum/iridium microcoil, offer a low-risk approach for administering electrical stimulation to the dorsal root ganglion (DRG). This flexible electrode is aimed to conform to the DRG. The stimulation occurs through a transcutaneous electrical stimulation (TES) patch, which subsequently transmits the stimulation to the Injectrode via a subcutaneous metal collector. However, effectiveness of stimulation relies on the specific geometrical configurations of the Injectrode-collector-patch system. Hence, there is a need to investigate which design parameters influence the activation of targeted neural structures. Approach We employed a hybrid computational modeling approach to analyze the impact of the Injectrode system design parameters on charge delivery and the neural response to stimulation. We constructed multiple finite element method models of DRG stimulation and multi-compartment models of DRG neurons. We simulated the neural responses using parameters based on prior acute preclinical experiments. Additionally, we developed multiple human-scale computational models of DRG stimulation to investigate how design parameters like Injectrode size and orientation influenced neural activation thresholds. Main results Our findings were in accordance with acute experimental measurements and indicated that the Injectrode system predominantly engages large-diameter afferents (Aβ-fibers). These activation thresholds were contingent upon the surface area of the Injectrode. As the charge density decreased due to increasing surface area, there was a corresponding expansion in the stimulation amplitude range before triggering any pain-related mechanoreceptor (Aδ-fibers) activity. Significance The Injectrode demonstrates potential as a viable technology for minimally invasive stimulation of the DRG. Our findings indicate that utilizing a larger surface area Injectrode enhances the therapeutic margin, effectively distinguishing the desired Aβ activation from the undesired Aδ-fiber activation.
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9
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Liang L, Damiani A, Del Brocco M, Rogers ER, Jantz MK, Fisher LE, Gaunt RA, Capogrosso M, Lempka SF, Pirondini E. A systematic review of computational models for the design of spinal cord stimulation therapies: from neural circuits to patient-specific simulations. J Physiol 2023; 601:3103-3121. [PMID: 36409303 PMCID: PMC10259770 DOI: 10.1113/jp282884] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 11/08/2022] [Indexed: 08/02/2023] Open
Abstract
Seventy years ago, Hodgkin and Huxley published the first mathematical model to describe action potential generation, laying the foundation for modern computational neuroscience. Since then, the field has evolved enormously, with studies spanning from basic neuroscience to clinical applications for neuromodulation. Computer models of neuromodulation have evolved in complexity and personalization, advancing clinical practice and novel neurostimulation therapies, such as spinal cord stimulation. Spinal cord stimulation is a therapy widely used to treat chronic pain, with rapidly expanding indications, such as restoring motor function. In general, simulations contributed dramatically to improve lead designs, stimulation configurations, waveform parameters and programming procedures and provided insight into potential mechanisms of action of electrical stimulation. Although the implementation of neural models are relentlessly increasing in number and complexity, it is reasonable to ask whether this observed increase in complexity is necessary for improved accuracy and, ultimately, for clinical efficacy. With this aim, we performed a systematic literature review and a qualitative meta-synthesis of the evolution of computational models, with a focus on complexity, personalization and the use of medical imaging to capture realistic anatomy. Our review showed that increased model complexity and personalization improved both mechanistic and translational studies. More specifically, the use of medical imaging enabled the development of patient-specific models that can help to transform clinical practice in spinal cord stimulation. Finally, we combined our results to provide clear guidelines for standardization and expansion of computational models for spinal cord stimulation.
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Affiliation(s)
- Lucy Liang
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Arianna Damiani
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Matteo Del Brocco
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Evan R Rogers
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
| | - Maria K Jantz
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Lee E Fisher
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Robert A Gaunt
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Marco Capogrosso
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Scott F Lempka
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA
| | - Elvira Pirondini
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
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10
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Elkhadrawi M, Akcakaya M, Fulton S, Yates BJ, Fisher LE, Horn CC. Prediction of gastrointestinal functional state based on myoelectric recordings utilizing a deep neural network architecture. PLoS One 2023; 18:e0289076. [PMID: 37498882 PMCID: PMC10374095 DOI: 10.1371/journal.pone.0289076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 07/10/2023] [Indexed: 07/29/2023] Open
Abstract
Functional and motility-related gastrointestinal (GI) disorders affect nearly 40% percent of the population. Disturbances of GI myoelectric activity have been proposed to play a significant role in these disorders. A significant barrier to usage of these signals in diagnosis and treatment is the lack of consistent relationships between GI myoelectric features and function. A potential cause of this issue is the use of arbitrary classification criteria, such as percentage of power in tachygastric and bradygastric frequency bands. Here we applied automatic feature extraction using a deep neural network architecture on GI myoelectric signals from free-moving ferrets. For each animal, we recorded during baseline control and feeding conditions lasting for 1 h. Data were trained on a 1-dimensional residual convolutional network, followed by a fully connected layer, with a decision based on a sigmoidal output. For this 2-class problem, accuracy was 90%, sensitivity (feeding detection) was 90%, and specificity (baseline detection) was 89%. By comparison, approaches using hand-crafted features (e.g., SVM, random forest, and logistic regression) produced an accuracy from 54% to 82%, sensitivity from 46% to 84% and specificity from 66% to 80%. These results suggest that automatic feature extraction and deep neural networks could be useful to assess GI function for comparing baseline to an active functional GI state, such as feeding. In future testing, the current approach could be applied to determine normal and disease-related GI myoelectric patterns to diagnosis and assess patients with GI disease.
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Affiliation(s)
- Mahmoud Elkhadrawi
- Department of Electrical and Computer Engineering, University of Pittsburgh School of Engineering, Pittsburgh, PA, United States of America
| | - Murat Akcakaya
- Department of Electrical and Computer Engineering, University of Pittsburgh School of Engineering, Pittsburgh, PA, United States of America
| | - Stephanie Fulton
- UPMC Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States of America
| | - Bill J. Yates
- Department of Otolaryngology, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States of America
- Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Lee E. Fisher
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, United States of America
- Department of Physical Medicine & Rehabilitation, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States of America
- Department of Bioengineering, University of Pittsburgh School of Engineering, Pittsburgh, PA, United States of America
| | - Charles C. Horn
- UPMC Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States of America
- Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, United States of America
- Division of Hematology/Oncology, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States of America
- Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States of America
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11
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Abstract
Neurotechnologies for treating pain rely on electrical stimulation of the central or peripheral nervous system to disrupt or block pain signaling and have been commercialized to treat a variety of pain conditions. While their adoption is accelerating, neurotechnologies are still frequently viewed as a last resort, after many other treatment options have been explored. We review the pain conditions commonly treated with electrical stimulation, as well as the specific neurotechnologies used for treating those conditions. We identify barriers to adoption, including a limited understanding of mechanisms of action, inconsistent efficacy across patients, and challenges related to selectivity of stimulation and off-target side effects. We describe design improvements that have recently been implemented, as well as some cutting-edge technologies that may address the limitations of existing neurotechnologies. Addressing these challenges will accelerate adoption and change neurotechnologies from last-line to first-line treatments for people living with chronic pain.
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Affiliation(s)
- Lee E Fisher
- Rehab Neural Engineering Labs, Department of Physical Medicine and Rehabilitation, and Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA;
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
| | - Scott F Lempka
- Department of Biomedical Engineering, Biointerfaces Institute, and Department of Anesthesiology, University of Michigan, Ann Arbor, Michigan, USA;
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12
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Powell MP, Verma N, Sorensen E, Carranza E, Boos A, Fields DP, Roy S, Ensel S, Barra B, Balzer J, Goldsmith J, Friedlander RM, Wittenberg GF, Fisher LE, Krakauer JW, Gerszten PC, Pirondini E, Weber DJ, Capogrosso M. Epidural stimulation of the cervical spinal cord for post-stroke upper-limb paresis. Nat Med 2023; 29:689-699. [PMID: 36807682 DOI: 10.1038/s41591-022-02202-6] [Citation(s) in RCA: 34] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 12/22/2022] [Indexed: 02/22/2023]
Abstract
Cerebral strokes can disrupt descending commands from motor cortical areas to the spinal cord, which can result in permanent motor deficits of the arm and hand. However, below the lesion, the spinal circuits that control movement remain intact and could be targeted by neurotechnologies to restore movement. Here we report results from two participants in a first-in-human study using electrical stimulation of cervical spinal circuits to facilitate arm and hand motor control in chronic post-stroke hemiparesis ( NCT04512690 ). Participants were implanted for 29 d with two linear leads in the dorsolateral epidural space targeting spinal roots C3 to T1 to increase excitation of arm and hand motoneurons. We found that continuous stimulation through selected contacts improved strength (for example, grip force +40% SCS01; +108% SCS02), kinematics (for example, +30% to +40% speed) and functional movements, thereby enabling participants to perform movements that they could not perform without spinal cord stimulation. Both participants retained some of these improvements even without stimulation and no serious adverse events were reported. While we cannot conclusively evaluate safety and efficacy from two participants, our data provide promising, albeit preliminary, evidence that spinal cord stimulation could be an assistive as well as a restorative approach for upper-limb recovery after stroke.
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Affiliation(s)
- Marc P Powell
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nikhil Verma
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
- NeuroMechatronics Lab, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Erynn Sorensen
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Erick Carranza
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Amy Boos
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Daryl P Fields
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
| | - Souvik Roy
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
| | - Scott Ensel
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beatrice Barra
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jeffrey Balzer
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jeff Goldsmith
- Department of Biostatistics, Columbia University, New York, NY, USA
| | - Robert M Friedlander
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - George F Wittenberg
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
- Veterans Affairs HS, Pittsburgh, PA, USA
| | - Lee E Fisher
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - John W Krakauer
- Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
- Department of Neuroscience, Johns Hopkins University, Baltimore, MD, USA
- Department of Physical Medicine and Rehabilitation, Johns Hopkins University, Baltimore, MD, USA
- The Santa Fe Institute, Santa Fe, NM, USA
| | - Peter C Gerszten
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Elvira Pirondini
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Douglas J Weber
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
- NeuroMechatronics Lab, Carnegie Mellon University, Pittsburgh, PA, USA
- The Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Marco Capogrosso
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA.
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.
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13
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Tomaselli L, Sciullo M, Fulton S, Yates BJ, Fisher LE, Ventura V, Horn CC. Anesthesia suppresses gastric myoelectric power in the ferret. bioRxiv 2023:2023.02.23.529745. [PMID: 36865110 PMCID: PMC9980102 DOI: 10.1101/2023.02.23.529745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/03/2023]
Abstract
BACKGROUND Gastrointestinal myoelectric signals have been the focus of extensive research; although it is unclear how general anesthesia affects these signals, studies have often been conducted under general anesthesia. Here, we explore this issue directly by recording gastric myoelectric signals during awake and anesthetized states in the ferret and also explore the contribution of behavioral movement to observed changes in signal power. METHODS Ferrets were surgically implanted with electrodes to record gastric myoelectric activity from the serosal surface of the stomach, and, following recovery, were tested in awake and isoflurane-anesthetized conditions. Video recordings were also analyzed during awake experiments to compare myoelectric activity during behavioral movement and rest. KEY RESULTS A significant decrease in gastric myoelectric signal power was detected under isoflurane anesthesia compared to the awake condition. Moreover, a detailed analysis of the awake recordings indicates that behavioral movement is associated with increased signal power compared to rest. CONCLUSIONS & INFERENCES These results suggest that both general anesthesia and behavioral movement can affect the amplitude of gastric myoelectric. In summary, caution should be taken in studying myoelectric data collected under anesthesia. Further, behavioral movement could have an important modulatory role on these signals, affecting their interpretation in clinical settings.
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14
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Petersen BA, Sparto PJ, Fisher LE. Clinical measures of balance and gait cannot differentiate somatosensory impairments in people with lower-limb amputation. Gait Posture 2023; 99:104-110. [PMID: 36375214 PMCID: PMC9970031 DOI: 10.1016/j.gaitpost.2022.10.018] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 09/30/2022] [Accepted: 10/23/2022] [Indexed: 02/04/2023]
Abstract
BACKGROUND In addition to a range of functional impairments seen in individuals with a lower-limb amputation, this population is at a substantially elevated risk of falls. Studies postulate that the lack of sensory feedback from the prosthetic limb contributes heavily to these impairments, but the extent to which sensation affects functional measures remains unclear. RESEARCH QUESTION The purpose of this study is to determine how sensory impairments in the lower extremities relate to performance with common clinical functional measures of balance and gait in individuals with a lower-limb amputation. Here we evaluate the effects of somatosensory integrity to clinical and lab measures of static, reactive and dynamic balance, and gait stability. METHODS In 20 individuals with lower-limb amputation (AMP) and 20 age and gender-matched able-bodied controls (CON), we evaluated the effects of sensory integrity (pressure, proprioception, and vibration) on measures of balance and gait. Static, reactive, and dynamic balance were assessed using the Sensory Organization Test (SOT), Motor Control Test (MCT), and Functional Gait Assessment (FGA), respectively. Gait stability was assessed through measures of step length asymmetry and step width variability. Sensation was categorized into intact or impaired sensation by pressure thresholds and differences across groups were analyzed. RESULTS There were significant differences between AMP and CON groups for reliance on vision for static balance in the SOT, MCT, and FGA (p < 0.01). Despite differences across groups, there were no significant differences within the AMP group based on intact or impaired sensation across all functional measures. SIGNIFICANCE Despite being able to detect differences between able-bodied individuals and individuals with an amputation, these functional measures cannot distinguish between levels of impairment within participants with an amputation. These findings suggest that more challenging and robust metrics are needed to evaluate the effects of sensation and function in individuals with an amputation.
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Affiliation(s)
- B A Petersen
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA; Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - P J Sparto
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA; Department of Physical Therapy, University of Pittsburgh, Pittsburgh, PA, USA
| | - L E Fisher
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA; Center for the Neural Basis of Cognition, Pittsburgh, PA, USA; Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA; Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.
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15
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Jantz MK, Gopinath C, Kumar R, Chin C, Wong L, Ogren JI, Fisher LE, McLaughlin BL, Gaunt RA. High-density spinal cord stimulation selectively activates lower urinary tract nerves. J Neural Eng 2022; 19:066014. [PMID: 36343359 PMCID: PMC9855651 DOI: 10.1088/1741-2552/aca0c2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 11/07/2022] [Indexed: 11/09/2022]
Abstract
Objective.Epidural spinal cord stimulation (SCS) is a potential intervention to improve limb and autonomic functions, with lumbar stimulation improving locomotion and thoracic stimulation regulating blood pressure. Here, we asked whether sacral SCS could be used to target the lower urinary tract (LUT) and used a high-density epidural electrode array to test whether individual electrodes could selectively recruit LUT nerves.Approach. We placed a high-density epidural SCS array on the dorsal surface of the sacral spinal cord and cauda equina of anesthetized cats and recorded the stimulation-evoked activity from nerve cuffs on the pelvic, pudendal and sciatic nerves.Main results. Here we show that sacral SCS evokes responses in nerves innervating the bladder and urethra and that these nerves can be activated selectively. Sacral SCS always recruited the pelvic and pudendal nerves and selectively recruited both of these nerves in all but one animal. Individual branches of the pudendal nerve were always recruited as well. Electrodes that selectively recruited specific peripheral nerves were spatially clustered on the arrays, suggesting anatomically organized sensory pathways.Significance.This selective recruitment demonstrates a mechanism to directly modulate bladder and urethral function through known reflex pathways, which could be used to restore bladder and urethral function after injury or disease.
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Affiliation(s)
- Maria K Jantz
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, United States of America
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America
- Center for the Neural Basis of Cognition, Pittsburgh, PA, United States of America
| | - Chaitanya Gopinath
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, United States of America
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Ritesh Kumar
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, United States of America
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America
- Center for the Neural Basis of Cognition, Pittsburgh, PA, United States of America
| | - Celine Chin
- Micro-Leads Inc., Somerville, MA, United States of America
| | - Liane Wong
- Micro-Leads Inc., Somerville, MA, United States of America
| | - John I Ogren
- Micro-Leads Inc., Somerville, MA, United States of America
| | - Lee E Fisher
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, United States of America
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America
- Center for the Neural Basis of Cognition, Pittsburgh, PA, United States of America
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, United States of America
- Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States of America
| | | | - Robert A Gaunt
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, United States of America
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America
- Center for the Neural Basis of Cognition, Pittsburgh, PA, United States of America
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, United States of America
- Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States of America
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16
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Nanivadekar AC, Chandrasekaran S, Helm ER, Boninger ML, Collinger JL, Gaunt RA, Fisher LE. Closed-loop stimulation of lateral cervical spinal cord in upper-limb amputees to enable sensory discrimination: a case study. Sci Rep 2022; 12:17002. [PMID: 36220864 PMCID: PMC9553970 DOI: 10.1038/s41598-022-21264-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 09/26/2022] [Indexed: 12/29/2022] Open
Abstract
Modern myoelectric prosthetic hands have multiple independently controllable degrees of freedom, but require constant visual attention to use effectively. Somatosensory feedback provides information not available through vision alone and is essential for fine motor control of our limbs. Similarly, stimulation of the nervous system can potentially provide artificial somatosensory feedback to reduce the reliance on visual cues to efficiently operate prosthetic devices. We have shown previously that epidural stimulation of the lateral cervical spinal cord can evoke tactile sensations perceived as emanating from the missing arm and hand in people with upper-limb amputation. In this case study, two subjects with upper-limb amputation used this somatotopically-matched tactile feedback to discriminate object size and compliance while controlling a prosthetic hand. With less than 30 min of practice each day, both subjects were able to use artificial somatosensory feedback to perform a subset of the discrimination tasks at a success level well above chance. Subject 1 was consistently more adept at determining object size (74% accuracy; chance: 33%) while Subject 2 achieved a higher accuracy level in determining object compliance (60% accuracy; chance 33%). In each subject, discrimination of the other object property was only slightly above or at chance level suggesting that the task design and stimulation encoding scheme are important determinants of which object property could be reliably identified. Our observations suggest that changes in the intensity of artificial somatosensory feedback provided via spinal cord stimulation can be readily used to infer information about object properties with minimal training.
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Affiliation(s)
- Ameya C. Nanivadekar
- grid.21925.3d0000 0004 1936 9000Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213 USA ,grid.509981.c0000 0004 7644 8442Center for Neural Basis of Cognition, Pittsburgh, PA 15213 USA
| | - Santosh Chandrasekaran
- grid.21925.3d0000 0004 1936 9000Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA 15213 USA ,grid.509981.c0000 0004 7644 8442Center for Neural Basis of Cognition, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213 USA
| | - Eric R. Helm
- grid.21925.3d0000 0004 1936 9000Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213 USA
| | - Michael L. Boninger
- grid.21925.3d0000 0004 1936 9000Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000University of Pittsburgh Clinical Translational Science Institute, Pittsburgh, PA 15213 USA
| | - Jennifer L. Collinger
- grid.21925.3d0000 0004 1936 9000Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213 USA ,grid.509981.c0000 0004 7644 8442Center for Neural Basis of Cognition, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213 USA ,Human Engineering Research Labs, Department of Veteran Affairs, VA Center of Excellence, Pittsburgh, PA 15206 USA ,grid.147455.60000 0001 2097 0344Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA USA
| | - Robert A. Gaunt
- grid.21925.3d0000 0004 1936 9000Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213 USA ,grid.509981.c0000 0004 7644 8442Center for Neural Basis of Cognition, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213 USA ,grid.147455.60000 0001 2097 0344Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA USA
| | - Lee E. Fisher
- grid.21925.3d0000 0004 1936 9000Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213 USA ,grid.509981.c0000 0004 7644 8442Center for Neural Basis of Cognition, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213 USA ,grid.147455.60000 0001 2097 0344Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA USA
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17
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Jantz MK, Liang L, Damiani A, Fisher LE, Newton T, Neufeld E, Hitchens TK, Pirondini E, Capogrosso M, Gaunt RA. A Computational Study of Lower Urinary Tract Nerve Recruitment with Epidural Stimulation of the Lumbosacral Spinal Cord. Annu Int Conf IEEE Eng Med Biol Soc 2022; 2022:744-747. [PMID: 36086335 DOI: 10.1109/embc48229.2022.9871292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Bladder dysfunction is a major health risk for people with spinal cord injury. Recently, we have demonstrated that epidural sacral spinal cord stimulation (SCS) can be used to activate lower urinary tract nerves and provide both major components of bladder control: voiding and continence. To effectively control these functions, it is necessary to selectively recruit the afferents of the pudendal nerve that evoke these distinct bladder reflexes. Translation of this innovation to clinical practice requires an understanding of optimal electrode placements and stimulation parameters to guide surgical practice and therapy design. Computational modeling is an important tool to address many of these experimentally intractable stimulation optimization questions. Here, we built a realistic MRI-based finite element computational model of the feline sacral spinal cord which included realistic axon trajectories in the dorsal and ventral roots. We coupled the model with biophysical simulations of membrane dynamics of afferent and efferent axons that project to the lower urinary tract through the pelvic and pudendal nerves. We simulated the electromagnetic fields arising from stimulation through SCS electrodes and calculated the expected recruitment of pelvic and pudendal fibers. We found that SCS can selectively recruit pudendal afferents, in agreement with our experimental data in cats. Our results suggest that SCS is a promising technology to improve bladder function after spinal cord injury, and computational modeling unlocks the potential for highly optimized, selective stimulation. Clinical Relevance - This model provides a method to non-invasively establish electrode placement and stimulation parameters for improving bladder function with epidural spinal cord stimulation.
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18
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Tomaselli L, Sciullo M, Fulton S, Fisher LE, Yates BJ, Ventura V, Horn CC. Impact of Isoflurane Anesthesia on Gastrointestinal Myoelectric Recordings: A Comparative Analysis of Awake and Anesthetized States in Ferrets. FASEB J 2022. [DOI: 10.1096/fasebj.2022.36.s1.r5559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
| | | | | | - Lee E. Fisher
- University of Pittsburgh School of MedicinePittsburghPA
| | - Bill J. Yates
- University of Pittsburgh School of MedicinePittsburghPA
| | - Valérie Ventura
- Statistics and Data ScienceCarnegie Mellon UniversityPittsburghPA
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19
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Verma N, Graham RD, Mudge J, Trevathan JK, Franke M, Shoffstall AJ, Williams J, Dalrymple AN, Fisher LE, Weber DJ, Lempka SF, Ludwig KA. Augmented Transcutaneous Stimulation Using an Injectable Electrode: A Computational Study. Front Bioeng Biotechnol 2022; 9:796042. [PMID: 34988068 PMCID: PMC8722711 DOI: 10.3389/fbioe.2021.796042] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Accepted: 11/25/2021] [Indexed: 11/13/2022] Open
Abstract
Minimally invasive neuromodulation technologies seek to marry the neural selectivity of implantable devices with the low-cost and non-invasive nature of transcutaneous electrical stimulation (TES). The Injectrode® is a needle-delivered electrode that is injected onto neural structures under image guidance. Power is then transcutaneously delivered to the Injectrode using surface electrodes. The Injectrode serves as a low-impedance conduit to guide current to the deep on-target nerve, reducing activation thresholds by an order of magnitude compared to using only surface stimulation electrodes. To minimize off-target recruitment of cutaneous fibers, the energy transfer efficiency from the surface electrodes to the Injectrode must be optimized. TES energy is transferred to the Injectrode through both capacitive and resistive mechanisms. Electrostatic finite element models generally used in TES research consider only the resistive means of energy transfer by defining tissue conductivities. Here, we present an electroquasistatic model, taking into consideration both the conductivity and permittivity of tissue, to understand transcutaneous power delivery to the Injectrode. The model was validated with measurements taken from (n = 4) swine cadavers. We used the validated model to investigate system and anatomic parameters that influence the coupling efficiency of the Injectrode energy delivery system. Our work suggests the relevance of electroquasistatic models to account for capacitive charge transfer mechanisms when studying TES, particularly when high-frequency voltage components are present, such as those used for voltage-controlled pulses and sinusoidal nerve blocks.
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Affiliation(s)
- Nishant Verma
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States.,Wisconsin Institute for Translational Neuroengineering (WITNe)-Madison, Madison, WI, United States
| | - Robert D Graham
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States.,Biointerfaces Institute, University of Michigan, Ann Arbor, MI, United States
| | - Jonah Mudge
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States.,Wisconsin Institute for Translational Neuroengineering (WITNe)-Madison, Madison, WI, United States
| | - James K Trevathan
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States.,Wisconsin Institute for Translational Neuroengineering (WITNe)-Madison, Madison, WI, United States
| | | | - Andrew J Shoffstall
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
| | - Justin Williams
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States.,Wisconsin Institute for Translational Neuroengineering (WITNe)-Madison, Madison, WI, United States
| | - Ashley N Dalrymple
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States.,Rehab Neural Engineering Labs (RNEL), Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, United States
| | - Lee E Fisher
- Rehab Neural Engineering Labs (RNEL), Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, United States
| | - Douglas J Weber
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States.,Rehab Neural Engineering Labs (RNEL), Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, United States
| | - Scott F Lempka
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States.,Biointerfaces Institute, University of Michigan, Ann Arbor, MI, United States.,Department of Anesthesiology, University of Michigan, Ann Arbor, MI, United States
| | - Kip A Ludwig
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States.,Wisconsin Institute for Translational Neuroengineering (WITNe)-Madison, Madison, WI, United States.,Department of Neurosurgery, University of Wisconsin-Madison, Madison, WI, United States
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20
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Rekant J, Fisher LE, Boninger M, Gaunt RA, Collinger JL. Amputee, clinician, and regulator perspectives on current and prospective upper extremity prosthetic technologies. Assist Technol 2022:1-13. [PMID: 34982647 DOI: 10.1080/10400435.2021.2020935] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
Abstract
Existing prosthetic technologies for people with upper limb amputation are being adopted at moderate rates. Once fitted for these devices, many upper limb amputees report not using them regularly or at all. The primary aim of this study was to solicit feedback about prosthetic technology and important device design criteria from amputees, clinicians, and device regulators. We compare these perspectives to identify common or divergent priorities. Twenty-one adults with upper limb loss, 35 clinicians, and 3 regulators completed a survey on existing prosthetic technologies and a conceptual sensorimotor prosthesis driven by implanted myoelectric electrodes with sensory feedback via spinal root stimulation. The survey included questions from the Trinity Amputation and Prosthesis Experience Scale, the Disabilities of the Arm, Shoulder, and Hand, and novel questions about technology acceptance and neuroprosthetic design. User and clinician ratings of satisfaction with existing devices were similar. Amputees were most accepting of the proposed sensorimotor prosthesis (75.5% vs clinicians(68.8%), regulators(67.8%)). Stakeholders valued user-centered outcomes like individualized task goals, improved quality of life, device reliability, and user safety; regulators emphasized these last two. The results of this study provide insight into amputee, clinician, and regulator priorities to inform future upper-limb prosthetic design and clinical trial protocol development.
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Affiliation(s)
- Julie Rekant
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lee E Fisher
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA.,Center for Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Michael Boninger
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA.,Human Engineering Research Labs, VA Center of Excellence, Department of Veteran Affairs, Pittsburgh, PA, USA
| | - Robert A Gaunt
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA.,Center for Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Jennifer L Collinger
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA.,Center for Neural Basis of Cognition, Pittsburgh, PA, USA.,Human Engineering Research Labs, VA Center of Excellence, Department of Veteran Affairs, Pittsburgh, PA, USA
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21
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Beethe AZ, Flanagan SD, Lovalekar M, Fisher LE, Nindl BC, Connaboy C. The Bilateral Deficit Phenomenon in Elbow Flexion: Explanations for Its Inconsistent Occurrence and Detection. Percept Mot Skills 2021; 129:47-62. [PMID: 34913749 DOI: 10.1177/00315125211060953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The underlying mechanism(s) of the Bilateral Deficit (BLD) phenomenon is without consensus. Methodological inconsistencies across prior works may be an important source of equivocal results and interpretations. Based on repeatability problems with the BLD measure and maximal force definition, the presence or absence of the BLD phenomenon is altered, shifting conclusions of its mechanistic cause. Our purpose in this study was to examine methodological inconsistencies in applying the BLD measure to establish optimal methods for evaluating the underlying mechanism. Eleven healthy participants engaged in one familiarity and five test sessions, completing bilateral and unilateral elbow maximal voluntary isometric contractions. We defined maximal force by averaged and absolute peak and plateau values. BLD was evident if the bilateral index (BI), the ratio of the bilateral over summed unilateral forces, was statistically different from zero. We addressed interclass correlations (ICC), Chronbach's α, standard error of the mean, and minimal detectable change between and within sessions for all force measures and BI. We evaluated all combinations of sessions (i.e., 1-2, 3-5, 5-6) and maximal forces to establish the optimal number of sessions to achieve reliability. BLD was present for test sessions, but not for familiarization. All measures of maximal force were highly reliable between and within sessions (ICC(2,1) ≥ .895). BI was only considered significantly reliable in sessions 3-5 (p < .027), defined by absolute and average plateau forces, but reliability was still quantifiably poor (absolute: ICC(2,1) = .392; average: ICC(2,1) = .375). These results demonstrate that high force reliability within and between sessions does not translate to stable and reliable BI, potentially exposing the lack of any defined BLD mechanism.
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Affiliation(s)
- Anne Z Beethe
- Neuromuscular Research Laboratory and Warrior Human Performance Research Center, Department of Sports Medicine and Nutrition, School of Health and Rehabilitation Sciences, 6614University of Pittsburgh, Pittsburgh, PA, USA.,Perception Action Laboratory, Department of Kinesiology and Health Science, Utah State University, Logan, UT, USA
| | - Shawn D Flanagan
- Neuromuscular Research Laboratory and Warrior Human Performance Research Center, Department of Sports Medicine and Nutrition, School of Health and Rehabilitation Sciences, 6614University of Pittsburgh, Pittsburgh, PA, USA
| | - Mita Lovalekar
- Neuromuscular Research Laboratory and Warrior Human Performance Research Center, Department of Sports Medicine and Nutrition, School of Health and Rehabilitation Sciences, 6614University of Pittsburgh, Pittsburgh, PA, USA
| | - Lee E Fisher
- Rehab Neural Engineering Laboratories, Department of Physical Medicine and Rehabilitation, 6614University of Pittsburgh, Pittsburgh, PA, USA
| | - Bradley C Nindl
- Neuromuscular Research Laboratory and Warrior Human Performance Research Center, Department of Sports Medicine and Nutrition, School of Health and Rehabilitation Sciences, 6614University of Pittsburgh, Pittsburgh, PA, USA
| | - Christopher Connaboy
- Neuromuscular Research Laboratory and Warrior Human Performance Research Center, Department of Sports Medicine and Nutrition, School of Health and Rehabilitation Sciences, 6614University of Pittsburgh, Pittsburgh, PA, USA
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22
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Dalrymple AN, Ting JE, Bose R, Trevathan JK, Nieuwoudt S, Lempka SF, Franke M, Ludwig KA, Shoffstall AJ, Fisher LE, Weber DJ. Stimulation of the dorsal root ganglion using an Injectrode ®. J Neural Eng 2021; 18. [PMID: 34650008 DOI: 10.1088/1741-2552/ac2ffb] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 10/14/2021] [Indexed: 01/15/2023]
Abstract
Objective. The goal of this work was to compare afferent fiber recruitment by dorsal root ganglion (DRG) stimulation using an injectable polymer electrode (Injectrode®) and a more traditional cylindrical metal electrode.Approach. We exposed the L6 and L7 DRG in four cats via a partial laminectomy or burr hole. We stimulated the DRG using an Injectrode or a stainless steel (SS) electrode using biphasic pulses at three different pulse widths (80, 150, 300μs) and pulse amplitudes spanning the range used for clinical DRG stimulation. We recorded antidromic evoked compound action potentials (ECAPs) in the sciatic, tibial, and common peroneal nerves using nerve cuffs. We calculated the conduction velocity of the ECAPs and determined the charge-thresholds and recruitment rates for ECAPs from Aα, Aβ, and Aδfibers. We also performed electrochemical impedance spectroscopy measurements for both electrode types.Main results. The ECAP thresholds for the Injectrode did not differ from the SS electrode across all primary afferents (Aα, Aβ, Aδ) and pulse widths; charge-thresholds increased with wider pulse widths. Thresholds for generating ECAPs from Aβfibers were 100.0 ± 32.3 nC using the SS electrode, and 90.9 ± 42.9 nC using the Injectrode. The ECAP thresholds from the Injectrode were consistent over several hours of stimulation. The rate of recruitment was similar between the Injectrodes and SS electrode and decreased with wider pulse widths.Significance. The Injectrode can effectively excite primary afferents when used for DRG stimulation within the range of parameters used for clinical DRG stimulation. The Injectrode can be implanted through minimally invasive techniques while achieving similar neural activation to conventional electrodes, making it an excellent candidate for future DRG stimulation and neuroprosthetic applications.
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Affiliation(s)
- Ashley N Dalrymple
- Department of Mechanical Engineering, Carnegie Mellon University, 5000 Forbes Ave, Wean 1323, Pittsburgh, PA 15217, United States of America.,Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, 15217, United States of America
| | - Jordyn E Ting
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, 15217, United States of America.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America.,Center for Neural Basis of Cognition, Pittsburgh, PA, 15217, United States of America
| | - Rohit Bose
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, 15217, United States of America.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America.,Center for Neural Basis of Cognition, Pittsburgh, PA, 15217, United States of America
| | - James K Trevathan
- Departments of Biomedical Engineering and Neurological Surgery, University of Wisconsin-Madison, Madison, WI, United States of America
| | | | - Scott F Lempka
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States of America
| | | | - Kip A Ludwig
- Departments of Biomedical Engineering and Neurological Surgery, University of Wisconsin-Madison, Madison, WI, United States of America.,Neuronoff Inc., Cleveland, OH, United States of America.,Wisconsin Institute for Translational Neuroengineering (WITNe), Madison, WI, United States of America
| | - Andrew J Shoffstall
- Neuronoff Inc., Cleveland, OH, United States of America.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States of America
| | - Lee E Fisher
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, 15217, United States of America.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America.,Center for Neural Basis of Cognition, Pittsburgh, PA, 15217, United States of America.,Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Douglas J Weber
- Department of Mechanical Engineering, Carnegie Mellon University, 5000 Forbes Ave, Wean 1323, Pittsburgh, PA 15217, United States of America.,Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, 15217, United States of America.,Center for Neural Basis of Cognition, Pittsburgh, PA, 15217, United States of America.,Neuroscience Institute, Carnegie Mellon University, 5000 Forbes Ave, Wean 1323, Pittsburgh, PA 15217, United States of America
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23
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Horn CC, Wong L, Shepard BS, Gourash WF, McLaughlin BL, Fisher LE, Ahmed BH. Surgical placement of customized abdominal vagus nerve stimulating and gastrointestinal serosal surface recording electrodes. J Surg Case Rep 2021; 2021:rjab463. [PMID: 34703575 PMCID: PMC8536206 DOI: 10.1093/jscr/rjab463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 09/24/2021] [Indexed: 11/12/2022] Open
Abstract
Bioelectronic medical approaches to control vagus nerve-to-organ signaling have the potential to treat cardiac, respiratory, gastrointestinal (GI) and metabolic diseases, such as obesity. Unlike cervical vagus nerve stimulation (VNS), abdominal VNS could provide specific therapeutic control of the GI tract without off-target effects on thoracic organs; however, surgical approaches for abdominal VNS electrode placement are not well established. Moreover, optimal device configurations and additional placement of GI recording electrodes for closed-loop control are largely unknown. We designed VNS cuff and GI planar serosal electrodes and tested placement of these devices in laparoscopic surgery in two cadavers. We determined that electrode positioning on the ventral abdominal vagus nerve and gastric antrum was feasible but other sites, such as the duodenum and proximal stomach, were more difficult. The current investigation can guide potential placement and design of VNS cuff and GI electrodes for development of closed-loop GI therapeutic devices.
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Affiliation(s)
- Charles C Horn
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | | | - Brook S Shepard
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - William F Gourash
- Department of Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | | | - Lee E Fisher
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Bestoun H Ahmed
- Department of Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA
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24
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Dalrymple AN, Ting JE, Bose R, Nieuwoudt S, Franke M, Ludwig KA, Shoffstall AJ, Fisher LE, Weber DJ. Recruitment of Primary Afferents by Dorsal Root Ganglion Stimulation using the Injectrode. Int IEEE EMBS Conf Neural Eng 2021; 2021:609-612. [PMID: 34630868 DOI: 10.1109/ner49283.2021.9441420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Chronic pain affects millions of people in the United States and pharmacological treatments have been ineffective. Dorsal root ganglion (DRG) stimulation is a neuromodulation method that delivers electrical stimulation to the DRG to relieve pain. DRG electrodes are rigid and cylindrical. The implantation of DRG electrodes requires a technically-challenging surgery that involves steering electrodes laterally towards the DRG. The Injectrode is an injectable conductive polymer that cures in place and is capable of delivering electrical current to stimulate neural tissue. We used the Injectrode to stimulate the L6 and L7 DRG in cats, measuring neural responses evoked in the sciatic, tibial, and common peroneal nerves to measure the thresholds for activating fibers. A cylindrical stainless-steel electrode was used for comparison. Thresholds were 38% higher with the Injectrode versus stainless-steel, likely owing to its larger contact surface area with the DRG. Both Aα and Aβ sensory fibers were activated using DRG stimulation. The Injectrode has the potential to offer a new and simple method for DRG stimulation that can potentially offer more complete coverage of the DRG.
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Affiliation(s)
- Ashley N Dalrymple
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Jordyn E Ting
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
| | - Rohit Bose
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
| | | | | | | | | | - Lee E Fisher
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
| | - Douglas J Weber
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
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25
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Beethe AZ, Ahamed NU, Connaboy C, Lovalekar M, Fisher LE, Nindl BC, Flanagan SD. Differences in compound muscle activation patterns explain upper extremity bilateral deficits. Hum Mov Sci 2021; 79:102851. [PMID: 34333306 DOI: 10.1016/j.humov.2021.102851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 06/20/2021] [Accepted: 07/21/2021] [Indexed: 10/20/2022]
Affiliation(s)
- Anne Z Beethe
- Neuromuscular Research Laboratory and Warrior Human Performance Research Center, Department of Sports Medicine and Nutrition, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, United States of America; Perception Action Laboratory, Department of Kinesiology and Health Science, Utah State University, Logan, UT, United States of America.
| | - Nizam U Ahamed
- Neuromuscular Research Laboratory and Warrior Human Performance Research Center, Department of Sports Medicine and Nutrition, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Christopher Connaboy
- Neuromuscular Research Laboratory and Warrior Human Performance Research Center, Department of Sports Medicine and Nutrition, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Mita Lovalekar
- Neuromuscular Research Laboratory and Warrior Human Performance Research Center, Department of Sports Medicine and Nutrition, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Lee E Fisher
- Rehab Neural Engineering Laboratories, Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Bradley C Nindl
- Neuromuscular Research Laboratory and Warrior Human Performance Research Center, Department of Sports Medicine and Nutrition, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Shawn D Flanagan
- Neuromuscular Research Laboratory and Warrior Human Performance Research Center, Department of Sports Medicine and Nutrition, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, United States of America
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26
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Chandrasekaran S, Nanivadekar AC, McKernan G, Helm ER, Boninger ML, Collinger J, Gaunt R, Fisher LE. Correction: Sensory restoration by epidural stimulation of the lateral spinal cord in upper-limb amputees. eLife 2021; 10:72438. [PMID: 34309510 PMCID: PMC8313228 DOI: 10.7554/elife.72438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
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27
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Shulgach JA, Beam DW, Nanivadekar AC, Miller DM, Fulton S, Sciullo M, Ogren J, Wong L, McLaughlin BL, Yates BJ, Horn CC, Fisher LE. Selective stimulation of the ferret abdominal vagus nerve with multi-contact nerve cuff electrodes. Sci Rep 2021; 11:12925. [PMID: 34155231 PMCID: PMC8217223 DOI: 10.1038/s41598-021-91900-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 06/01/2021] [Indexed: 12/14/2022] Open
Abstract
Dysfunction and diseases of the gastrointestinal (GI) tract are a major driver of medical care. The vagus nerve innervates and controls multiple organs of the GI tract and vagus nerve stimulation (VNS) could provide a means for affecting GI function and treating disease. However, the vagus nerve also innervates many other organs throughout the body, and off-target effects of VNS could cause major side effects such as changes in blood pressure. In this study, we aimed to achieve selective stimulation of populations of vagal afferents using a multi-contact cuff electrode wrapped around the abdominal trunks of the vagus nerve. Four-contact nerve cuff electrodes were implanted around the dorsal (N = 3) or ventral (N = 3) abdominal vagus nerve in six ferrets, and the response to stimulation was measured via a 32-channel microelectrode array (MEA) inserted into the left or right nodose ganglion. Selectivity was characterized by the ability to evoke responses in MEA channels through one bipolar pair of cuff contacts but not through the other bipolar pair. We demonstrated that it was possible to selectively activate subpopulations of vagal neurons using abdominal VNS. Additionally, we quantified the conduction velocity of evoked responses to determine what types of nerve fibers (i.e., Aδ vs. C) responded to stimulation. We also quantified the spatial organization of evoked responses in the nodose MEA to determine if there is somatotopic organization of the neurons in that ganglion. Finally, we demonstrated in a separate set of three ferrets that stimulation of the abdominal vagus via a four-contact cuff could selectively alter gastric myoelectric activity, suggesting that abdominal VNS can potentially be used to control GI function.
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Affiliation(s)
- Jonathan A Shulgach
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, 15213, USA.,Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Dylan W Beam
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, 15213, USA.,Center for Neural Basis of Cognition, Pittsburgh, PA, 15213, USA
| | - Ameya C Nanivadekar
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, 15213, USA.,Center for Neural Basis of Cognition, Pittsburgh, PA, 15213, USA
| | - Derek M Miller
- Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Stephanie Fulton
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Michael Sciullo
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - John Ogren
- Micro-Leads Inc., Somerville, MA, 02144, USA
| | - Liane Wong
- Micro-Leads Inc., Somerville, MA, 02144, USA
| | | | - Bill J Yates
- Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA, 15213, USA.,Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA, 15213, USA.,Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Charles C Horn
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, 15213, USA.,Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, 15213, USA.,Department of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA.,Department of Anesthesiology, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Lee E Fisher
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, 15213, USA. .,Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, 15213, USA. .,Center for Neural Basis of Cognition, Pittsburgh, PA, 15213, USA. .,Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, 15213, USA.
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28
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Horn CC, Forssell M, Sciullo M, Harms JE, Fulton S, Mou C, Sun F, Simpson TW, Xiao G, Fisher LE, Bettinger C, Fedder GK. Hydrogel-based electrodes for selective cervical vagus nerve stimulation. J Neural Eng 2021; 18. [PMID: 33784636 DOI: 10.1088/1741-2552/abf398] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2020] [Accepted: 03/30/2021] [Indexed: 11/11/2022]
Abstract
Objective.Electrical vagus nerve stimulation (VNS) has the potential to treat a wide variety of diseases by modulating afferent and efferent communication to the heart, lungs, esophagus, stomach, and intestines. Although distal vagal nerve branches, close to end organs, could provide a selective therapeutic approach, these locations are often surgically inaccessible. In contrast, the cervical vagus nerve has been targeted for decades using surgically implantable helix electrodes to treat epileptic seizures and depression; however, to date, clinical implementation of VNS has relied on an electrode with contacts that fully wrap around the nerve, producing non-selective activation of the entire nerve. Here we demonstrate selective cervical VNS using cuff electrodes with multiple contacts around the nerve circumference to target different functional pathways.Approach.These flexible probes were adjusted to the diameter of the nerve using an adhesive hydrogel wrap to create a robust electrode interface. Our approach was verified in a rat model by demonstrating that cervical VNS produces neural activity in the abdominal vagus nerve while limiting effects on the cardiovascular system (i.e. changes in heart rate or blood pressure).Main results.This study demonstrates the potential for selective cervical VNS as a therapeutic approach for modulating distal nerve branches while reducing off target effects.Significance.This methodology could potentially be refined to treat gastrointestinal, metabolic, inflammatory, cardiovascular, and respiratory diseases amenable to vagal neuromodulatory control.
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Affiliation(s)
- Charles C Horn
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America.,UPMC Hillman Cancer Center, Pittsburgh, PA, United States of America.,Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Mats Forssell
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, United States of America
| | - Michael Sciullo
- UPMC Hillman Cancer Center, Pittsburgh, PA, United States of America
| | - Jonathan E Harms
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America.,UPMC Hillman Cancer Center, Pittsburgh, PA, United States of America
| | - Stephanie Fulton
- UPMC Hillman Cancer Center, Pittsburgh, PA, United States of America
| | - Chenchen Mou
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States of America
| | - Fan Sun
- UPMC Hillman Cancer Center, Pittsburgh, PA, United States of America.,Department of Microbiology and Molecular Genetics, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Tyler W Simpson
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Gutian Xiao
- UPMC Hillman Cancer Center, Pittsburgh, PA, United States of America.,Department of Microbiology and Molecular Genetics, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Lee E Fisher
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, United States of America.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Christopher Bettinger
- Department of Material Science and Engineering, Carnegie Mellon University, Pittsburgh, PA, United States of America
| | - Gary K Fedder
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, United States of America
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29
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Sobinov A, Boots MT, Gritsenko V, Fisher LE, Gaunt RA, Yakovenko S. Approximating complex musculoskeletal biomechanics using multidimensional autogenerating polynomials. PLoS Comput Biol 2020; 16:e1008350. [PMID: 33326417 PMCID: PMC7773415 DOI: 10.1371/journal.pcbi.1008350] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 12/30/2020] [Accepted: 09/17/2020] [Indexed: 11/23/2022] Open
Abstract
Computational models of the musculoskeletal system are scientific tools used to study human movement, quantify the effects of injury and disease, plan surgical interventions, or control realistic high-dimensional articulated prosthetic limbs. If the models are sufficiently accurate, they may embed complex relationships within the sensorimotor system. These potential benefits are limited by the challenge of implementing fast and accurate musculoskeletal computations. A typical hand muscle spans over 3 degrees of freedom (DOF), wrapping over complex geometrical constraints that change its moment arms and lead to complex posture-dependent variation in torque generation. Here, we report a method to accurately and efficiently calculate musculotendon length and moment arms across all physiological postures of the forearm muscles that actuate the hand and wrist. Then, we use this model to test the hypothesis that the functional similarities of muscle actions are embedded in muscle structure. The posture dependent muscle geometry, moment arms and lengths of modeled muscles were captured using autogenerating polynomials that expanded their optimal selection of terms using information measurements. The iterative process approximated 33 musculotendon actuators, each spanning up to 6 DOFs in an 18 DOF model of the human arm and hand, defined over the full physiological range of motion. Using these polynomials, the entire forearm anatomy could be computed in <10 μs, which is far better than what is required for real-time performance, and with low errors in moment arms (below 5%) and lengths (below 0.4%). Moreover, we demonstrate that the number of elements in these autogenerating polynomials does not increase exponentially with increasing muscle complexity; complexity increases linearly instead. Dimensionality reduction using the polynomial terms alone resulted in clusters comprised of muscles with similar functions, indicating the high accuracy of approximating models. We propose that this novel method of describing musculoskeletal biomechanics might further improve the applications of detailed and scalable models to describe human movement. The community in the fields of biomechanics, neural engineering, and neuroscience has the need to understand and simulate realistic muscle actions in real-time. In biomechanics, the models of muscle structure have been of paramount importance for understanding the mechanical demands of movements. In neural engineering, the use of biomimetic control schemes require realistic and real-time computations with low latencies to achieve an intuitive interface with high-dimensional active prostheses or orthoses. In neuroscience, the new realization of the close relationship between neural computations and body mechanics has been promoted under the concept of neuromechanics. This concept has been instrumental in the understanding of neural computations for movement planning and execution. To enable the theoretical framework of neuromechanical computations embedded within musculoskeletal organization we propose a novel method for calculating muscle biomechanics in real-time with objective approximations that embed structural and functional attributes of simulated muscles. This description offers a scalable solution that accurately computes muscle kinematic states with real-time latencies surpassing the previous results by an order of magnitude.
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Affiliation(s)
- Anton Sobinov
- Rockefeller Neuroscience Institute, School of Medicine, West Virginia University, Morgantown, WV, United States of America
- Department of Neuroscience, School of Medicine, West Virginia University, Morgantown, West Virginia, United States of America
| | - Matthew T. Boots
- Rockefeller Neuroscience Institute, School of Medicine, West Virginia University, Morgantown, WV, United States of America
- Department of Mechanical and Aerospace Engineering, Benjamin M. Statler College of Engineering and Mineral Resources, West Virginia University, Morgantown, WV, United States of America
| | - Valeriya Gritsenko
- Rockefeller Neuroscience Institute, School of Medicine, West Virginia University, Morgantown, WV, United States of America
- Department of Neuroscience, School of Medicine, West Virginia University, Morgantown, West Virginia, United States of America
- Department of Mechanical and Aerospace Engineering, Benjamin M. Statler College of Engineering and Mineral Resources, West Virginia University, Morgantown, WV, United States of America
- Department of Human Performance, School of Medicine, West Virginia University, Morgantown, WV, United States of America
| | - Lee E. Fisher
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, United States of America
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America
- Center for the Neural Basis of Cognition, Pittsburgh, PA, United States of America
| | - Robert A. Gaunt
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, United States of America
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Sergiy Yakovenko
- Rockefeller Neuroscience Institute, School of Medicine, West Virginia University, Morgantown, WV, United States of America
- Department of Neuroscience, School of Medicine, West Virginia University, Morgantown, West Virginia, United States of America
- Department of Mechanical and Aerospace Engineering, Benjamin M. Statler College of Engineering and Mineral Resources, West Virginia University, Morgantown, WV, United States of America
- Department of Human Performance, School of Medicine, West Virginia University, Morgantown, WV, United States of America
- * E-mail:
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Chandrasekaran S, Nanivadekar AC, McKernan G, Helm ER, Boninger ML, Collinger JL, Gaunt RA, Fisher LE. Sensory restoration by epidural stimulation of the lateral spinal cord in upper-limb amputees. eLife 2020; 9:54349. [PMID: 32691733 PMCID: PMC7373432 DOI: 10.7554/elife.54349] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Accepted: 06/21/2020] [Indexed: 12/14/2022] Open
Abstract
Restoring somatosensory feedback to people with limb amputations is crucial to improve prosthetic control. Multiple studies have demonstrated that peripheral nerve stimulation and targeted reinnervation can provide somatotopically relevant sensory feedback. While effective, the surgical procedures required for these techniques remain a major barrier to translatability. Here, we demonstrate in four people with upper-limb amputation that epidural spinal cord stimulation (SCS), a common clinical technique to treat pain, evoked somatosensory percepts that were perceived as emanating from the missing arm and hand. Over up to 29 days, stimulation evoked sensory percepts in consistent locations in the missing hand regardless of time since amputation or level of amputation. Evoked sensations were occasionally described as naturalistic (e.g. touch or pressure), but were often paresthesias. Increasing stimulus amplitude increased the perceived intensity linearly, without increasing area of the sensations. These results demonstrate the potential of SCS as a tool to restore somatosensation after amputations. Even some of the most advanced prosthetic arms lack an important feature: the ability to relay information about touch or pressure to the wearer. In fact, many people prefer to use simpler prostheses whose cables and harnesses pass on information about tension. However, recent studies suggest that electrical stimulation might give prosthesis users more sensation and better control. After an amputation, the nerves that used to deliver sensory information from the hand still exist above the injury. Stimulating these nerves can help to recreate sensations in the missing limb and improve the control of the prosthesis. Still, this stimulation requires complicated surgical interventions to implant electrodes in or around the nerves. Spinal cord stimulation – a technique where a small electrical device is inserted near the spinal cord to stimulate nerves – may be an easier alternative. This approach only requires a simple outpatient procedure, and it is routinely used to treat chronic pain conditions. Now, Chandrasekaran, Nanivadekar et al. show that spinal cord stimulation can produce the feeling of sensations in a person’s missing hand or arm. In the experiments, four people who had an arm amputation underwent spinal cord stimulation over 29 days. During the stimulation, the participants reported feeling electrical buzzing, vibration, or pressure in their missing limb. Changing the strength of the electric signals delivered to the spinal cord altered the intensity of these sensations. The experiments are a step toward developing better prosthetics that restore some sensation. Further studies are now needed to determine whether spinal cord stimulation would allow people to perform sensory tasks with a prosthetic, for example handling an object that they cannot see.
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Affiliation(s)
- Santosh Chandrasekaran
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, United States.,Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, United States.,Center for Neural Basis of Cognition, Pittsburgh, United States
| | - Ameya C Nanivadekar
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, United States.,Center for Neural Basis of Cognition, Pittsburgh, United States.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, United States
| | - Gina McKernan
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, United States.,Human Engineering Research Labs, VA Center of Excellence, Department of Veteran Affairs, Pittsburgh, United States
| | - Eric R Helm
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, United States
| | - Michael L Boninger
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, United States.,Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, United States.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, United States.,Human Engineering Research Labs, VA Center of Excellence, Department of Veteran Affairs, Pittsburgh, United States.,University of Pittsburgh Clinical Translational Science Institute, Pittsburgh, United States
| | - Jennifer L Collinger
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, United States.,Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, United States.,Center for Neural Basis of Cognition, Pittsburgh, United States.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, United States.,Human Engineering Research Labs, VA Center of Excellence, Department of Veteran Affairs, Pittsburgh, United States
| | - Robert A Gaunt
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, United States.,Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, United States.,Center for Neural Basis of Cognition, Pittsburgh, United States.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, United States
| | - Lee E Fisher
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, United States.,Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, United States.,Center for Neural Basis of Cognition, Pittsburgh, United States.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, United States
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31
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Kolarcik CL, Castro CA, Lesniak A, Demetris AJ, Fisher LE, Gaunt RA, Weber DJ, Cui XT. Host tissue response to floating microelectrode arrays chronically implanted in the feline spinal nerve. J Neural Eng 2020; 17:046012. [PMID: 32434161 DOI: 10.1088/1741-2552/ab94d7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
OBJECTIVE Neural interfacing technologies could significantly improve quality of life for people living with the loss of a limb. Both motor commands and sensory feedback must be considered; these complementary systems are segregated from one another in the spinal nerve. APPROACH The dorsal root ganglion-ventral root (DRG-VR) complex was targeted chronically with floating microelectrode arrays designed to record from motor neuron axons in the VR or stimulate sensory neurons in the DRG. Hematoxylin and eosin and Nissl/Luxol fast blue staining were performed. Characterization of the tissue response in regions of interest and pixel-based image analyses were used to quantify MAC387 (monocytes/macrophages), NF200 (axons), S100 (Schwann cells), vimentin (fibroblasts, endothelial cells, astrocytes), and GLUT1 (glucose transport proteins) reactivity. Implanted roots were compared to non-implanted roots and differences between the VR and DRG examined. MAIN RESULTS The tissue response associated with chronic array implantation in this peripheral location is similar to that observed in central nervous system locations. Markers of inflammation were increased in implanted roots relative to control roots with MAC387 positive cells distributed throughout the region corresponding to the device footprint. Significant decreases in neuronal density and myelination were observed in both the VR, which contains only neuronal axons, and the DRG, which contains both neuronal axons and cell bodies. Notably, decreases in NF200 in the VR were observed only at implant times less than ten weeks. Observations related to the blood-nerve barrier and tissue integrity suggest that tissue remodeling occurs, particularly in the VR. SIGNIFICANCE This study was designed to assess the viability of the DRG-VR complex as a site for neural interfacing applications and suggests that continued efforts to mitigate the tissue response will be critical to achieve the overall goal of a long-term, reliable neural interface.
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Affiliation(s)
- Christi L Kolarcik
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America. Center for the Neural Basis of Cognition, University of Pittsburgh and Carnegic Mellon University, Pittsburgh, PA, United States of America. McGowan Institute for Regenerative Medicine, Pittsburgh, PA, United States of America. Systems Neuroscience Center, Pittsburgh, PA, United States of America. Live Like Lou Center for ALS Research, Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA, United States of America
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32
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Beringer CR, Mansouri M, Fisher LE, Collinger JL, Munin MC, Boninger ML, Gaunt RA. The effect of wrist posture on extrinsic finger muscle activity during single joint movements. Sci Rep 2020; 10:8377. [PMID: 32433481 PMCID: PMC7239904 DOI: 10.1038/s41598-020-65167-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2019] [Accepted: 04/26/2020] [Indexed: 11/09/2022] Open
Abstract
Wrist posture impacts the muscle lengths and moment arms of the extrinsic finger muscles that cross the wrist. As a result, the electromyographic (EMG) activity associated with digit movement at different wrist postures must also change. We sought to quantify the posture-dependence of extrinsic finger muscle activity using bipolar fine-wire electrodes inserted into the extrinsic finger muscles of able-bodied subjects during unrestricted wrist and finger movements across the entire range of motion. EMG activity of all the recorded finger muscles were significantly different (p < 0.05, ANOVA) when performing the same digit movement in five different wrist postures. Depending on the wrist posture, EMG activity changed by up to 70% in individual finger muscles for the same movement, with the highest levels of activity observed in finger extensors when the wrist was extended. Similarly, finger flexors were most active when the wrist was flexed. For the finger flexors, EMG variations with wrist posture were most prominent for index finger muscles, while the EMG activity of all finger extensor muscles were modulated in a similar way across all digits. In addition to comprehensively quantifying the effect of wrist posture on extrinsic finger EMG activity in able-bodied subjects, these results may contribute to designing control algorithms for myoelectric prosthetic hands in the future.
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Affiliation(s)
- Carl R Beringer
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, 15213, USA
| | - Misagh Mansouri
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Lee E Fisher
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, 15213, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Jennifer L Collinger
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, 15213, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Veterans Affairs, Pittsburgh, PA, 15206, USA
| | - Michael C Munin
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Michael L Boninger
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Veterans Affairs, Pittsburgh, PA, 15206, USA
- McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, 15219, USA
| | - Robert A Gaunt
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, 15213, USA.
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, 15213, USA.
- Center for the Neural Basis of Cognition, Pittsburgh, PA, 15213, USA.
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, 15213, USA.
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Shulgach JA, Nanivadekar AC, Miller D, Fulton S, Sciullo M, Ogren J, Wong L, McLaughlin B, Yates BJ, Horn CC, Fisher LE. Selective Stimulation of Vagal Pathways Using a Multi‐contact Circumferential Cuff Electrode. FASEB J 2020. [DOI: 10.1096/fasebj.2020.34.s1.09383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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34
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Gopinath C, Jantz MK, Kumar R, Nanivadekar AC, Ogren JI, Chitnis G, Wong L, McLaughlin BL, Fisher LE, Gaunt RA. SPARC: Spinal cord epidural stimulation and microstimulation of dorsal root ganglion with penetrating microelectrode arrays enables selective activation of micturition and continence reflexes. FASEB J 2020. [DOI: 10.1096/fasebj.2020.34.s1.06229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Harms JE, Miller D, Shulgach JA, Nanivadekar AC, Fulton S, Sciullo M, Fisher LE, Yates BJ, Horn CC. Gastric Distension‐induced Nodose Ganglionic Cell Responses Using a High‐throughput Multi‐electrode Array in the Ferret. FASEB J 2020. [DOI: 10.1096/fasebj.2020.34.s1.09881] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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36
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Zheng XS, Griffith AY, Chang E, Looker MJ, Fisher LE, Clapsaddle B, Cui XT. Evaluation of a conducting elastomeric composite material for intramuscular electrode application. Acta Biomater 2020; 103:81-91. [PMID: 31863910 DOI: 10.1016/j.actbio.2019.12.021] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 11/25/2019] [Accepted: 12/10/2019] [Indexed: 01/14/2023]
Abstract
Electrical stimulation of the muscle has been proven efficacious in preventing atrophy and/or reanimating paralyzed muscles. Intramuscular electrodes made from metals have significantly higher Young's Moduli than the muscle tissues, which has the potential to cause chronic inflammation and decrease device performance. Here, we present an intramuscular electrode made from an elastomeric conducting polymer composite consisting of PEDOT-PEG copolymer, silicone and carbon nanotubes (CNT) with fluorosilicone insulation. The electrode wire has a Young's modulus of 804 (±99) kPa, which better mimics the muscle tissue modulus than conventional stainless steel (SS) electrodes. Additionally, the non-metallic composition enables metal-artifact free CT and MR imaging. These soft wire (SW) electrodes present comparable electrical impedance to SS electrodes of similar geometric surface area, activate muscle at a lower threshold, and maintain stable electrical properties in vivo up to 4 weeks. Histologically, the SW electrodes elicited significantly less fibrotic encapsulation and less IBA-1 positive macrophage accumulation than the SS electrodes at one and three months. Further phenotyping the macrophages with the iNOS (pro-inflammatory) and ARG-1 (pro-healing) markers revealed significantly less presence of pro-inflammatory macrophage around SW implants at one month. By three months, there was a significant increase in pro-healing macrophages (ARG-1) around the SW implants but not around the SS implants. Furthermore, a larger number of AchR clusters closer to SW implants were found at both time points compared to SS implants. These results suggest that a softer implant encourages a more intimate and healthier electrode-tissue interface. STATEMENT OF SIGNIFICANCE: Intramuscular electrodes made from metals have significantly higher Young's Moduli than the muscle tissues, which has the potential to cause chronic inflammation and decrease device performance. Here, we present an intramuscular electrode made from an elastomeric conducting polymer composite consisting of PEDOT-PEG copolymer, silicone and carbon nanotubes with fluorosilicone insulation. This elastomeric composite results in an electrode wire with a Young's modulus mimicking that of the muscle tissue, which elicits significantly less foreign body response compared to stainless steel wires. The lack of metal in this composite also enables metal-artifact free MRI and CT imaging.
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Affiliation(s)
- X Sally Zheng
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, United States
| | - Azante Y Griffith
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, United States
| | - Emily Chang
- TDA Research Inc., Wheat Ridge, CO 80033, United States
| | | | - Lee E Fisher
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, United States; Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213, United States; Center for Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, United States
| | | | - X Tracy Cui
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, United States; Center for Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, United States; McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, United States.
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Urbin M, Liu M, Bottorff EC, Gaunt RA, Fisher LE, Weber DJ. Hindlimb motor responses evoked by microstimulation of the lumbar dorsal root ganglia during quiet standing. J Neural Eng 2019; 17:016019. [PMID: 31597128 PMCID: PMC10321059 DOI: 10.1088/1741-2552/ab4c6c] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Somatosensory afferent pathways have been a target for neural prostheses that seek to restore sensory feedback from amputated limbs and to recruit muscles paralyzed by neurological injury. These pathways supply inputs to spinal reflex circuits that are necessary for coordinating muscle activity in the lower limb. The dorsal root ganglia (DRG) is a potential site for accessing sensory neurons because DRG microstimulation selectively recruits major nerve branches of the cat hindlimb. Previous DRG microstimulation experiments have been performed in anesthetized animals, but effects on muscle recruitment and behavior in awake animals have not been examined. OBJECTIVE The objective of the current study was to measure the effects of DRG microstimulation on evoking changes in hindlimb muscle activity during quiet standing. APPROACH In this study, 32-channel penetrating microelectrode arrays were implanted chronically in the left L6 and L7 DRG of four cats. During each week of testing, one DRG electrode was selected to deliver microstimulation pulse-trains during quiet standing. Electromyographic (EMG) signals were recorded from intramuscular electrodes in ten hindlimb muscles, and ground-reaction forces (GRF) were measured under the foot of the implanted limb. MAIN RESULTS DRG Microstimulation evoked a mix of excitatory and inhibitory responses across muscles. Response rates were highest when microstimulation was applied on the L7 array, producing more excitatory than inhibitory responses. Response rates for the L6 array were lower, and the composition of responses was more evenly balanced between excitation and inhibition. On approximately one third of testing weeks, microstimulation induced a transient unloading of the hindlimb as indicated by a decrease in GRF. Reciprocal inhibition at the knee was a prevalent response pattern across testing days which contributed to the unloading force on this subset of testing weeks. SIGNIFICANCE Results show that single-channel microstimulation in the lumbar DRG evokes stereotyped patterns of muscle recruitment in awake animals, demonstrating that even limited sensory input can elicit hindlimb behavior. These findings imply that DRG microstimulation may have utility in neural prosthetic applications aimed at restoring somatosensory feedback and promoting motor function after neurological injury.
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Affiliation(s)
- M.A. Urbin
- Department of Physical Medicine & Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA, 15213
- VA Pittsburgh Healthcare System, Pittsburgh, PA, USA, 15213
| | - Monica Liu
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA, 15213
| | | | - Robert A. Gaunt
- Department of Physical Medicine & Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA, 15213
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA, 15213
| | - Lee E. Fisher
- Department of Physical Medicine & Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA, 15213
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA, 15213
| | - Douglas J. Weber
- Department of Physical Medicine & Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA, 15213
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA, 15213
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38
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King KW, Cusack WF, Nanivadekar AC, Ayers CA, Urbin MA, Gaunt RA, Fisher LE, Weber DJ. DRG microstimulation evokes postural responses in awake, standing felines. J Neural Eng 2019; 17:016014. [PMID: 31648208 PMCID: PMC9124048 DOI: 10.1088/1741-2552/ab50f4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Objective. We have demonstrated previously that microstimulation in the dorsal root ganglia (DRG) can selectively evoke activity in primary afferent neurons in anesthetized cats. This study describes the results of experiments focused on characterizing the postural effects of DRG microstimulation in awake cats during quiet standing. Approach. To understand the parameters of stimulation that can affect these postural shifts, we measured changes in ground reaction forces (GRF) while varying stimulation location and amplitude. Four animals were chronically implanted at the L6 and L7 DRG with penetrating multichannel microelectrode arrays. During each week of testing, we identified electrode channels that recruited primary afferent neurons with fast (80–120 m s−1) and medium (30–75 m s−1) conduction velocities, and selected one channel to deliver current-controlled biphasic stimulation trains during quiet standing. Main results. Postural responses were identified by changes in GRFs and were characterized based on their magnitude and latency. During DRG microstimulation, animals did not exhibit obvious signs of distress or discomfort, which could be indicative of pain or aversion to a noxious sensation. Across 56 total weeks, 13 electrode channels evoked behavioral responses, as detected by a significant change in GRF. Stimulation amplitude modulated the magnitude of the GRF responses for these 13 channels (p < 0.001). It was not possible to predict whether or not an electrode would drive a behavioral response based on information including conduction velocity, recruitment threshold, or the DRG in which it resided. Significance. The distinct and repeatable effects on the postural response to low amplitude (<40 μA) DRG microstimulation support that this technique may be an effective way to restore somatosensory feedback after neurological injuries such as amputation.
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Affiliation(s)
- Kevin W King
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, United States of America. Center for Neural Basis of Cognition, Pittsburgh, PA 15213, United States of America. Rehabilitation Neural Engineering Laboratories, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA 15213, United States of America. KWK and WFC contributed equally to this work. LEF and DJW contributed equally to this work
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Nanivadekar AC, Ayers CA, Gaunt RA, Weber DJ, Fisher LE. Selectivity of afferent microstimulation at the DRG using epineural and penetrating electrode arrays. J Neural Eng 2019; 17:016011. [PMID: 31577993 PMCID: PMC9131467 DOI: 10.1088/1741-2552/ab4a24] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
OBJECTIVE We have shown previously that microstimulation of the lumbar dorsal root ganglia (L5-L7 DRG) using penetrating microelectrodes, selectively recruits distal branches of the sciatic and femoral nerves in an acute preparation. However, a variety of challenges limit the clinical translatability of DRG microstimulation via penetrating electrodes. For clinical translation of a DRG somatosensory neural interface, electrodes placed on the epineural surface of the DRG may be a viable path forward. The goal of this study was to evaluate the recruitment properties of epineural electrodes and compare their performance with that of penetrating electrodes. Here, we compare the number of selectively recruited distal nerve branches and the threshold stimulus intensities between penetrating and epineural electrode arrays. APPROACH Antidromically propagating action potentials were recorded from multiple distal branches of the femoral and sciatic nerves in response to epineural stimulation on 11 ganglia in four cats to quantify the selectivity of DRG stimulation. Compound action potentials (CAPs) were recorded using nerve cuff electrodes implanted around up to nine distal branches of the femoral and sciatic nerve trunks. We also tested stimulation selectivity with penetrating microelectrode arrays implanted into ten ganglia in four cats. A binary search was carried out to identify the minimum stimulus intensity that evoked a response at any of the distal cuffs, as well as whether the threshold response selectively occurred in only a single distal nerve branch. MAIN RESULTS Stimulation evoked activity in just a single peripheral nerve through 67% of epineural electrodes (35/52) and through 79% of the penetrating microelectrodes (240/308). The recruitment threshold (median = 9.67 nC/phase) and dynamic range of epineural stimulation (median = 1.01 nC/phase) were significantly higher than penetrating stimulation (0.90 nC/phase and 0.36 nC/phase, respectively). However, the pattern of peripheral nerves recruited for each DRG were similar for stimulation through epineural and penetrating electrodes. SIGNIFICANCE Despite higher recruitment thresholds, epineural stimulation provides comparable selectivity and superior dynamic range to penetrating electrodes. These results suggest that it may be possible to achieve a highly selective neural interface with the DRG without penetrating the epineurium.
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Affiliation(s)
- Ameya C Nanivadekar
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, United States of America. Rehabilitation Neural Engineering Laboratories, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA 15213, United States of America. Center for Neural Basis of Cognition, Pittsburgh, PA 15213, United States of America
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Nanivadekar AC, Miller DM, Fulton S, Wong L, Ogren J, Chitnis G, McLaughlin B, Zhai S, Fisher LE, Yates BJ, Horn CC. Machine learning prediction of emesis and gastrointestinal state in ferrets. PLoS One 2019; 14:e0223279. [PMID: 31626659 PMCID: PMC6799899 DOI: 10.1371/journal.pone.0223279] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2019] [Accepted: 09/17/2019] [Indexed: 12/30/2022] Open
Abstract
Although electrogastrography (EGG) could be a critical tool in the diagnosis of patients with gastrointestinal (GI) disease, it remains under-utilized. The lack of spatial and temporal resolution using current EGG methods presents a significant roadblock to more widespread usage. Human and preclinical studies have shown that GI myoelectric electrodes can record signals containing significantly more information than can be derived from abdominal surface electrodes. The current study sought to assess the efficacy of multi-electrode arrays, surgically implanted on the serosal surface of the GI tract, from gastric fundus-to-duodenum, in recording myoelectric signals. It also examines the potential for machine learning algorithms to predict functional states, such as retching and emesis, from GI signal features. Studies were performed using ferrets, a gold standard model for emesis testing. Our results include simultaneous recordings from up to six GI recording sites in both anesthetized and chronically implanted free-moving ferrets. Testing conditions to produce different gastric states included gastric distension, intragastric infusion of emetine (a prototypical emetic agent), and feeding. Despite the observed variability in GI signals, machine learning algorithms, including k-nearest neighbors and support vector machines, were able to detect the state of the stomach with high overall accuracy (>75%). The present study is the first demonstration of machine learning algorithms to detect the physiological state of the stomach and onset of retching, which could provide a methodology to diagnose GI diseases and symptoms such as nausea and vomiting.
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Affiliation(s)
- Ameya C. Nanivadekar
- Dept. Bioengineering, Swanson School of Engineering, Univ. Pittsburgh, Pittsburgh, PA, United States of America
| | - Derek M. Miller
- Dept. Otolaryngology, Univ. Pittsburgh School of Medicine, Pittsburgh, PA, United States of America
| | - Stephanie Fulton
- UPMC Hillman Cancer Center, Univ. Pittsburgh School of Medicine, Pittsburgh, PA, United States of America
| | - Liane Wong
- Micro-Leads Inc., Somerville, MA, United States of America
| | - John Ogren
- Micro-Leads Inc., Somerville, MA, United States of America
| | - Girish Chitnis
- Micro-Leads Inc., Somerville, MA, United States of America
| | | | - Shuyan Zhai
- UPMC Hillman Cancer Center, Univ. Pittsburgh School of Medicine, Pittsburgh, PA, United States of America
| | - Lee E. Fisher
- Dept. Bioengineering, Swanson School of Engineering, Univ. Pittsburgh, Pittsburgh, PA, United States of America
- Dept. Physical Medicine and Rehabilitation, Univ. Pittsburgh School of Medicine, Pittsburgh, PA, United States of America
| | - Bill J. Yates
- Dept. Otolaryngology, Univ. Pittsburgh School of Medicine, Pittsburgh, PA, United States of America
- Dept. Neuroscience, Univ. Pittsburgh, PA, United States of America
- Center for Neuroscience, Univ. Pittsburgh, Pittsburgh, PA, United States of America
| | - Charles C. Horn
- UPMC Hillman Cancer Center, Univ. Pittsburgh School of Medicine, Pittsburgh, PA, United States of America
- Center for Neuroscience, Univ. Pittsburgh, Pittsburgh, PA, United States of America
- Dept. Medicine, Univ. Pittsburgh School of Medicine, Pittsburgh, PA, United States of America
- Dept. Anesthesiology, Univ. Pittsburgh School of Medicine, Pittsburgh, PA, United States of America
- * E-mail:
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Abstract
Autonomic nerves are attractive targets for medical therapies using electroceutical devices because of the potential for selective control and few side effects. These devices use novel materials, electrode configurations, stimulation patterns, and closed-loop control to treat heart failure, hypertension, gastrointestinal and bladder diseases, obesity/diabetes, and inflammatory disorders. Critical to progress is a mechanistic understanding of multi-level controls of target organs, disease adaptation, and impact of neuromodulation to restore organ function.
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Affiliation(s)
- Charles C Horn
- Biobehavioral Oncology Program, UPMC Hillman Cancer Center , Pittsburgh, Pennsylvania.,Department of Medicine, University of Pittsburgh School of Medicine , Pittsburgh, Pennsylvania.,Center for Neuroscience, University of Pittsburgh , Pittsburgh, Pennsylvania
| | - Jeffrey L Ardell
- University of California- Los Angeles (UCLA) Cardiac Arrhythmia Center, Los Angeles, California.,UCLA Neurocardiology Research Program of Excellence, David Geffen School of Medicine , Los Angeles, California
| | - Lee E Fisher
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh School of Medicine , Pittsburgh, Pennsylvania.,Department of Bioengineering, University of Pittsburgh , Pittsburgh, Pennsylvania
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Zheng X, Woeppel KM, Griffith AY, Chang E, Looker MJ, Fisher LE, Clapsaddle BJ, Cui XT. Soft Conducting Elastomer for Peripheral Nerve Interface. Adv Healthc Mater 2019; 8:e1801311. [PMID: 30843365 DOI: 10.1002/adhm.201801311] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2018] [Revised: 01/24/2019] [Indexed: 12/17/2022]
Abstract
State-of-the-art intraneural electrodes made from silicon or polyimide substrates have shown promise in selectively modulating efferent and afferent activity in the peripheral nervous system. However, when chronically implanted, these devices trigger a multiphase foreign body response ending in device encapsulation. The presence of encapsulation increases the distance between the electrode and the excitable tissue, which not only reduces the recordable signal amplitude but also requires increased current to activate nearby axons. Herein, this study reports a novel conducting polymer based intraneural electrode which has Young's moduli similar to that of nerve tissue. The study first describes material optimization of the soft wire conductive matrix and evaluates their mechanical and electrochemical properties. Second, the study demonstrates 3T3 cell survival when cultured with media eluted from the soft wires. Third, the study presents acute in vivo functionality for stimulation of peripheral nerves to evoke force and compound muscle action potential in a rat model. Furthermore, comprehensive histological analyses show that soft wires elicit significantly less scar tissue encapsulation, less changes to axon size, density and morphology, and reduced macrophage activation compared to polyimide implants in the sciatic nerves at 1 month postimplantation.
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Affiliation(s)
- Xin Zheng
- Department of Bioengineering, University of Pittsburgh, 3501 Fifth Ave., Pittsburgh, PA, 15213, USA
| | - Kevin M Woeppel
- Department of Bioengineering, University of Pittsburgh, 3501 Fifth Ave., Pittsburgh, PA, 15213, USA
| | - Azante Y Griffith
- Department of Bioengineering, University of Pittsburgh, 3501 Fifth Ave., Pittsburgh, PA, 15213, USA
| | - Emily Chang
- TDA Research Inc., 12345 W. 52nd Street, Wheat Ridge, CO, 80033, USA
| | - Michael J Looker
- TDA Research Inc., 12345 W. 52nd Street, Wheat Ridge, CO, 80033, USA
| | - Lee E Fisher
- Department of Physical Medicine and Rehabilitation, Department of Bioengineering, University of Pittsburgh, 3250 Fifth Ave., Pittsburgh, PA, 15213, USA
| | | | - Xinyan Tracy Cui
- Department of Bioengineering, University of Pittsburgh, 3501 Fifth Ave., Pittsburgh, PA, 15213, USA
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Kashkoush AI, Gaunt RA, Fisher LE, Bruns TM, Weber DJ. Recording single- and multi-unit neuronal action potentials from the surface of the dorsal root ganglion. Sci Rep 2019; 9:2786. [PMID: 30808921 PMCID: PMC6391375 DOI: 10.1038/s41598-019-38924-w] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2018] [Accepted: 01/03/2019] [Indexed: 12/30/2022] Open
Abstract
The dorsal root ganglia (DRG) contain cell bodies of primary afferent neurons, which are frequently studied by recording extracellularly with penetrating microelectrodes inserted into the DRG. We aimed to isolate single- and multi-unit activity from primary afferents in the lumbar DRG using non-penetrating electrode arrays and to characterize the relationship of that activity with limb position and movement. The left sixth and seventh lumbar DRG (L6-L7) were instrumented with penetrating and non-penetrating electrode arrays to record neural activity during passive hindlimb movement in 7 anesthetized cats. We found that the non-penetrating arrays could record both multi-unit and well-isolated single-unit activity from the surface of the DRG, although with smaller signal to noise ratios (SNRs) compared to penetrating electrodes. Across all recorded units, the median SNR was 1.1 for non-penetrating electrodes and 1.6 for penetrating electrodes. Although the non-penetrating arrays were not anchored to the DRG or surrounding tissues, the spike amplitudes did not change (<1% change from baseline spike amplitude) when the limb was moved passively over a limited range of motion (~20 degrees at the hip). Units of various sensory fiber types were recorded, with 20% of units identified as primary muscle spindles, 37% as secondary muscle spindles, and 24% as cutaneous afferents. Our study suggests that non-penetrating electrode arrays can record modulated single- and multi-unit neural activity of various sensory fiber types from the DRG surface.
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Affiliation(s)
- Ahmed I Kashkoush
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Robert A Gaunt
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.,Center for the Neural Basis of Cognition, Pittsburgh, Pennsylvania, United States of America
| | - Lee E Fisher
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.,Center for the Neural Basis of Cognition, Pittsburgh, Pennsylvania, United States of America
| | - Tim M Bruns
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.,Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Douglas J Weber
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America. .,Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America. .,Center for the Neural Basis of Cognition, Pittsburgh, Pennsylvania, United States of America.
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Petersen BA, Nanivadekar AC, Chandrasekaran S, Fisher LE. Phantom limb pain: peripheral neuromodulatory and neuroprosthetic approaches to treatment. Muscle Nerve 2018; 59:154-167. [DOI: 10.1002/mus.26294] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/01/2018] [Indexed: 12/11/2022]
Affiliation(s)
- Bailey A. Petersen
- Department of Bioengineering; University of Pittsburgh; 3520 Fifth Avenue, Pittsburgh Pennsylvania 15213 USA
| | - Ameya C. Nanivadekar
- Department of Bioengineering; University of Pittsburgh; 3520 Fifth Avenue, Pittsburgh Pennsylvania 15213 USA
| | - Santosh Chandrasekaran
- Department of Physical Medicine and Rehabilitation; University of Pittsburgh; Pittsburgh Pennsylvania USA
| | - Lee E. Fisher
- Department of Bioengineering; University of Pittsburgh; 3520 Fifth Avenue, Pittsburgh Pennsylvania 15213 USA
- Department of Physical Medicine and Rehabilitation; University of Pittsburgh; Pittsburgh Pennsylvania USA
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Ayers CA, Fisher LE, Gaunt RA, Weber DJ. Microstimulation of the lumbar DRG recruits primary afferent neurons in localized regions of lower limb. J Neurophysiol 2016; 116:51-60. [PMID: 27052583 DOI: 10.1152/jn.00961.2015] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2015] [Accepted: 03/31/2016] [Indexed: 11/22/2022] Open
Abstract
Patterned microstimulation of the dorsal root ganglion (DRG) has been proposed as a method for delivering tactile and proprioceptive feedback to amputees. Previous studies demonstrated that large- and medium-diameter afferent neurons could be recruited separately, even several months after implantation. However, those studies did not examine the anatomical localization of sensory fibers recruited by microstimulation in the DRG. Achieving precise recruitment with respect to both modality and receptive field locations will likely be crucial to create a viable sensory neuroprosthesis. In this study, penetrating microelectrode arrays were implanted in the L5, L6, and L7 DRG of four isoflurane-anesthetized cats instrumented with nerve cuff electrodes around the proximal and distal branches of the sciatic and femoral nerves. A binary search was used to find the recruitment threshold for evoking a response in each nerve cuff. The selectivity of DRG stimulation was characterized by the ability to recruit individual distal branches to the exclusion of all others at threshold; 84.7% (n = 201) of the stimulation electrodes recruited a single nerve branch, with 9 of the 15 instrumented nerves recruited selectively. The median stimulation threshold was 0.68 nC/phase, and the median dynamic range (increase in charge while stimulation remained selective) was 0.36 nC/phase. These results demonstrate the ability of DRG microstimulation to achieve selective recruitment of the major nerve branches of the hindlimb, suggesting that this approach could be used to drive sensory input from localized regions of the limb. This sensory input might be useful for restoring tactile and proprioceptive feedback to a lower-limb amputee.
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Affiliation(s)
- Christopher A Ayers
- Center for Neural Basis of Cognition, Pittsburgh, Pennsylvania; Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania; and
| | - Lee E Fisher
- Center for Neural Basis of Cognition, Pittsburgh, Pennsylvania; Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania; and Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Robert A Gaunt
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania; and Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Douglas J Weber
- Center for Neural Basis of Cognition, Pittsburgh, Pennsylvania; Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania; and Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, Pennsylvania
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Fisher LE, Lynch KA, Fernandes PA, Bekkeng TA, Moen J, Zettergren M, Miceli RJ, Powell S, Lessard MR, Horak P. Including sheath effects in the interpretation of planar retarding potential analyzer's low-energy ion data. Rev Sci Instrum 2016; 87:043504. [PMID: 27131671 DOI: 10.1063/1.4944416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
The interpretation of planar retarding potential analyzers (RPA) during ionospheric sounding rocket missions requires modeling the thick 3D plasma sheath. This paper overviews the theory of RPAs with an emphasis placed on the impact of the sheath on current-voltage (I-V) curves. It then describes the Petite Ion Probe (PIP) which has been designed to function in this difficult regime. The data analysis procedure for this instrument is discussed in detail. Data analysis begins by modeling the sheath with the Spacecraft Plasma Interaction System (SPIS), a particle-in-cell code. Test particles are traced through the sheath and detector to determine the detector's response. A training set is constructed from these simulated curves for a support vector regression analysis which relates the properties of the I-V curve to the properties of the plasma. The first in situ use of the PIPs occurred during the MICA sounding rocket mission which launched from Poker Flat, Alaska in February of 2012. These data are presented as a case study, providing valuable cross-instrument comparisons. A heritage top-hat thermal ion electrostatic analyzer, called the HT, and a multi-needle Langmuir probe have been used to validate both the PIPs and the data analysis method. Compared to the HT, the PIP ion temperature measurements agree with a root-mean-square error of 0.023 eV. These two instruments agree on the parallel-to-B plasma flow velocity with a root-mean-square error of 130 m/s. The PIP with its field of view aligned perpendicular-to-B provided a density measurement with an 11% error compared to the multi-needle Langmuir Probe. Higher error in the other PIP's density measurement is likely due to simplifications in the SPIS model geometry.
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Affiliation(s)
- L E Fisher
- Department of Physics and Astronomy, Dartmouth College, Hanover, New Hampshire 03755, USA
| | - K A Lynch
- Department of Physics and Astronomy, Dartmouth College, Hanover, New Hampshire 03755, USA
| | - P A Fernandes
- Department of Physics and Astronomy, Dartmouth College, Hanover, New Hampshire 03755, USA
| | - T A Bekkeng
- Department of Physics, University of Oslo, Oslo, Norway
| | - J Moen
- Department of Physics, University of Oslo, Oslo, Norway
| | - M Zettergren
- Physical Sciences Department, Embry-Riddle Aeronautical University, Daytona Beach, Florida 32114, USA
| | - R J Miceli
- Earth and Atmospheric Sciences, Cornell University, Ithaca, New York 14850, USA
| | - S Powell
- Earth and Atmospheric Sciences, Cornell University, Ithaca, New York 14850, USA
| | - M R Lessard
- Space Science Center, University of New Hampshire, Durham, New Hampshire 03824, USA
| | - P Horak
- Department of Physics and Astronomy, Dartmouth College, Hanover, New Hampshire 03755, USA
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Sicari BM, Rubin JP, Dearth CL, Wolf MT, Ambrosio F, Boninger M, Turner NJ, Weber DJ, Simpson TW, Wyse A, Brown EHP, Dziki JL, Fisher LE, Brown S, Badylak SF. An acellular biologic scaffold promotes skeletal muscle formation in mice and humans with volumetric muscle loss. Sci Transl Med 2014; 6:234ra58. [PMID: 24786326 DOI: 10.1126/scitranslmed.3008085] [Citation(s) in RCA: 318] [Impact Index Per Article: 31.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Biologic scaffolds composed of naturally occurring extracellular matrix (ECM) can provide a microenvironmental niche that alters the default healing response toward a constructive and functional outcome. The present study showed similarities in the remodeling characteristics of xenogeneic ECM scaffolds when used as a surgical treatment for volumetric muscle loss in both a preclinical rodent model and five male patients. Porcine urinary bladder ECM scaffold implantation was associated with perivascular stem cell mobilization and accumulation within the site of injury, and de novo formation of skeletal muscle cells. The ECM-mediated constructive remodeling was associated with stimulus-responsive skeletal muscle in rodents and functional improvement in three of the five human patients.
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Affiliation(s)
- Brian M Sicari
- McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219, USA
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Debnath S, Bauman MJ, Fisher LE, Weber DJ, Gaunt RA. Microelectrode array recordings from the ventral roots in chronically implanted cats. Front Neurol 2014; 5:104. [PMID: 25071697 PMCID: PMC4083189 DOI: 10.3389/fneur.2014.00104] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2014] [Accepted: 06/07/2014] [Indexed: 11/13/2022] Open
Abstract
The ventral spinal roots contain the axons of spinal motoneurons and provide the only location in the peripheral nervous system where recorded neural activity can be assured to be motor rather than sensory. This study demonstrates recordings of single unit activity from these ventral root axons using floating microelectrode arrays (FMAs). Ventral root recordings were characterized by examining single unit yield and signal-to-noise ratios (SNR) with 32-channel FMAs implanted chronically in the L6 and L7 spinal roots of nine cats. Single unit recordings were performed for implant periods of up to 12 weeks. Motor units were identified based on active discharge during locomotion and inactivity under anesthesia. Motor unit yield and SNR were calculated for each electrode, and results were grouped by electrode site size, which were varied systematically between 25 and 160 μm to determine effects on signal quality. The unit yields and SNR did not differ significantly across this wide range of electrode sizes. Both SNR and yield decayed over time, but electrodes were able to record spikes with SNR >2 up to 12 weeks post-implant. These results demonstrate that it is feasible to record single unit activity from multiple isolated motor units with penetrating microelectrode arrays implanted chronically in the ventral spinal roots. This approach could be useful for creating a spinal nerve interface for advanced neural prostheses, and results of this study will be used to improve design of microelectrodes for chronic neural recording in the ventral spinal roots.
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Affiliation(s)
- Shubham Debnath
- Department of Bioengineering, University of Pittsburgh , Pittsburgh, PA , USA
| | - Matthew J Bauman
- Department of Bioengineering, University of Pittsburgh , Pittsburgh, PA , USA
| | - Lee E Fisher
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh , Pittsburgh, PA , USA
| | - Douglas J Weber
- Department of Bioengineering, University of Pittsburgh , Pittsburgh, PA , USA ; Department of Physical Medicine and Rehabilitation, University of Pittsburgh , Pittsburgh, PA , USA
| | - Robert A Gaunt
- Department of Bioengineering, University of Pittsburgh , Pittsburgh, PA , USA ; Department of Physical Medicine and Rehabilitation, University of Pittsburgh , Pittsburgh, PA , USA
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Fisher LE, Ayers CA, Ciollaro M, Ventura V, Weber DJ, Gaunt RA. Chronic recruitment of primary afferent neurons by microstimulation in the feline dorsal root ganglia. J Neural Eng 2014; 11:036007. [DOI: 10.1088/1741-2560/11/3/036007] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Fisher LE, Tyler DJ, Triolo RJ. Optimization of selective stimulation parameters for multi-contact electrodes. J Neuroeng Rehabil 2013; 10:25. [PMID: 23442372 PMCID: PMC3599334 DOI: 10.1186/1743-0003-10-25] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2012] [Accepted: 02/21/2013] [Indexed: 11/15/2022] Open
Abstract
Background Multi-contact stimulating electrodes are gaining acceptance as a means for interfacing with the peripheral nervous system. These electrodes can potentially activate many independent populations of motor units within a single peripheral nerve, but quantifying their recruitment properties and the overlap in stimulation between contacts is difficult and time consuming. Further, current methods for quantifying overlap between contacts are ambiguous and can lead to suboptimal selective stimulation parameters. This study describes a novel method for optimizing stimulation parameters for multi-contact peripheral stimulating electrodes to produce strong, selective muscle contractions. The method is tested with four-contact spiral nerve-cuff electrodes implanted on bilateral femoral nerves of two individuals with spinal cord injury, but it is designed to be extendable to other electrode technologies with higher densities of contacts. Methods To optimize selective stimulation parameters for multi-contact electrodes, first, recruitment and overlap are characterized for all contacts within an electrode. Recruitment is measured with the twitch response to single stimulus pulses, and overlap between pairs of contacts is quantified by the deviation in their combined response from linear addition of individual responses. Simple mathematical models are fit to recruitment and overlap data, and a cost function is defined to maximize recruitment and minimize overlap between all contacts. Results Results are presented for four-contact nerve-cuff electrodes stimulating bilateral femoral nerves of two human subjects with spinal cord injury. Knee extension moments between 11.6 and 43.2 Nm were achieved with selective stimulation through multiple contacts of each nerve-cuff with less than 10% overlap between pairs of contacts. The overlap in stimulation measured in response to selective stimulation parameters was stable at multiple repeated time points after implantation. Conclusions These results suggest that the method described here can provide an automated means of determining stimulus parameters to achieve strong muscle contractions via selective stimulation through multi-contact peripheral nerve electrodes.
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Affiliation(s)
- Lee E Fisher
- Case Western Reserve University, Cleveland, OH 44106, USA.
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