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Mirkiani S, O'Sullivan CL, Roszko DA, Faridi P, Hu DS, Everaert DG, Toossi A, Kang R, Fang T, Tyreman N, Dalrymple AN, Robinson K, Uwiera RRE, Shah H, Fox R, Konrad PE, Mushahwar VK. Safety of mapping the motor networks in the spinal cord using penetrating microelectrodes in Yucatan minipigs. J Neurosurg Spine 2024:1-13. [PMID: 38728765 DOI: 10.3171/2024.2.spine23757] [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] [Received: 07/08/2023] [Accepted: 02/21/2024] [Indexed: 05/12/2024]
Abstract
OBJECTIVE The goal of this study was to assess the safety of mapping spinal cord locomotor networks using penetrating stimulation microelectrodes in Yucatan minipigs (YMPs) as a clinically translational animal model. METHODS Eleven YMPs were trained to walk up and down a straight line. Motion capture was performed, and electromyographic (EMG) activity of hindlimb muscles was recorded during overground walking. The YMPs underwent a laminectomy and durotomy to expose the lumbar spinal cord. Using an ultrasound-guided stereotaxic frame, microelectrodes were inserted into the spinal cord in 8 animals. Pial cuts were made to prevent tissue dimpling before microelectrode insertion. Different locations within the lumbar enlargement were electrically stimulated to map the locomotor networks. The remaining 3 YMPs served as sham controls, receiving the laminectomy, durotomy, and pial cuts but not microelectrode insertion. The Porcine Thoracic Injury Behavioral Scale (PTIBS) and hindlimb reflex assessment results were recorded for 4 weeks postoperatively. Overground gait kinematics and hindlimb EMG activity were recorded again at weeks 3 and 4 postoperatively and compared with preoperative measures. The animals were euthanized at the end of week 4, and the lumbar spinal cords were extracted and preserved for immunohistochemical analysis. RESULTS All YMPs showed transient deficits in hindlimb function postoperatively. Except for 1 YMP in the experimental group, all animals regained normal ambulation and balance (PTIBS score 10) at the end of weeks 3 and 4. One animal in the experimental group showed gait and balance deficits by week 4 (PTIBS score 4). This animal was excluded from the kinematics and EMG analyses. Overground gait kinematic measures and EMG activity showed no significant (p > 0.05) differences between preoperative and postoperative values, and between the experimental and sham groups. Less than 5% of electrode tracks were visible in the tissue analysis of the animals in the experimental group. There was no statistically significant difference in damage caused by pial cuts between the experimental and sham groups. Tissue damage due to the pial cuts was more frequently observed in immunohistochemical analyses than microelectrode tracks. CONCLUSIONS These findings suggest that mapping spinal locomotor networks in porcine models can be performed safely, without lasting damage to the spinal cord.
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Affiliation(s)
- Soroush Mirkiani
- 1Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Alberta, Canada
- 2Institute for Augmentative and Restorative Technologies and Health Innovations (iSMART), University of Alberta, Edmonton, Alberta, Canada
| | - Carly L O'Sullivan
- 1Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Alberta, Canada
- 2Institute for Augmentative and Restorative Technologies and Health Innovations (iSMART), University of Alberta, Edmonton, Alberta, Canada
| | - David A Roszko
- 2Institute for Augmentative and Restorative Technologies and Health Innovations (iSMART), University of Alberta, Edmonton, Alberta, Canada
- 3Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, Ontario, Canada
| | - Pouria Faridi
- 1Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Alberta, Canada
- 2Institute for Augmentative and Restorative Technologies and Health Innovations (iSMART), University of Alberta, Edmonton, Alberta, Canada
| | - David S Hu
- 2Institute for Augmentative and Restorative Technologies and Health Innovations (iSMART), University of Alberta, Edmonton, Alberta, Canada
- 4Division of Physical Medicine and Rehabilitation, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada
| | - Dirk G Everaert
- 2Institute for Augmentative and Restorative Technologies and Health Innovations (iSMART), University of Alberta, Edmonton, Alberta, Canada
- 4Division of Physical Medicine and Rehabilitation, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada
| | - Amirali Toossi
- 1Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Alberta, Canada
- 2Institute for Augmentative and Restorative Technologies and Health Innovations (iSMART), University of Alberta, Edmonton, Alberta, Canada
- 4Division of Physical Medicine and Rehabilitation, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada
| | - Ryan Kang
- 2Institute for Augmentative and Restorative Technologies and Health Innovations (iSMART), University of Alberta, Edmonton, Alberta, Canada
| | - Tongzhou Fang
- 2Institute for Augmentative and Restorative Technologies and Health Innovations (iSMART), University of Alberta, Edmonton, Alberta, Canada
| | - Neil Tyreman
- 2Institute for Augmentative and Restorative Technologies and Health Innovations (iSMART), University of Alberta, Edmonton, Alberta, Canada
- 4Division of Physical Medicine and Rehabilitation, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada
| | - Ashley N Dalrymple
- 1Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Alberta, Canada
- 2Institute for Augmentative and Restorative Technologies and Health Innovations (iSMART), University of Alberta, Edmonton, Alberta, Canada
- 5Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania
| | - Kevin Robinson
- 6School of Physical Therapy, Belmont University, Nashville, Tennessee
| | - Richard R E Uwiera
- 2Institute for Augmentative and Restorative Technologies and Health Innovations (iSMART), University of Alberta, Edmonton, Alberta, Canada
- 7Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Alberta, Canada
| | - Hamid Shah
- 8Vanderbilt University Medical Center, Nashville, Tennessee
| | - Richard Fox
- 2Institute for Augmentative and Restorative Technologies and Health Innovations (iSMART), University of Alberta, Edmonton, Alberta, Canada
- 9Division of Neurosurgery, Department of Surgery, University of Alberta, Edmonton, Alberta, Canada
| | - Peter E Konrad
- 10Department of Neurosurgery, West Virginia University, Morgantown, West Virginia; and
- 11Integrative Neuroscience & Clinical Innovation, Rockefeller Neuroscience Institute, Morgantown, West Virginia
| | - Vivian K Mushahwar
- 1Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Alberta, Canada
- 2Institute for Augmentative and Restorative Technologies and Health Innovations (iSMART), University of Alberta, Edmonton, Alberta, Canada
- 4Division of Physical Medicine and Rehabilitation, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada
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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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3
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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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4
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Nair V, Dalrymple AN, Yu Z, Balakrishnan G, Bettinger CJ, Weber DJ, Yang K, Robinson JT. Miniature battery-free bioelectronics. Science 2023; 382:eabn4732. [PMID: 37943926 DOI: 10.1126/science.abn4732] [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] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 09/28/2023] [Indexed: 11/12/2023]
Abstract
Miniature wireless bioelectronic implants that can operate for extended periods of time can transform how we treat disorders by acting rapidly on precise nerves and organs in a way that drugs cannot. To reach this goal, materials and methods are needed to wirelessly transfer energy through the body or harvest energy from the body itself. We review some of the capabilities of emerging energy transfer methods to identify the performance envelope for existing technology and discover where opportunities lie to improve how much-and how efficiently-we can deliver energy to the tiny bioelectronic implants that can support emerging medical technologies.
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Affiliation(s)
- Vishnu Nair
- Rice Neuroengineering Initiative, Rice University, Houston, TX, USA
| | - Ashley N Dalrymple
- 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
| | - Zhanghao Yu
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA
| | - Gaurav Balakrishnan
- Department of Materials Science & Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Christopher J Bettinger
- Department of Materials Science & Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Douglas J Weber
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Center for Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Kaiyuan Yang
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA
| | - Jacob T Robinson
- Rice Neuroengineering Initiative, Rice University, Houston, TX, USA
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA
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5
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Refy O, Blanchard B, Miller-Peterson A, Dalrymple AN, Bedoy EH, Zaripova A, Motaghedi N, Mo O, Panthangi S, Reinhart A, Torres-Oviedo G, Geyer H, Weber DJ. Dynamic spinal reflex adaptation during locomotor adaptation. J Neurophysiol 2023; 130:1008-1014. [PMID: 37701940 DOI: 10.1152/jn.00248.2023] [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: 06/23/2023] [Revised: 09/01/2023] [Accepted: 09/01/2023] [Indexed: 09/14/2023] Open
Abstract
The dynamics and interaction of spinal and supraspinal centers during locomotor adaptation remain vaguely understood. In this work, we use Hoffmann reflex measurements to investigate changes in spinal reflex gains during split-belt locomotor adaptation. We show that spinal reflex gains are dynamically modulated during split-belt locomotor adaptation. During first exposure to split-belt transitions, modulation occurs mostly on the leg ipsilateral to the speed change and constitutes rapid suppression or facilitation of the reflex gains, followed by slow recovery to baseline. Over repeated exposure, the modulation pattern washes out. We further show that reflex gain modulation strongly correlates with correction of leg asymmetry, and cannot be explained by speed modulation solely. We argue that reflex modulation is likely of supraspinal origins and constitutes an integral part of the neural substrate underlying split-belt locomotor adaptation.NEW & NOTEWORTHY This work presents direct evidence for spinal reflex modulation during locomotor adaptation. In particular, we show that reflexes can be modulated on-demand unilaterally during split-belt locomotor adaptation and speculate about reflex modulation as an underlying mechanism for adaptation of gait asymmetry in healthy adults.
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Affiliation(s)
- Omar Refy
- Department of Physics, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
- NeuroMechatronics Lab, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
- Legged Systems Lab, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
| | - Belle Blanchard
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
| | - Abigail Miller-Peterson
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
| | - Ashley N Dalrymple
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
- NeuroMechatronics Lab, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
- Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, United States
- Department of Physical Medicine and Rehabilitation, University of Utah, Salt Lake City, Utah, United States
| | - Ernesto H Bedoy
- NeuroMechatronics Lab, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
- Center for Neuroscience, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
| | - Amelia Zaripova
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
| | - Nadim Motaghedi
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
| | - Owen Mo
- School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
| | - Shalini Panthangi
- School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
| | - Alex Reinhart
- Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
| | - Gelsy Torres-Oviedo
- Swanson School of Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
| | - Hartmut Geyer
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
- Robotics Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
- School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
- Legged Systems Lab, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
| | - Douglas J Weber
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
- NeuroMechatronics Lab, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
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Jantz MK, Mak J, Dalrymple AN, Farooqui J, Grigsby EM, Herrera AJ, Pirondini E, Collinger JL. Lifting as we climb: Experiences and recommendations from women in neural engineering. Front Neurosci 2023; 17:1104419. [PMID: 36968482 PMCID: PMC10033556 DOI: 10.3389/fnins.2023.1104419] [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] [Received: 11/21/2022] [Accepted: 02/22/2023] [Indexed: 03/11/2023] Open
Abstract
Neural engineering is an emerging and multidisciplinary field in which engineering approaches are applied to neuroscience problems. Women are underrepresented in engineering fields, and indeed in science, technology, engineering, and mathematics (STEM) fields generally. Underrepresentation of women is particularly notable at later academic career stages, suggesting that even though women are interested in the field, barriers exist that ultimately cause them to leave. Here, we investigate many of the obstacles to women's success in the field of neural engineering and provide recommendations and materials to overcome them. We conducted a review of the literature from the past 15 years regarding the experiences of women in academic careers, as well as reports on the number of women in fields closely related to neural engineering from the National Science Foundation (NSF) and the American Society for Engineering Education (ASEE). Additionally, we interviewed six women in neural engineering who are involved in initiatives and outreach concerning the inclusion and experiences of women in engineering. Throughout the literature and interviews, we identified common themes spanning the role of identity and confidence, professional relationships, career-related hurdles, and personal and professional expectations. We explore each of these themes in detail and provide resources to support the growth of women as they climb within the field of neural engineering.
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Affiliation(s)
- Maria K. Jantz
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
- Center for Neural Basis of Cognition, Pittsburgh, PA, United States
| | - Jennifer Mak
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
- Center for Neural Basis of Cognition, Pittsburgh, PA, United States
| | - Ashley N. Dalrymple
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Juhi Farooqui
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, United States
- Center for Neural Basis of Cognition, Pittsburgh, PA, United States
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Erinn M. Grigsby
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, United States
| | - Angelica J. Herrera
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
- Center for Neural Basis of Cognition, Pittsburgh, PA, United States
| | - Elvira Pirondini
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
- Center for Neural Basis of Cognition, Pittsburgh, PA, United States
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, United States
| | - Jennifer L. Collinger
- Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
- Center for Neural Basis of Cognition, Pittsburgh, PA, United States
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States
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Dalrymple AN, Hooper CA, Kuriakose MG, Capogrosso M, Weber DJ. Using a high-frequency carrier does not improve comfort of transcutaneous spinal cord stimulation. J Neural Eng 2023; 20. [PMID: 36595241 DOI: 10.1088/1741-2552/acabe8] [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] [Received: 09/14/2022] [Accepted: 12/15/2022] [Indexed: 12/23/2022]
Abstract
Objective.Spinal cord neuromodulation has gained much attention for demonstrating improved motor recovery in people with spinal cord injury, motivating the development of clinically applicable technologies. Among them, transcutaneous spinal cord stimulation (tSCS) is attractive because of its non-invasive profile. Many tSCS studies employ a high-frequency (10 kHz) carrier, which has been reported to reduce stimulation discomfort. However, these claims have come under scrutiny in recent years. The purpose of this study was to determine whether using a high-frequency carrier for tSCS is more comfortable at therapeutic amplitudes, which evoke posterior root-muscle (PRM) reflexes.Approach.In 16 neurologically intact participants, tSCS was delivered using a 1 ms long monophasic pulse with and without a high-frequency carrier. Stimulation amplitude and pulse duration were varied and PRM reflexes were recorded from the soleus, gastrocnemius, and tibialis anterior muscles. Participants rated their discomfort during stimulation from 0 to 10 at PRM reflex threshold.Main Results.At PRM reflex threshold, the addition of a high-frequency carrier (0.87 ± 0.2) was equally comfortable as conventional stimulation (1.03 ± 0.18) but required approximately double the charge to evoke the PRM reflex (conventional: 32.4 ± 9.2µC; high-frequency carrier: 62.5 ± 11.1µC). Strength-duration curves for tSCS with a high-frequency carrier had a rheobase that was 4.8× greater and a chronaxie that was 5.7× narrower than the conventional monophasic pulse, indicating that the addition of a high-frequency carrier makes stimulation less efficient in recruiting neural activity in spinal roots.Significance.Using a high-frequency carrier for tSCS is equally as comfortable and less efficient as conventional stimulation at amplitudes required to stimulate spinal dorsal roots.
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Affiliation(s)
- Ashley N Dalrymple
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States of America.,NeuroMechatronics Lab, Carnegie Mellon University, Pittsburgh, PA, United States of America
| | - Charli Ann Hooper
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States of America.,NeuroMechatronics Lab, Carnegie Mellon University, Pittsburgh, PA, United States of America.,Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States of America
| | - Minna G Kuriakose
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America.,Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Marco Capogrosso
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America.,Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, United States of America.,Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, United States of America.,Center for Neural Basis of Cognition, Pittsburgh, PA, United States of America
| | - Douglas J Weber
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States of America.,NeuroMechatronics Lab, Carnegie Mellon University, Pittsburgh, PA, United States of America.,Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, United States of America
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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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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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10
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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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11
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Affiliation(s)
- Ashley N Dalrymple
- Department of Physical Medicine and Rehabilitation Rehabilitation Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
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Shepherd RK, Carter PM, Enke YL, Thompson A, Flynn B, Trang EP, Dalrymple AN, Fallon JB. Chronic intracochlear electrical stimulation at high charge densities: reducing platinum dissolution. J Neural Eng 2020; 17:056009. [DOI: 10.1088/1741-2552/abb7a6] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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13
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Dalrymple AN, Huynh M, Nayagam BA, Lee CD, Weiland GR, Petrossians A, J J, Iii W, Fallon JB, Shepherd RK. Electrochemical and biological characterization of thin-film platinum-iridium alloy electrode coatings: a chronic in vivo study. J Neural Eng 2020; 17:036012. [PMID: 32408281 DOI: 10.1088/1741-2552/ab933d] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
OBJECTIVE To evaluate the electrochemical properties, biological response, and surface characterization of an electrodeposited Platinum-Iridium (Pt-Ir) electrode coating on cochlear implants subjected to chronic stimulation in vivo. APPROACH Electrochemical impedance spectroscopy (EIS), charge storage capacity (CSC), charge injection limit (CIL), and voltage transient (VT) impedance were measured bench-top before and after implant and in vivo. Coated Pt-Ir and uncoated Pt electrode arrays were implanted into cochlea of normal hearing rats and stimulated for ∼4 h d, 5 d week-1 for 5 weeks at levels within the normal clinical range. Neural function was monitored using electrically-evoked auditory brainstem responses. After explant, the electrode surfaces were assessed, and cochleae examined histologically. MAIN RESULTS When measured on bench-top before and after stimulation, Pt-Ir coated electrodes had significantly lower VT impedance (p < 0.001) and significantly higher CSC (p < 0.001) and CIL (p < 0.001) compared to uncoated Pt electrodes. In vivo, the CSC and CIL of Pt-Ir were significantly higher than Pt throughout the implantation period (p= 0.047 and p< 0.001, respectively); however, the VT impedance (p= 0.3) was not. There was no difference in foreign body response between material cohorts, although cochleae implanted with coated electrodes contained small deposits of Pt-Ir. There was no evidence of increased neural loss or loss of neural function in either group. Surface examination revealed no Pt corrosion on any electrodes. SIGNIFICANCE Electrodeposited Pt-Ir electrodes demonstrated significant improvements in electrochemical performance on the bench-top and in vivo compared to uncoated Pt. Neural function and tissue response to Pt-Ir electrodes were not different from uncoated Pt, despite small deposits of Pt-Ir in the tissue capsule. Electrodeposited Pt-Ir coatings offer promise as an improved electrode coating for active neural prostheses.
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Abstract
OBJECTIVE Neuromodulation technologies are increasingly used for improving function after neural injury. To achieve a symbiotic relationship between device and user, the device must augment remaining function, and independently adapt to day-to-day changes in function. The goal of this study was to develop predictive control strategies to produce over-ground walking in a model of hemisection spinal cord injury (SCI) using intraspinal microstimulation (ISMS). APPROACH Eight cats were anaesthetized and placed in a sling over a walkway. The residual function of a hemisection SCI was mimicked by manually moving one hind-limb through the walking cycle. ISMS targeted motor networks in the lumbosacral enlargement to activate muscles in the other, presumably 'paralyzed' limb, using low levels of current (<130 μA). Four people took turns to move the 'intact' limb, generating four different walking styles. Two control strategies, which used ground reaction force and angular velocity information about the manually moved 'intact' limb to control the timing of the transitions of the 'paralyzed' limb through the step cycle, were compared. The first strategy used thresholds on the raw sensor values to initiate transitions. The second strategy used reinforcement learning and Pavlovian control to learn predictions about the sensor values. Thresholds on the predictions were then used to initiate transitions. MAIN RESULTS Both control strategies were able to produce alternating, over-ground walking. Transitions based on raw sensor values required manual tuning of thresholds for each person to produce walking, whereas Pavlovian control did not. Learning occurred quickly during walking: predictions of the sensor signals were learned rapidly, initiating correct transitions after ≤4 steps. Pavlovian control was resilient to different walking styles and different cats, and recovered from induced mistakes during walking. SIGNIFICANCE This work demonstrates, for the first time, that Pavlovian control can augment remaining function and facilitate personalized walking with minimal tuning requirements.
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Affiliation(s)
- Ashley N Dalrymple
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada. Sensory Motor Adaptive Rehabilitation Technology (SMART) Network, University of Alberta, Edmonton, AB, Canada
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15
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Dalrymple AN, Robles UA, Huynh M, Nayagam BA, Green RA, Poole-Warren LA, Fallon JB, Shepherd RK. Electrochemical and biological performance of chronically stimulated conductive hydrogel electrodes. J Neural Eng 2020; 17:026018. [DOI: 10.1088/1741-2552/ab7cfc] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
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16
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Dalrymple AN, Huynh M, Robles UA, Marroquin JB, Lee CD, Petrossians A, Whalen JJ, Li D, Parkington HC, Forsythe JS, Green RA, Poole-Warren LA, Shepherd RK, Fallon JB. Electrochemical and mechanical performance of reduced graphene oxide, conductive hydrogel, and electrodeposited Pt-Ir coated electrodes: an active in vitro study. J Neural Eng 2019; 17:016015. [PMID: 31652427 DOI: 10.1088/1741-2552/ab5163] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
OBJECTIVE To systematically compare the in vitro electrochemical and mechanical properties of several electrode coatings that have been reported to increase the efficacy of medical bionics devices by increasing the amount of charge that can be delivered safely to the target neural tissue. APPROACH Smooth platinum (Pt) ring and disc electrodes were coated with reduced graphene oxide, conductive hydrogel, or electrodeposited Pt-Ir. Electrodes with coatings were compared with uncoated smooth Pt electrodes before and after an in vitro accelerated aging protocol. The various coatings were compared mechanically using the adhesion-by-tape test. Electrodes were stimulated in saline for 24 hours/day 7 days/week for 21 d at 85 °C (1.6-year equivalence) at a constant charge density of 200 µC/cm2/phase. Electrodes were graded on surface corrosion and trace analysis of Pt in the electrolyte after aging. Electrochemical measurements performed before, during, and after aging included electrochemical impedance spectroscopy, cyclic voltammetry, and charge injection limit and impedance from voltage transient recordings. MAIN RESULTS All three coatings adhered well to smooth Pt and exhibited electrochemical advantage over smooth Pt electrodes prior to aging. After aging, graphene coated electrodes displayed a stimulation-induced increase in impedance and reduction in the charge injection limit (p < 0.001), alongside extensive corrosion and release of Pt into the electrolyte. In contrast, both conductive hydrogel and Pt-Ir coated electrodes had smaller impedances and larger charge injection limits than smooth Pt electrodes (p < 0.001) following aging regardless of the stimulus level and with little evidence of corrosion or Pt dissolution. SIGNIFICANCE This study rigorously tested the mechanical and electrochemical performance of electrode coatings in vitro and provided suitable candidates for future in vivo testing.
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17
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Dalrymple AN, Sharples SA, Osachoff N, Lognon AP, Whelan PJ. A supervised machine learning approach to characterize spinal network function. J Neurophysiol 2019; 121:2001-2012. [PMID: 30943091 DOI: 10.1152/jn.00763.2018] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [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: 01/27/2023] Open
Abstract
Spontaneous activity is a common feature of immature neuronal networks throughout the central nervous system and plays an important role in network development and consolidation. In postnatal rodents, spontaneous activity in the spinal cord exhibits complex, stochastic patterns that have historically proven challenging to characterize. We developed a software tool for quickly and automatically characterizing and classifying episodes of spontaneous activity generated from developing spinal networks. We recorded spontaneous activity from in vitro lumbar ventral roots of 16 neonatal [postnatal day (P)0-P3] mice. Recordings were DC coupled and detrended, and episodes were separated for analysis. Amplitude-, duration-, and frequency-related features were extracted from each episode and organized into five classes. Paired classes and features were used to train and test supervised machine learning algorithms. Multilayer perceptrons were used to classify episodes as rhythmic or multiburst. We increased network excitability with potassium chloride and tested the utility of the tool to detect changes in features and episode class. We also demonstrate usability by having a novel experimenter use the program to classify episodes collected at a later time point (P5). Supervised machine learning-based classification of episodes accounted for changes that traditional approaches cannot detect. Our tool, named SpontaneousClassification, advances the detail in which we can study not only developing spinal networks, but also spontaneous networks in other areas of the nervous system. NEW & NOTEWORTHY Spontaneous activity is important for nervous system network development and consolidation. Our software uses machine learning to automatically and quickly characterize and classify episodes of spontaneous activity in the spinal cord of newborn mice. It detected changes in network activity following KCl-enhanced excitation. Using our software to classify spontaneous activity throughout development, in pathological models, or with neuromodulation, may offer insight into the development and organization of spinal circuits.
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Affiliation(s)
- A N Dalrymple
- Neuroscience and Mental Health Institute, University of Alberta , Edmonton, Alberta , Canada
| | - S A Sharples
- Hotchkiss Brain Institute, University of Calgary , Calgary, Alberta , Canada.,Graduate Program in Neuroscience, University of Calgary , Calgary, Alberta , Canada
| | - N Osachoff
- Department of Comparative Biology and Experimental Medicine, University of Calgary , Calgary, Alberta , Canada
| | - A P Lognon
- Hotchkiss Brain Institute, University of Calgary , Calgary, Alberta , Canada.,Graduate Program in Neuroscience, University of Calgary , Calgary, Alberta , Canada
| | - P J Whelan
- Hotchkiss Brain Institute, University of Calgary , Calgary, Alberta , Canada.,Department of Comparative Biology and Experimental Medicine, University of Calgary , Calgary, Alberta , Canada
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Dalrymple AN, Everaert DG, Hu DS, Mushahwar VK. A speed-adaptive intraspinal microstimulation controller to restore weight-bearing stepping in a spinal cord hemisection model. J Neural Eng 2018; 15:056023. [PMID: 30084388 DOI: 10.1088/1741-2552/aad872] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE The goal of this study was to develop control strategies to produce alternating, weight-bearing stepping in a cat model of hemisection spinal cord injury (SCI) using intraspinal microstimulation (ISMS). APPROACH Six cats were anesthetized and the functional consequences of a hemisection SCI were simulated by manually moving one hind-limb through the gait cycle over a moving treadmill belt. ISMS activated the muscles in the other leg by stimulating motor networks in the lumbosacral enlargement using low levels of current (<110 µA). The control strategy used signals from ground reaction forces and angular velocity from the manually-moved limb to anticipate states of the gait cycle, and controlled ISMS to move the other hind-limb into the opposite state. Adaptive control strategies were developed to ensure weight-bearing at different stepping speeds. The step period was predicted using generalizations obtained through four supervised machine learning algorithms and used to adapt the control strategy for faster steps. MAIN RESULTS At a single speed, 100% of the steps had sufficient weight-bearing; at faster speeds without adaptation, 97.6% of steps were weight-bearing (significantly less than that for single speed; p = 0.002). By adapting the control strategy for faster steps using the predicted step period, weight-bearing was achieved in more than 99% of the steps in three of four methods (significantly more than without adaptation p < 0.04). Overall, a multivariate model tree increased the number of weight-bearing steps, restored step symmetry, and maintained alternation at faster stepping speeds. SIGNIFICANCE Through the adaptive control strategies guided by supervised machine learning, we were able to restore weight-bearing and maintain alternation and step symmetry at varying stepping speeds.
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Affiliation(s)
- Ashley N Dalrymple
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada. Sensory Motor Adaptive Rehabilitation Technology (SMART) Network, University of Alberta, Edmonton, AB, Canada
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Farsinezhad S, Mohammadpour A, Dalrymple AN, Geisinger J, Kar P, Brett MJ, Shankar K. Transparent anodic TiO2 nanotube arrays on plastic substrates for disposable biosensors and flexible electronics. J Nanosci Nanotechnol 2013; 13:2885-91. [PMID: 23763175 DOI: 10.1166/jnn.2013.7409] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
Exploitation of anodically formed self-organized TiO2 nanotube arrays in mass-manufactured, disposable biosensors, rollable electrochromic displays and flexible large-area solar cells would greatly benefit from integration with transparent and flexible polymeric substrates. Such integration requires the vacuum deposition of a thin film of titanium on the desired substrate, which is then anodized in suitable media to generate TiO2 nanotube arrays. However the challenges associated with control of Ti film morphology, nanotube array synthesis conditions, and film adhesion and transparency, have necessitated the use of substrate heating during deposition to temperatures of at least 300 degrees C and as high as 500 degrees C to generate highly ordered open-pore nanotube arrays, thus preventing the use of polymeric substrates. We report on a film growth technique that exploits atomic peening to achieve high quality transparent TiO2 nanotube arrays with lengths up to 5.1 microm at room temperature on polyimide substrates without the need for substrate heating or substrate biasing or a Kauffman ion source. The superior optical quality and uniformity of the nanotube arrays was evidenced by the high specular reflectivity and the smooth pattern of periodic interferometric fringes in the transmission spectra of the nanotube arrays, from which the wavelength-dependent effective refractive index was extracted for the air-TiO2 composite medium. A fluorescent immunoassay biosensor constructed using 5.1 microm-long transparent titania nanotube arrays (TTNAs) grown on Kapton substrates detected human cardiac troponin I at a concentration of 0.1 microg ml(-1).
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Affiliation(s)
- Samira Farsinezhad
- Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB T6G 2V4, Canada
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