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Gupta B, Saxena A, Perillo ML, Wade-Kleyn LC, Thompson CH, Purcell EK. Structural, Functional, and Genetic Changes Surrounding Electrodes Implanted in the Brain. Acc Chem Res 2024; 57:1346-1359. [PMID: 38630432 PMCID: PMC11079975 DOI: 10.1021/acs.accounts.4c00057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 04/09/2024] [Accepted: 04/09/2024] [Indexed: 05/08/2024]
Abstract
Implantable neurotechnology enables monitoring and stimulating of the brain signals responsible for performing cognitive, motor, and sensory tasks. Electrode arrays implanted in the brain are increasingly used in the clinic to treat a variety of sources of neurological diseases and injuries. However, the implantation of a foreign body typically initiates a tissue response characterized by physical disruption of vasculature and the neuropil as well as the initiation of inflammation and the induction of reactive glial states. Likewise, electrical stimulation can induce damage to the surrounding tissue depending on the intensity and waveform parameters of the applied stimulus. These phenomena, in turn, are likely influenced by the surface chemistry and characteristics of the materials employed, but further information is needed to effectively link the biological responses observed to specific aspects of device design. In order to inform improved design of implantable neurotechnology, we are investigating the basic science principles governing device-tissue integration. We are employing multiple techniques to characterize the structural, functional, and genetic changes that occur in the cells surrounding implanted electrodes. First, we have developed a new "device-in-slice" technique to capture chronically implanted electrodes within thick slices of live rat brain tissue for interrogation with single-cell electrophysiology and two-photon imaging techniques. Our data revealed several new observations of tissue remodeling surrounding devices: (a) there was significant disruption of dendritic arbors in neurons near implants, where losses were driven asymmetrically on the implant-facing side. (b) There was a significant loss of dendritic spine densities in neurons near implants, with a shift toward more immature (nonfunctional) morphologies. (c) There was a reduction in excitatory neurotransmission surrounding implants, as evidenced by a reduction in the frequency of excitatory postsynaptic currents (EPSCs). Lastly, (d) there were changes in the electrophysiological underpinnings of neuronal spiking regularity. In parallel, we initiated new studies to explore changes in gene expression surrounding devices through spatial transcriptomics, which we applied to both recording and stimulating arrays. We found that (a) device implantation is associated with the induction of hundreds of genes associated with neuroinflammation, glial reactivity, oligodendrocyte function, and cellular metabolism and (b) electrical stimulation induces gene expression associated with damage or plasticity in a manner dependent upon the intensity of the applied stimulus. We are currently developing computational analysis tools to distill biomarkers of device-tissue interactions from large transcriptomics data sets. These results improve the current understanding of the biological response to electrodes implanted in the brain while producing new biomarkers for benchmarking the effects of novel electrode designs on responses. As the next generation of neurotechnology is developed, it will be increasingly important to understand the influence of novel materials, surface chemistries, and implant architectures on device performance as well as the relationship with the induction of specific cellular signaling pathways.
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Affiliation(s)
- Bhavna Gupta
- Neuroscience
Program, Michigan State University, 775 Woodlot Dr., East Lansing, Michigan 48824, United States
- Institute
for Quantitative Health Science and Engineering, Michigan State University, 775 Woodlot Dr., East Lansing, Michigan 48824, United States
| | - Akash Saxena
- Institute
for Quantitative Health Science and Engineering, Michigan State University, 775 Woodlot Dr., East Lansing, Michigan 48824, United States
- Department
of Electrical and Computer Engineering, Michigan State University, 775 Woodlot Dr., East Lansing, Michigan 48824, United States
| | - Mason L. Perillo
- Department
of Biomedical Engineering, Michigan State
University, 775 Woodlot Dr., East Lansing, Michigan 48824, United States
- Institute
for Quantitative Health Science and Engineering, Michigan State University, 775 Woodlot Dr., East Lansing, Michigan 48824, United States
| | - Lauren C. Wade-Kleyn
- Department
of Biomedical Engineering, Michigan State
University, 775 Woodlot Dr., East Lansing, Michigan 48824, United States
- Institute
for Quantitative Health Science and Engineering, Michigan State University, 775 Woodlot Dr., East Lansing, Michigan 48824, United States
| | - Cort H. Thompson
- Department
of Biomedical Engineering, Michigan State
University, 775 Woodlot Dr., East Lansing, Michigan 48824, United States
- Institute
for Quantitative Health Science and Engineering, Michigan State University, 775 Woodlot Dr., East Lansing, Michigan 48824, United States
| | - Erin K. Purcell
- Department
of Biomedical Engineering, Michigan State
University, 775 Woodlot Dr., East Lansing, Michigan 48824, United States
- Neuroscience
Program, Michigan State University, 775 Woodlot Dr., East Lansing, Michigan 48824, United States
- Institute
for Quantitative Health Science and Engineering, Michigan State University, 775 Woodlot Dr., East Lansing, Michigan 48824, United States
- Department
of Electrical and Computer Engineering, Michigan State University, 775 Woodlot Dr., East Lansing, Michigan 48824, United States
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Richie J, Letner JG, Mclane-Svoboda A, Huan Y, Ghaffari DH, Valle ED, Patel PR, Chiel HJ, Pelled G, Weiland JD, Chestek CA. Fabrication and Validation of Sub-Cellular Carbon Fiber Electrodes. IEEE Trans Neural Syst Rehabil Eng 2024; 32:739-749. [PMID: 38294928 PMCID: PMC10919889 DOI: 10.1109/tnsre.2024.3360866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2024]
Abstract
Multielectrode arrays for interfacing with neurons are of great interest for a wide range of medical applications. However, current electrodes cause damage over time. Ultra small carbon fibers help to address issues but controlling the electrode site geometry is difficult. Here we propose a methodology to create small, pointed fiber electrodes (SPFe). We compare the SPFe to previously made blowtorched fibers in characterization. The SPFe result in small site sizes [Formula: see text] with consistently sharp points (20.8 ± 7.64°). Additionally, these electrodes were able to record and/or stimulate neurons multiple animal models including rat cortex, mouse retina, Aplysia ganglia and octopus axial cord. In rat cortex, these electrodes recorded significantly higher peak amplitudes than the traditional blowtorched fibers. These SPFe may be applicable to a wide range of applications requiring a highly specific interface with individual neurons.
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Troughton JG, Ansong Snr YO, Duobaite N, Proctor CM. Finite element analysis of electric field distribution during direct current stimulation of the spinal cord: Implications for device design. APL Bioeng 2023; 7:046109. [PMID: 37928641 PMCID: PMC10624505 DOI: 10.1063/5.0163264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 11/15/2023] [Accepted: 10/12/2023] [Indexed: 11/07/2023] Open
Abstract
Spinal cord injury (SCI) arises from damage to the spinal cord, often caused by trauma or disease. The resulting sensorimotor dysfunction is variable and dependent on the extent of the injury. Despite years of research, curative options for SCI remain limited. However, recent advancements in electric field stimulated axonal regrowth have shown promise for neuronal regeneration. One roadblock in the development of therapeutic treatments based on this is a lack of understanding of the exogenous electric field distribution in the injured tissue, and in particular, how this is influenced by electrode geometry and placement. To better understand this electric field, and provide a means by which it can be optimized, we have developed a finite element model of such spinal cord treatment. We investigate the impact of variations in electrode geometry, spinal cord size, and applied current magnitude as well as looking at several injury models in relation to clinically observed outcomes. Through this, we show that electrode shape has little effect on the induced electric field, that the placement of these electrodes has a noticeable influence on the field distribution, and that the magnitude of this field is governed by both the applied current and the spinal cord morphology. We also show that the injury modality influences the induced field distribution and that a stronger understanding of the injury will help decide treatment parameters. This work provides guidance in the design of electrodes for future clinical application in direct current electric field stimulation for axonal regeneration.
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Affiliation(s)
| | - Yaw O. Ansong Snr
- Department of Engineering, University of Cambridge, Trumpington Street, Cambridge, United Kingdom
| | - Nida Duobaite
- Department of Engineering, University of Cambridge, Trumpington Street, Cambridge, United Kingdom
| | - Christopher M. Proctor
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom
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4
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Yankovaskaya UI, Korznikova EA, Korpusova SD, Zakharov PV. Mechanical Properties of the Pt-CNT Composite under Uniaxial Deformation: Tension and Compression. MATERIALS (BASEL, SWITZERLAND) 2023; 16:ma16114140. [PMID: 37297274 DOI: 10.3390/ma16114140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Revised: 04/30/2023] [Accepted: 05/26/2023] [Indexed: 06/12/2023]
Abstract
Composite materials are gaining increasing attention from researchers worldwide due to their ability to offer tailored properties for various technical challenges. One of these promising fields is metal matrix composites, including carbon-reinforced metals and alloys. These materials allow for the reduction of density while simultaneously enhancing their functional properties. This study is focused on the Pt-CNT composite, its mechanical characteristics, and structural features under uniaxial deformation depending on temperature and mass fractions of carbon nanotube (CNT). The mechanical behavior of platinum reinforced with carbon nanotubes of diameters varying in the interval 6.62-16.55 Å under uniaxial tension and compression deformation has been studied by the molecular dynamics method. Simulations for tensile and compression deformations have been done for all specimens at different temperatures (viz. 300 K, 500 K, 700 K, 900 K, 1100 K, and 1500 K). The calculated mechanical characteristics allow us to conclude that, compared to pure platinum, the Young's modulus increased by about 60%. The results indicate that yield and tensile strength values decreases with increase in temperature for all simulation blocks. This increase was due to the inherent high axial rigidity of CNTs. In this work, these characteristics are calculated for the first time for Pt-CNT. It can be concluded that CNTs can be an effective reinforcing material for composites based on a metal matrix under tensile strain.
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Affiliation(s)
- Ustina I Yankovaskaya
- Department of Physics, Polzunov Altai State Technical University, Barnaul 656038, Russia
| | - Elena A Korznikova
- Polytechnic Institute (Branch) in Mirny, North-Eastern Federal University, Mirny 678170, Russia
- Institute for Metals Superplasticity Problems of RAS, Ufa 450001, Russia
| | - Sofia D Korpusova
- Department of Physics, Peter the Great St. Petersburg Polytechnic University, St. Petersburg 195251, Russia
| | - Pavel V Zakharov
- Department of Physics, Peter the Great St. Petersburg Polytechnic University, St. Petersburg 195251, Russia
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Zhou M, Young BK, Valle ED, Koo B, Kim J, Weiland JD. Full-field, conformal epiretinal electrode array using hydrogel and polymer hybrid technology. Sci Rep 2023; 13:6973. [PMID: 37117214 PMCID: PMC10147691 DOI: 10.1038/s41598-023-32976-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 04/05/2023] [Indexed: 04/30/2023] Open
Abstract
Shape-morphable electrode arrays can form 3D surfaces to conform to complex neural anatomy and provide consistent positioning needed for next-generation neural interfaces. Retinal prostheses need a curved interface to match the spherical eye and a coverage of several cm to restore peripheral vision. We fabricated a full-field array that can (1) cover a visual field of 57° based on electrode position and of 113° based on the substrate size; (2) fold to form a compact shape for implantation; (3) self-deploy into a curvature fitting the eye after implantation. The full-field array consists of multiple polymer layers, specifically, a sandwich structure of elastomer/polyimide-based-electrode/elastomer, coated on one side with hydrogel. Electrodeposition of high-surface-area platinum/iridium alloy significantly improved the electrical properties of the electrodes. Hydrogel over-coating reduced electrode performance, but the electrodes retained better properties than those without platinum/iridium. The full-field array was rolled into a compact shape and, once implanted into ex vivo pig eyes, restored to a 3D curved surface. The full-field retinal array provides significant coverage of the retina while allowing surgical implantation through an incision 33% of the final device diameter. The shape-changing material platform can be used with other neural interfaces that require conformability to complex neuroanatomy.
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Affiliation(s)
- Muru Zhou
- Macromolecular Science and Engineering Program, University of Michigan, Ann Arbor, 48105, USA
| | - Benjamin K Young
- Department of Ophthalmology, Oregon Health and Sciences University, Portland, OR, 97239, USA
| | - Elena Della Valle
- Biomedical Engineering, University of Michigan, Ann Arbor, 48105, USA
| | - Beomseo Koo
- Biomedical Engineering, University of Michigan, Ann Arbor, 48105, USA
| | - Jinsang Kim
- Macromolecular Science and Engineering Program, University of Michigan, Ann Arbor, 48105, USA
- Biomedical Engineering, University of Michigan, Ann Arbor, 48105, USA
- Chemical Engineering, University of Michigan, Ann Arbor, 48105, USA
- Materials Science and Engineering, University of Michigan, Ann Arbor, 48105, USA
- Chemistry, University of Michigan, Ann Arbor, 48105, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, 48105, USA
| | - James D Weiland
- Biomedical Engineering, University of Michigan, Ann Arbor, 48105, USA.
- Biointerfaces Institute, University of Michigan, Ann Arbor, 48105, USA.
- Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, 48105, USA.
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Letner JG, Patel PR, Hsieh JC, Smith Flores IM, della Valle E, Walker LA, Weiland JD, Chestek CA, Cai D. Post-explant profiling of subcellular-scale carbon fiber intracortical electrodes and surrounding neurons enables modeling of recorded electrophysiology. J Neural Eng 2023; 20:026019. [PMID: 36848679 PMCID: PMC10022369 DOI: 10.1088/1741-2552/acbf78] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 01/12/2023] [Accepted: 02/27/2023] [Indexed: 03/01/2023]
Abstract
Objective.Characterizing the relationship between neuron spiking and the signals that electrodes record is vital to defining the neural circuits driving brain function and informing clinical brain-machine interface design. However, high electrode biocompatibility and precisely localizing neurons around the electrodes are critical to defining this relationship.Approach.Here, we demonstrate consistent localization of the recording site tips of subcellular-scale (6.8µm diameter) carbon fiber electrodes and the positions of surrounding neurons. We implanted male rats with carbon fiber electrode arrays for 6 or 12+ weeks targeting layer V motor cortex. After explanting the arrays, we immunostained the implant site and localized putative recording site tips with subcellular-cellular resolution. We then 3D segmented neuron somata within a 50µm radius from implanted tips to measure neuron positions and health and compare to healthy cortex with symmetric stereotaxic coordinates.Main results.Immunostaining of astrocyte, microglia, and neuron markers confirmed that overall tissue health was indicative of high biocompatibility near the tips. While neurons near implanted carbon fibers were stretched, their number and distribution were similar to hypothetical fibers placed in healthy contralateral brain. Such similar neuron distributions suggest that these minimally invasive electrodes demonstrate the potential to sample naturalistic neural populations. This motivated the prediction of spikes produced by nearby neurons using a simple point source model fit using recorded electrophysiology and the mean positions of the nearest neurons observed in histology. Comparing spike amplitudes suggests that the radius at which single units can be distinguished from others is near the fourth closest neuron (30.7 ± 4.6µm,X-± S) in layer V motor cortex.Significance.Collectively, these data and simulations provide the first direct evidence that neuron placement in the immediate vicinity of the recording site influences how many spike clusters can be reliably identified by spike sorting.
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Affiliation(s)
- Joseph G Letner
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Paras R Patel
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Jung-Chien Hsieh
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Israel M Smith Flores
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Elena della Valle
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Logan A Walker
- Biophysics Program, University of Michigan, Ann Arbor, MI 48109, United States of America
- Department of Computational Medicine and Bioinformatics, Michigan Medicine, Ann Arbor, MI 48109, United States of America
| | - James D Weiland
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, United States of America
- Department of Ophthalmology and Visual Sciences, Kellogg Eye Center, University of Michigan, Ann Arbor, MI 48105, United States of America
| | - Cynthia A Chestek
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, United States of America
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109, United States of America
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, United States of America
- Robotics Department, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Dawen Cai
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109, United States of America
- Biophysics Program, University of Michigan, Ann Arbor, MI 48109, United States of America
- Department of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, MI 48109, United States of America
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Xu M, Zhao Y, Xu G, Zhang Y, Sun S, Sun Y, Wang J, Pei R. Recent Development of Neural Microelectrodes with Dual-Mode Detection. BIOSENSORS 2022; 13:59. [PMID: 36671894 PMCID: PMC9856135 DOI: 10.3390/bios13010059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 12/24/2022] [Accepted: 12/28/2022] [Indexed: 06/17/2023]
Abstract
Neurons communicate through complex chemical and electrophysiological signal patterns to develop a tight information network. A physiological or pathological event cannot be explained by signal communication mode. Therefore, dual-mode electrodes can simultaneously monitor the chemical and electrophysiological signals in the brain. They have been invented as an essential tool for brain science research and brain-computer interface (BCI) to obtain more important information and capture the characteristics of the neural network. Electrochemical sensors are the most popular methods for monitoring neurochemical levels in vivo. They are combined with neural microelectrodes to record neural electrical activity. They simultaneously detect the neurochemical and electrical activity of neurons in vivo using high spatial and temporal resolutions. This paper systematically reviews the latest development of neural microelectrodes depending on electrode materials for simultaneous in vivo electrochemical sensing and electrophysiological signal recording. This includes carbon-based microelectrodes, silicon-based microelectrode arrays (MEAs), and ceramic-based MEAs, focusing on the latest progress since 2018. In addition, the structure and interface design of various types of neural microelectrodes have been comprehensively described and compared. This could be the key to simultaneously detecting electrochemical and electrophysiological signals.
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Affiliation(s)
- Meng Xu
- CAS Key Laboratory for Nano-Bio Interface, Division of Nano-biomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics (SINANO), Chinese Academy of Sciences, Suzhou 215123, China
- School of Nano-Tech and Nano-Bionics, University of Science and Technology of China (USTC), Hefei 230026, China
| | - Yuewu Zhao
- CAS Key Laboratory for Nano-Bio Interface, Division of Nano-biomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics (SINANO), Chinese Academy of Sciences, Suzhou 215123, China
| | - Guanghui Xu
- School of Nano-Tech and Nano-Bionics, University of Science and Technology of China (USTC), Hefei 230026, China
| | - Yuehu Zhang
- CAS Key Laboratory for Nano-Bio Interface, Division of Nano-biomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics (SINANO), Chinese Academy of Sciences, Suzhou 215123, China
- School of Nano-Tech and Nano-Bionics, University of Science and Technology of China (USTC), Hefei 230026, China
| | - Shengkai Sun
- CAS Key Laboratory for Nano-Bio Interface, Division of Nano-biomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics (SINANO), Chinese Academy of Sciences, Suzhou 215123, China
| | - Yan Sun
- CAS Key Laboratory for Nano-Bio Interface, Division of Nano-biomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics (SINANO), Chinese Academy of Sciences, Suzhou 215123, China
- School of Nano-Tech and Nano-Bionics, University of Science and Technology of China (USTC), Hefei 230026, China
| | - Jine Wang
- CAS Key Laboratory for Nano-Bio Interface, Division of Nano-biomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics (SINANO), Chinese Academy of Sciences, Suzhou 215123, China
- School of Nano-Tech and Nano-Bionics, University of Science and Technology of China (USTC), Hefei 230026, China
| | - Renjun Pei
- CAS Key Laboratory for Nano-Bio Interface, Division of Nano-biomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics (SINANO), Chinese Academy of Sciences, Suzhou 215123, China
- School of Nano-Tech and Nano-Bionics, University of Science and Technology of China (USTC), Hefei 230026, China
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Whitsitt QA, Koo B, Celik ME, Evans BM, Weiland JD, Purcell EK. Spatial Transcriptomics as a Novel Approach to Redefine Electrical Stimulation Safety. Front Neurosci 2022; 16:937923. [PMID: 35928007 PMCID: PMC9344921 DOI: 10.3389/fnins.2022.937923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 06/17/2022] [Indexed: 11/13/2022] Open
Abstract
Current standards for safe delivery of electrical stimulation to the central nervous system are based on foundational studies which examined post-mortem tissue for histological signs of damage. This set of observations and the subsequently proposed limits to safe stimulation, termed the “Shannon limits,” allow for a simple calculation (using charge per phase and charge density) to determine the intensity of electrical stimulation that can be delivered safely to brain tissue. In the three decades since the Shannon limits were reported, advances in molecular biology have allowed for more nuanced and detailed approaches to be used to expand current understanding of the physiological effects of stimulation. Here, we demonstrate the use of spatial transcriptomics (ST) in an exploratory investigation to assess the biological response to electrical stimulation in the brain. Electrical stimulation was delivered to the rat visual cortex with either acute or chronic electrode implantation procedures. To explore the influence of device type and stimulation parameters, we used carbon fiber ultramicroelectrode arrays (7 μm diameter) and microwire electrode arrays (50 μm diameter) delivering charge and charge density levels selected above and below reported tissue damage thresholds (range: 2–20 nC, 0.1–1 mC/cm2). Spatial transcriptomics was performed using Visium Spatial Gene Expression Slides (10x Genomics, Pleasanton, CA, United States), which enabled simultaneous immunohistochemistry and ST to directly compare traditional histological metrics to transcriptional profiles within each tissue sample. Our data give a first look at unique spatial patterns of gene expression that are related to cellular processes including inflammation, cell cycle progression, and neuronal plasticity. At the acute timepoint, an increase in inflammatory and plasticity related genes was observed surrounding a stimulating electrode compared to a craniotomy control. At the chronic timepoint, an increase in inflammatory and cell cycle progression related genes was observed both in the stimulating vs. non-stimulating microwire electrode comparison and in the stimulating microwire vs. carbon fiber comparison. Using the spatial aspect of this method as well as the within-sample link to traditional metrics of tissue damage, we demonstrate how these data may be analyzed and used to generate new hypotheses and inform safety standards for stimulation in cortex.
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Affiliation(s)
- Quentin A. Whitsitt
- Department of Biomedical Engineering, Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, United States
| | - Beomseo Koo
- Department of Biomedical Engineering, Biointerfaces Institute, University of Michigan, Ann Arbor, MI, United States
| | - Mahmut Emin Celik
- Department of Electrical and Electronics Engineering, Gazi University, Ankara, Turkey
| | - Blake M. Evans
- Department of Biomedical Engineering, Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, United States
| | - James D. Weiland
- Department of Biomedical Engineering, Biointerfaces Institute, University of Michigan, Ann Arbor, MI, United States
- Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI, United States
| | - Erin K. Purcell
- Department of Biomedical Engineering, Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, United States
- *Correspondence: Erin K. Purcell,
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