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Madarász M, Fedor FZ, Fekete Z, Rózsa B. Immunohistological responses in mice implanted with Parylene HT - ITO ECoG devices. Front Neurosci 2023; 17:1209913. [PMID: 37746144 PMCID: PMC10513038 DOI: 10.3389/fnins.2023.1209913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 08/17/2023] [Indexed: 09/26/2023] Open
Abstract
Transparent epidural devices that facilitate the concurrent use of electrophysiology and neuroimaging are arising tools for neuroscience. Testing the biocompatibility and evoked immune response of novel implantable devices is essential to lay down the fundamentals of their extensive application. Here we present an immunohistochemical evaluation of a Parylene HT/indium-tin oxide (ITO) based electrocorticography (ECoG) device, and provide long-term biocompatibility data at three chronic implantation lengths. We implanted Parylene HT/ITO ECoG devices epidurally in 5 mice and evaluated the evoked astroglial response, neuronal density and cortical thickness. We found increased astroglial response in the superficial cortical layers of all mice compared to contralateral unimplanted controls. This difference was largest at the first time point and decreased over time. Neuronal density was lower on the implanted side only at the last time point, while cortical thickness was smaller in the first and second time points, but not at the last. In this study, we present data that confirms the feasibility and chronic use of Parylene HT/ITO ECoG devices.
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Affiliation(s)
- Miklós Madarász
- BrainVision Center, Budapest, Hungary
- János Szentágothai PhD Program of Semmelweis University, Budapest, Hungary
| | - Flóra Z. Fedor
- BrainVision Center, Budapest, Hungary
- Laboratory of 3D Functional Network and Dendritic Imaging, Institute of Experimental Medicine, Budapest, Hungary
| | - Zoltán Fekete
- Research Group for Implantable Microsystems, Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
- Sleep Oscillation Research Group, Institute of Cognitive Neuroscience and Psychology, Research Center for Natural Sciences, Budapest, Hungary
| | - Balázs Rózsa
- BrainVision Center, Budapest, Hungary
- Laboratory of 3D Functional Network and Dendritic Imaging, Institute of Experimental Medicine, Budapest, Hungary
- Two-Photon Measurement Technology Research Group, The Faculty of Information Technology, Pázmány Péter Catholic University, Budapest, Hungary
- Femtonics Ltd., Budapest, Hungary
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2
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Branco MP, Geukes SH, Aarnoutse EJ, Ramsey NF, Vansteensel MJ. Nine decades of electrocorticography: A comparison between epidural and subdural recordings. Eur J Neurosci 2023; 57:1260-1288. [PMID: 36843389 DOI: 10.1111/ejn.15941] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 02/10/2023] [Accepted: 02/18/2023] [Indexed: 02/28/2023]
Abstract
In recent years, electrocorticography (ECoG) has arisen as a neural signal recording tool in the development of clinically viable neural interfaces. ECoG electrodes are generally placed below the dura mater (subdural) but can also be placed on top of the dura (epidural). In deciding which of these modalities best suits long-term implants, complications and signal quality are important considerations. Conceptually, epidural placement may present a lower risk of complications as the dura is left intact but also a lower signal quality due to the dura acting as a signal attenuator. The extent to which complications and signal quality are affected by the dura, however, has been a matter of debate. To improve our understanding of the effects of the dura on complications and signal quality, we conducted a literature review. We inventorized the effect of the dura on signal quality, decodability and longevity of acute and chronic ECoG recordings in humans and non-human primates. Also, we compared the incidence and nature of serious complications in studies that employed epidural and subdural ECoG. Overall, we found that, even though epidural recordings exhibit attenuated signal amplitude over subdural recordings, particularly for high-density grids, the decodability of epidural recorded signals does not seem to be markedly affected. Additionally, we found that the nature of serious complications was comparable between epidural and subdural recordings. These results indicate that both epidural and subdural ECoG may be suited for long-term neural signal recordings, at least for current generations of clinical and high-density ECoG grids.
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Affiliation(s)
- Mariana P Branco
- Department of Neurology and Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Simon H Geukes
- Department of Neurology and Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Erik J Aarnoutse
- Department of Neurology and Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Nick F Ramsey
- Department of Neurology and Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Mariska J Vansteensel
- Department of Neurology and Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
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Mintz Hemed N, Melosh NA. An integrated perspective for the diagnosis and therapy of neurodevelopmental disorders - From an engineering point of view. Adv Drug Deliv Rev 2023; 194:114723. [PMID: 36746077 DOI: 10.1016/j.addr.2023.114723] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 12/14/2022] [Accepted: 01/29/2023] [Indexed: 02/05/2023]
Abstract
Neurodevelopmental disorders (NDDs) are complex conditions with largely unknown pathophysiology. While many NDD symptoms are familiar, the cause of these disorders remains unclear and may involve a combination of genetic, biological, psychosocial, and environmental risk factors. Current diagnosis relies heavily on behaviorally defined criteria, which may be biased by the clinical team's professional and cultural expectations, thus a push for new biological-based biomarkers for NDDs diagnosis is underway. Emerging new research technologies offer an unprecedented view into the electrical, chemical, and physiological activity in the brain and with further development in humans may provide clinically relevant diagnoses. These could also be extended to new treatment options, which can start to address the underlying physiological issues. When combined with current speech, language, occupational therapy, and pharmacological treatment these could greatly improve patient outcomes. The current review will discuss the latest technologies that are being used or may be used for NDDs diagnosis and treatment. The aim is to provide an inspiring and forward-looking view for future research in the field.
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Affiliation(s)
- Nofar Mintz Hemed
- Department of Materials Science and Engineering, Stanford University, Stanford, CA 94305, USA.
| | - Nicholas A Melosh
- Department of Materials Science and Engineering, Stanford University, Stanford, CA 94305, USA
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Fekete Z, Zátonyi A, Kaszás A, Madarász M, Slézia A. Transparent neural interfaces: challenges and solutions of microengineered multimodal implants designed to measure intact neuronal populations using high-resolution electrophysiology and microscopy simultaneously. MICROSYSTEMS & NANOENGINEERING 2023; 9:66. [PMID: 37213820 PMCID: PMC10195795 DOI: 10.1038/s41378-023-00519-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 02/03/2023] [Accepted: 03/01/2023] [Indexed: 05/23/2023]
Abstract
The aim of this review is to present a comprehensive overview of the feasibility of using transparent neural interfaces in multimodal in vivo experiments on the central nervous system. Multimodal electrophysiological and neuroimaging approaches hold great potential for revealing the anatomical and functional connectivity of neuronal ensembles in the intact brain. Multimodal approaches are less time-consuming and require fewer experimental animals as researchers obtain denser, complex data during the combined experiments. Creating devices that provide high-resolution, artifact-free neural recordings while facilitating the interrogation or stimulation of underlying anatomical features is currently one of the greatest challenges in the field of neuroengineering. There are numerous articles highlighting the trade-offs between the design and development of transparent neural interfaces; however, a comprehensive overview of the efforts in material science and technology has not been reported. Our present work fills this gap in knowledge by introducing the latest micro- and nanoengineered solutions for fabricating substrate and conductive components. Here, the limitations and improvements in electrical, optical, and mechanical properties, the stability and longevity of the integrated features, and biocompatibility during in vivo use are discussed.
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Affiliation(s)
- Z. Fekete
- Research Group for Implantable Microsystems, Faculty of Information Technology & Bionics, Pázmány Péter Catholic University, Budapest, Hungary
- Institute of Cognitive Neuroscience & Psychology, Eotvos Lorand Research Network, Budapest, Hungary
| | - A. Zátonyi
- Research Group for Implantable Microsystems, Faculty of Information Technology & Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - A. Kaszás
- Mines Saint-Etienne, Centre CMP, Département BEL, F - 13541 Gardanne, France
- Institut de Neurosciences de la Timone, CNRS UMR 7289 & Aix-Marseille Université, 13005 Marseille, France
| | - M. Madarász
- János Szentágothai PhD Program of Semmelweis University, Budapest, Hungary
- BrainVision Center, Budapest, Hungary
| | - A. Slézia
- Institut de Neurosciences de la Timone, CNRS UMR 7289 & Aix-Marseille Université, 13005 Marseille, France
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Large-scale multimodal surface neural interfaces for primates. iScience 2022; 26:105866. [PMID: 36647381 PMCID: PMC9840154 DOI: 10.1016/j.isci.2022.105866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Deciphering the function of neural circuits can help with the understanding of brain function and treating neurological disorders. Progress toward this goal relies on the development of chronically stable neural interfaces capable of recording and modulating neural circuits with high spatial and temporal precision across large areas of the brain. Advanced innovations in designing high-density neural interfaces for small animal models have enabled breakthrough discoveries in neuroscience research. Developing similar neurotechnology for larger animal models such as nonhuman primates (NHPs) is critical to gain significant insights for translation to humans, yet still it remains elusive due to the challenges in design, fabrication, and system-level integration of such devices. This review focuses on implantable surface neural interfaces with electrical and optical functionalities with emphasis on the required technological features to realize scalable multimodal and chronically stable implants to address the unique challenges associated with nonhuman primate studies.
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Chiang CH, Wang C, Barth K, Rahimpour S, Trumpis M, Duraivel S, Rachinskiy I, Dubey A, Wingel KE, Wong M, Witham NS, Odell T, Woods V, Bent B, Doyle W, Friedman D, Bihler E, Reiche CF, Southwell DG, Haglund MM, Friedman AH, Lad SP, Devore S, Devinsky O, Solzbacher F, Pesaran B, Cogan G, Viventi J. Flexible, high-resolution thin-film electrodes for human and animal neural research. J Neural Eng 2021; 18:10.1088/1741-2552/ac02dc. [PMID: 34010815 PMCID: PMC8496685 DOI: 10.1088/1741-2552/ac02dc] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Accepted: 05/19/2021] [Indexed: 11/11/2022]
Abstract
Objective.Brain functions such as perception, motor control, learning, and memory arise from the coordinated activity of neuronal assemblies distributed across multiple brain regions. While major progress has been made in understanding the function of individual neurons, circuit interactions remain poorly understood. A fundamental obstacle to deciphering circuit interactions is the limited availability of research tools to observe and manipulate the activity of large, distributed neuronal populations in humans. Here we describe the development, validation, and dissemination of flexible, high-resolution, thin-film (TF) electrodes for recording neural activity in animals and humans.Approach.We leveraged standard flexible printed-circuit manufacturing processes to build high-resolution TF electrode arrays. We used biocompatible materials to form the substrate (liquid crystal polymer; LCP), metals (Au, PtIr, and Pd), molding (medical-grade silicone), and 3D-printed housing (nylon). We designed a custom, miniaturized, digitizing headstage to reduce the number of cables required to connect to the acquisition system and reduce the distance between the electrodes and the amplifiers. A custom mechanical system enabled the electrodes and headstages to be pre-assembled prior to sterilization, minimizing the setup time required in the operating room. PtIr electrode coatings lowered impedance and enabled stimulation. High-volume, commercial manufacturing enables cost-effective production of LCP-TF electrodes in large quantities.Main Results. Our LCP-TF arrays achieve 25× higher electrode density, 20× higher channel count, and 11× reduced stiffness than conventional clinical electrodes. We validated our LCP-TF electrodes in multiple human intraoperative recording sessions and have disseminated this technology to >10 research groups. Using these arrays, we have observed high-frequency neural activity with sub-millimeter resolution.Significance.Our LCP-TF electrodes will advance human neuroscience research and improve clinical care by enabling broad access to transformative, high-resolution electrode arrays.
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Affiliation(s)
- Chia-Han Chiang
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
- These authors contributed equally to this work
| | - Charles Wang
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
- These authors contributed equally to this work
| | - Katrina Barth
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
| | - Shervin Rahimpour
- Department of Neurosurgery, Duke School of Medicine, Durham, NC, United States of America
| | - Michael Trumpis
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
| | | | - Iakov Rachinskiy
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
| | - Agrita Dubey
- Center for Neural Science, New York University, NY, NY, United States of America
| | - Katie E Wingel
- Center for Neural Science, New York University, NY, NY, United States of America
| | - Megan Wong
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
| | - Nicholas S Witham
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, United States of America
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States of America
| | - Thomas Odell
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States of America
| | - Virginia Woods
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
| | - Brinnae Bent
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
| | - Werner Doyle
- Department of Neurosurgery, NYU Langone Medical Center, New York City, NY, United States of America
| | - Daniel Friedman
- Department of Neurology, NYU Grossman School of Medicine, NY, NY, United States of America
| | | | - Christopher F Reiche
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, United States of America
| | - Derek G Southwell
- Department of Neurosurgery, Duke School of Medicine, Durham, NC, United States of America
| | - Michael M Haglund
- Department of Neurosurgery, Duke School of Medicine, Durham, NC, United States of America
| | - Allan H Friedman
- Department of Neurosurgery, Duke School of Medicine, Durham, NC, United States of America
| | - Shivanand P Lad
- Department of Neurosurgery, Duke School of Medicine, Durham, NC, United States of America
| | - Sasha Devore
- Department of Neurology, NYU Grossman School of Medicine, NY, NY, United States of America
| | - Orrin Devinsky
- Department of Neurosurgery, NYU Langone Medical Center, New York City, NY, United States of America
- Department of Neurology, NYU Grossman School of Medicine, NY, NY, United States of America
- Comprehensive Epilepsy Center, NYU Langone Health, NY, NY, United States of America
| | - Florian Solzbacher
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, United States of America
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States of America
- Department of Materials Science & Engineering, University of Utah, Salt Lake City, UT, United States of America
| | - Bijan Pesaran
- Center for Neural Science, New York University, NY, NY, United States of America
- Department of Neurology, NYU Grossman School of Medicine, NY, NY, United States of America
| | - Gregory Cogan
- Department of Neurosurgery, Duke School of Medicine, Durham, NC, United States of America
- Department of Psychology and Neuroscience, Duke University, Durham, NC, United States of America
- Center for Cognitive Neuroscience, Duke University, Durham, NC, United States of America
- Duke Comprehensive Epilepsy Center, Duke School of Medicine, Durham, NC, United States of America
| | - Jonathan Viventi
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
- Department of Neurosurgery, Duke School of Medicine, Durham, NC, United States of America
- Department of Neurobiology, Duke School of Medicine, Durham, NC, United States of America
- Duke Comprehensive Epilepsy Center, Duke School of Medicine, Durham, NC, United States of America
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Leuthardt EC, Moran DW, Mullen TR. Defining Surgical Terminology and Risk for Brain Computer Interface Technologies. Front Neurosci 2021; 15:599549. [PMID: 33867912 PMCID: PMC8044752 DOI: 10.3389/fnins.2021.599549] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Accepted: 02/05/2021] [Indexed: 12/22/2022] Open
Abstract
With the emergence of numerous brain computer interfaces (BCI), their form factors, and clinical applications the terminology to describe their clinical deployment and the associated risk has been vague. The terms “minimally invasive” or “non-invasive” have been commonly used, but the risk can vary widely based on the form factor and anatomic location. Thus, taken together, there needs to be a terminology that best accommodates the surgical footprint of a BCI and their attendant risks. This work presents a semantic framework that describes the BCI from a procedural standpoint and its attendant clinical risk profile. We propose extending the common invasive/non-invasive distinction for BCI systems to accommodate three categories in which the BCI anatomically interfaces with the patient and whether or not a surgical procedure is required for deployment: (1) Non-invasive—BCI components do not penetrate the body, (2) Embedded—components are penetrative, but not deeper than the inner table of the skull, and (3) Intracranial –components are located within the inner table of the skull and possibly within the brain volume. Each class has a separate risk profile that should be considered when being applied to a given clinical population. Optimally, balancing this risk profile with clinical need provides the most ethical deployment of these emerging classes of devices. As BCIs gain larger adoption, and terminology becomes standardized, having an improved, more precise language will better serve clinicians, patients, and consumers in discussing these technologies, particularly within the context of surgical procedures.
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Affiliation(s)
- Eric C Leuthardt
- Department of Biomedical Engineering, Washington University, St. Louis, MO, United States.,Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, United States.,Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, United States.,Department of Mechanical Engineering and Materials Science, Washington University, St. Louis, MO, United States.,Center for Innovation in Neuroscience and Technology, Washington University School of Medicine, St. Louis, MO, United States.,Brain Laser Center, Washington University School of Medicine, St. Louis, MO, United States.,Division of Neurotechnology, Washington University School of Medicine, St. Louis, MO, United States
| | - Daniel W Moran
- Department of Biomedical Engineering, Washington University, St. Louis, MO, United States.,Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, United States
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Chin-Hao Chen R, Atry F, Richner T, Brodnick S, Pisaniello J, Ness J, Suminski AJ, Williams J, Pashaie R. A system identification analysis of optogenetically evoked electrocorticography and cerebral blood flow responses. J Neural Eng 2020; 17:056049. [PMID: 32299067 DOI: 10.1088/1741-2552/ab89fc] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE The main objective of this research was to study the coupling between neural circuits and the vascular network in the cortex of small rodents from system engineering point of view and generate a mathematical model for the dynamics of neurovascular coupling. The model was adopted to implement closed-loop blood flow control algorithms. APPROACH We used a combination of advanced technologies including optogenetics, electrocorticography, and optical coherence tomography to stimulate selected populations of neurons and simultaneously record induced electrocorticography and hemodynamic signals. We adopted system identification methods to analyze the acquired data and investigate the relation between optogenetic neural activation and consequential electrophysiology and blood flow responses. MAIN RESULTS We showed that the developed model, once trained by the acquired data, could successfully regenerate subtle spatio-temporal features of evoked electrocorticography and cerebral blood flow responses following an onset of optogenetic stimulation. SIGNIFICANCE The long term goal of this research is to open a new line for computational analysis of neurovascular coupling particularly in pathologies where the normal process of blood flow regulation in the central nervous system is disrupted including Alzheimer's disease.
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Affiliation(s)
- Rex Chin-Hao Chen
- Electrical Engineering, Computer Science Department, University of Wisconsin-Milwaukee, 3200N Cramer St., Milwaukee, WI, United States of America
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9
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Rogers N, Thunemann M, Devor A, Gilja V. Impact of Brain Surface Boundary Conditions on Electrophysiology and Implications for Electrocorticography. Front Neurosci 2020; 14:763. [PMID: 32903652 PMCID: PMC7438758 DOI: 10.3389/fnins.2020.00763] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Accepted: 06/29/2020] [Indexed: 12/02/2022] Open
Abstract
Volume conduction of electrical potentials in the brain is highly influenced by the material properties and geometry of the tissue and recording devices implanted into the tissue. These effects are very large in EEG due to the volume conduction through the skull and scalp but are often neglected in intracranial electrophysiology. When considering penetrating electrodes deep in the brain, the assumption of an infinite and homogenous medium can be used when the sources are far enough from the brain surface and the electrodes to minimize the boundary effect. When the electrodes are recording from the brain's surface the effect of the boundary cannot be neglected, and the large surface area and commonly used insulating materials in surface electrode arrays may further increase the effect by altering the nature of the boundary in the immediate vicinity of the electrodes. This gives the experimenter some control over the spatial profiles of the potentials by appropriate design of the electrode arrays. We construct a simple three-layer model to describe the effect of material properties and geometry above the brain surface on the electric potentials and conduct empirical experiments to validate this model. A laminar electrode array is used to measure the effect of insulating and relatively conducting layers above the cortical surface by recording evoked potentials alternating between a dried surface and saline covering layer, respectively. Empirically, we find that an insulating boundary amplifies the potentials relative to conductive saline by about a factor of 4, and that the effect is not constrained to potentials that originate near the surface. The model is applied to predict the influence of array design and implantation procedure on the recording amplitude and spatial selectivity of the surface electrode arrays.
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Affiliation(s)
- Nicholas Rogers
- Department of Physics, University of California, San Diego, La Jolla, CA, United States
| | - Martin Thunemann
- Department of Radiology, University of California, San Diego, La Jolla, CA, United States
| | - Anna Devor
- Department of Radiology, University of California, San Diego, La Jolla, CA, United States.,Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States.,Martinos Center for Biomedical Imaging, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, United States
| | - Vikash Gilja
- Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, United States
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Sung C, Jeon W, Nam KS, Kim Y, Butt H, Park S. Multimaterial and multifunctional neural interfaces: from surface-type and implantable electrodes to fiber-based devices. J Mater Chem B 2020; 8:6624-6666. [DOI: 10.1039/d0tb00872a] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Development of neural interfaces from surface electrodes to fibers with various type, functionality, and materials.
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Affiliation(s)
- Changhoon Sung
- Department of Bio and Brain Engineering
- Korea Advanced Institute of Science and Technology (KAIST)
- Daejeon 34141
- Republic of Korea
| | - Woojin Jeon
- Department of Bio and Brain Engineering
- Korea Advanced Institute of Science and Technology (KAIST)
- Daejeon 34141
- Republic of Korea
| | - Kum Seok Nam
- School of Electrical Engineering
- Korea Advanced Institute of Science and Technology (KAIST)
- Daejeon 34141
- Republic of Korea
| | - Yeji Kim
- Department of Bio and Brain Engineering
- Korea Advanced Institute of Science and Technology (KAIST)
- Daejeon 34141
- Republic of Korea
| | - Haider Butt
- Department of Mechanical Engineering
- Khalifa University
- Abu Dhabi 127788
- United Arab Emirates
| | - Seongjun Park
- Department of Bio and Brain Engineering
- Korea Advanced Institute of Science and Technology (KAIST)
- Daejeon 34141
- Republic of Korea
- KAIST Institute for Health Science and Technology (KIHST)
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