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Dalrymple AN, Jones ST, Fallon JB, Shepherd RK, Weber DJ. Overcoming failure: improving acceptance and success of implanted neural interfaces. Bioelectron Med 2025; 11:6. [PMID: 40083033 PMCID: PMC11907899 DOI: 10.1186/s42234-025-00168-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2024] [Accepted: 02/06/2025] [Indexed: 03/16/2025] Open
Abstract
Implanted neural interfaces are electronic devices that stimulate or record from neurons with the purpose of improving the quality of life of people who suffer from neural injury or disease. Devices have been designed to interact with neurons throughout the body to treat a growing variety of conditions. The development and use of implanted neural interfaces is increasing steadily and has shown great success, with implants lasting for years to decades and improving the health and quality of life of many patient populations. Despite these successes, implanted neural interfaces face a multitude of challenges to remain effective for the lifetime of their users. The devices are comprised of several electronic and mechanical components that each may be susceptible to failure. Furthermore, implanted neural interfaces, like any foreign body, will evoke an immune response. The immune response will differ for implants in the central nervous system and peripheral nervous system, as well as over time, ultimately resulting in encapsulation of the device. This review describes the challenges faced by developers of neural interface systems, particularly devices already in use in humans. The mechanical and technological failure modes of each component of an implant system is described. The acute and chronic reactions to devices in the peripheral and central nervous system and how they affect system performance are depicted. Further, physical challenges such as micro and macro movements are reviewed. The clinical implications of device failures are summarized and a guide for determining the severity of complication was developed and provided. Common methods to diagnose and examine mechanical, technological, and biological failure modes at various stages of development and testing are outlined, with an emphasis on chronic in vivo characterization of implant systems. Finally, this review concludes with an overview of some of the innovative solutions developed to reduce or resolve the challenges faced by implanted neural interface systems.
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Affiliation(s)
- Ashley N Dalrymple
- 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.
- NERVES Lab, University of Utah, Salt Lake City, UT, USA.
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.
- NeuroMechatronics Lab, Carnegie Mellon University, Pittsburgh, PA, USA.
| | - Sonny T Jones
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
- NERVES Lab, University of Utah, Salt Lake City, UT, USA
| | - James B Fallon
- Bionics Institute, St. Vincent's Hospital, Melbourne, VIC, Australia
- Medical Bionics Department, University of Melbourne, Melbourne, VIC, Australia
| | - Robert K Shepherd
- Bionics Institute, St. Vincent's Hospital, Melbourne, VIC, Australia
| | - Douglas J Weber
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
- NeuroMechatronics Lab, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
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2
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Papale P, Wang F, Self MW, Roelfsema PR. An extensive dataset of spiking activity to reveal the syntax of the ventral stream. Neuron 2025; 113:539-553.e5. [PMID: 39809277 DOI: 10.1016/j.neuron.2024.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 08/16/2024] [Accepted: 12/03/2024] [Indexed: 01/16/2025]
Abstract
Visual neuroscience benefits from high-quality datasets with neuronal responses to many images. Several neuroimaging datasets have been published in recent years, but no comparable dataset with spiking activity exists. Here, we introduce the THINGS ventral stream spiking dataset (TVSD). We extensively sampled neuronal activity in response to >25,000 natural images from the THINGS database in macaques, using high-channel-count implants in three key cortical regions: primary visual cortex (V1), V4, and the inferotemporal cortex. We showcase the utility of TVSD by using an artificial neural network to visualize the tuning of neurons. We also characterize the correlated fluctuations in activity within and between areas and demonstrate that these noise correlations are strongest between neurons with similar tuning. The TVSD allows researchers to answer many questions about neuronal tuning, analyze the interactions within and between cortical regions, and compare spiking activity in monkeys to human neuroimaging data.
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Affiliation(s)
- Paolo Papale
- Department of Vision & Cognition, Netherlands Institute for Neuroscience (KNAW), 1105 BA Amsterdam, the Netherlands.
| | - Feng Wang
- Department of Vision & Cognition, Netherlands Institute for Neuroscience (KNAW), 1105 BA Amsterdam, the Netherlands
| | - Matthew W Self
- Department of Vision & Cognition, Netherlands Institute for Neuroscience (KNAW), 1105 BA Amsterdam, the Netherlands
| | - Pieter R Roelfsema
- Department of Vision & Cognition, Netherlands Institute for Neuroscience (KNAW), 1105 BA Amsterdam, the Netherlands; Department of Integrative Neurophysiology, VU University, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands; Department of Neurosurgery, Academic Medical Centre, Postbus 22660, 1100 DD Amsterdam, the Netherlands; Laboratory of Visual Brain Therapy, Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, 75012 Paris, France.
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3
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Senk J, Hagen E, van Albada SJ, Diesmann M. Reconciliation of weak pairwise spike-train correlations and highly coherent local field potentials across space. Cereb Cortex 2024; 34:bhae405. [PMID: 39462814 PMCID: PMC11513197 DOI: 10.1093/cercor/bhae405] [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: 11/07/2023] [Revised: 09/09/2024] [Accepted: 09/23/2024] [Indexed: 10/29/2024] Open
Abstract
Multi-electrode arrays covering several square millimeters of neural tissue provide simultaneous access to population signals such as extracellular potentials and spiking activity of one hundred or more individual neurons. The interpretation of the recorded data calls for multiscale computational models with corresponding spatial dimensions and signal predictions. Multi-layer spiking neuron network models of local cortical circuits covering about $1\,{\text{mm}^{2}}$ have been developed, integrating experimentally obtained neuron-type-specific connectivity data and reproducing features of observed in-vivo spiking statistics. Local field potentials can be computed from the simulated spiking activity. We here extend a local network and local field potential model to an area of $4\times 4\,{\text{mm}^{2}}$, preserving the neuron density and introducing distance-dependent connection probabilities and conduction delays. We find that the upscaling procedure preserves the overall spiking statistics of the original model and reproduces asynchronous irregular spiking across populations and weak pairwise spike-train correlations in agreement with experimental recordings from sensory cortex. Also compatible with experimental observations, the correlation of local field potential signals is strong and decays over a distance of several hundred micrometers. Enhanced spatial coherence in the low-gamma band around $50\,\text{Hz}$ may explain the recent report of an apparent band-pass filter effect in the spatial reach of the local field potential.
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Affiliation(s)
- Johanna Senk
- Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Wilhelm-Johnen-Str., 52428 Jülich, Germany
- Sussex AI, School of Engineering and Informatics, University of Sussex, Chichester, Falmer, Brighton BN1 9QJ, United Kingdom
| | - Espen Hagen
- Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Wilhelm-Johnen-Str., 52428 Jülich, Germany
- Centre for Precision Psychiatry, Institute of Clinical Medicine, University of Oslo, and Division of Mental Health and Addiction, Oslo University Hospital, Ullevål Hospital, 0424 Oslo, Norway
| | - Sacha J van Albada
- Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Wilhelm-Johnen-Str., 52428 Jülich, Germany
- Institute of Zoology, University of Cologne, Zülpicher Str., 50674 Cologne, Germany
| | - Markus Diesmann
- Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Wilhelm-Johnen-Str., 52428 Jülich, Germany
- JARA-Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Wilhelm-Johnen-Str., 52428 Jülich Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, Pauwelsstr., 52074 Aachen, Germany
- Department of Physics, Faculty 1, RWTH Aachen University, Otto-Blumenthal-Str., 52074 Aachen, Germany
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4
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Guo J, Wang X, Bai R, Zhang Z, Chen H, Xue K, Ma C, Zang D, Yin E, Gao K, Ji B. A Cost-Effective and Easy-to-Fabricate Conductive Velcro Dry Electrode for Durable and High-Performance Biopotential Acquisition. BIOSENSORS 2024; 14:432. [PMID: 39329808 PMCID: PMC11430566 DOI: 10.3390/bios14090432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2024] [Revised: 09/02/2024] [Accepted: 09/04/2024] [Indexed: 09/28/2024]
Abstract
Compared with the traditional gel electrode, the dry electrode is being taken more seriously in bioelectrical recording because of its easy preparation, long-lasting ability, and reusability. However, the commonly used dry AgCl electrodes and silver cloth electrodes are generally hard to record through hair due to their flat contact surface. Claw electrodes can contact skin through hair on the head and body, but the internal claw structure is relatively hard and causes discomfort after being worn for a few hours. Here, we report a conductive Velcro electrode (CVE) with an elastic hook hair structure, which can collect biopotential through body hair. The elastic hooks greatly reduce discomfort after long-time wearing and can even be worn all day. The CVE electrode is fabricated by one-step immersion in conductive silver paste based on the cost-effective commercial Velcro, forming a uniform and durable conductive coating on a cluster of hook microstructures. The electrode shows excellent properties, including low impedance (15.88 kΩ @ 10 Hz), high signal-to-noise ratio (16.0 dB), strong water resistance, and mechanical resistance. After washing in laundry detergent, the impedance of CVE is still 16% lower than the commercial AgCl electrodes. To verify the mechanical strength and recovery capability, we conducted cyclic compression experiments. The results show that the displacement change of the electrode hook hair after 50 compression cycles was still less than 1%. This electrode provides a universal acquisition scheme, including effective acquisition of different parts of the body with or without hair. Finally, the gesture recognition from electromyography (EMG) by the CVE electrode was applied with accuracy above 90%. The CVE proposed in this study has great potential and promise in various human-machine interface (HMI) applications that employ surface biopotential signals on the body or head with hair.
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Affiliation(s)
- Jun Guo
- Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China
- National Key Laboratory of Unmanned Aerial Vehicle Technology, Integrated Research and Development Platform of Unmanned Aerial Vehicle Technology, Northwestern Polytechnical University, Xi'an 710072, China
- Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace, School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China
| | - Xuanqi Wang
- Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China
- National Key Laboratory of Unmanned Aerial Vehicle Technology, Integrated Research and Development Platform of Unmanned Aerial Vehicle Technology, Northwestern Polytechnical University, Xi'an 710072, China
- Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace, School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China
| | - Ruiyu Bai
- Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China
- National Key Laboratory of Unmanned Aerial Vehicle Technology, Integrated Research and Development Platform of Unmanned Aerial Vehicle Technology, Northwestern Polytechnical University, Xi'an 710072, China
- Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace, School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China
| | - Zimo Zhang
- Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China
- National Key Laboratory of Unmanned Aerial Vehicle Technology, Integrated Research and Development Platform of Unmanned Aerial Vehicle Technology, Northwestern Polytechnical University, Xi'an 710072, China
- Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace, School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China
| | - Huazhen Chen
- Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China
- National Key Laboratory of Unmanned Aerial Vehicle Technology, Integrated Research and Development Platform of Unmanned Aerial Vehicle Technology, Northwestern Polytechnical University, Xi'an 710072, China
- Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace, School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China
| | - Kai Xue
- Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China
- National Key Laboratory of Unmanned Aerial Vehicle Technology, Integrated Research and Development Platform of Unmanned Aerial Vehicle Technology, Northwestern Polytechnical University, Xi'an 710072, China
- Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace, School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China
| | - Chuang Ma
- Defense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100071, China
- Intelligent Game and Decision Laboratory, Beijing 100071, China
- Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, China
| | - Dawei Zang
- Department of Rehabilitation Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Erwei Yin
- Defense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100071, China
- Intelligent Game and Decision Laboratory, Beijing 100071, China
- Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, China
| | - Kunpeng Gao
- College of Information Science and Technology, Donghua University, Shanghai 201620, China
| | - Bowen Ji
- Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China
- National Key Laboratory of Unmanned Aerial Vehicle Technology, Integrated Research and Development Platform of Unmanned Aerial Vehicle Technology, Northwestern Polytechnical University, Xi'an 710072, China
- Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace, School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China
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Morales-Gregorio A, Kurth AC, Ito J, Kleinjohann A, Barthélemy FV, Brochier T, Grün S, van Albada SJ. Neural manifolds in V1 change with top-down signals from V4 targeting the foveal region. Cell Rep 2024; 43:114371. [PMID: 38923458 DOI: 10.1016/j.celrep.2024.114371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 03/25/2024] [Accepted: 05/31/2024] [Indexed: 06/28/2024] Open
Abstract
High-dimensional brain activity is often organized into lower-dimensional neural manifolds. However, the neural manifolds of the visual cortex remain understudied. Here, we study large-scale multi-electrode electrophysiological recordings of macaque (Macaca mulatta) areas V1, V4, and DP with a high spatiotemporal resolution. We find that the population activity of V1 contains two separate neural manifolds, which correlate strongly with eye closure (eyes open/closed) and have distinct dimensionalities. Moreover, we find strong top-down signals from V4 to V1, particularly to the foveal region of V1, which are significantly stronger during the eyes-open periods. Finally, in silico simulations of a balanced spiking neuron network qualitatively reproduce the experimental findings. Taken together, our analyses and simulations suggest that top-down signals modulate the population activity of V1. We postulate that the top-down modulation during the eyes-open periods prepares V1 for fast and efficient visual responses, resulting in a type of visual stand-by state.
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Affiliation(s)
- Aitor Morales-Gregorio
- Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Jülich, Germany; Institute of Zoology, University of Cologne, Cologne, Germany.
| | - Anno C Kurth
- Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Jülich, Germany; RWTH Aachen University, Aachen, Germany
| | - Junji Ito
- Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Jülich, Germany
| | - Alexander Kleinjohann
- Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Jülich, Germany; Theoretical Systems Neurobiology, RWTH Aachen University, Aachen, Germany
| | - Frédéric V Barthélemy
- Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Jülich, Germany; Institut de Neurosciences de la Timone (INT), CNRS and Aix-Marseille Université, Marseille, France
| | - Thomas Brochier
- Institut de Neurosciences de la Timone (INT), CNRS and Aix-Marseille Université, Marseille, France
| | - Sonja Grün
- Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Jülich, Germany; Theoretical Systems Neurobiology, RWTH Aachen University, Aachen, Germany; JARA-Institut Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany
| | - Sacha J van Albada
- Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Jülich, Germany; Institute of Zoology, University of Cologne, Cologne, Germany
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6
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Forró C, Musall S, Montes VR, Linkhorst J, Walter P, Wessling M, Offenhäusser A, Ingebrandt S, Weber Y, Lampert A, Santoro F. Toward the Next Generation of Neural Iontronic Interfaces. Adv Healthc Mater 2023; 12:e2301055. [PMID: 37434349 PMCID: PMC11468917 DOI: 10.1002/adhm.202301055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 05/23/2023] [Indexed: 07/13/2023]
Abstract
Neural interfaces are evolving at a rapid pace owing to advances in material science and fabrication, reduced cost of scalable complementary metal oxide semiconductor (CMOS) technologies, and highly interdisciplinary teams of researchers and engineers that span a large range from basic to applied and clinical sciences. This study outlines currently established technologies, defined as instruments and biological study systems that are routinely used in neuroscientific research. After identifying the shortcomings of current technologies, such as a lack of biocompatibility, topological optimization, low bandwidth, and lack of transparency, it maps out promising directions along which progress should be made to achieve the next generation of symbiotic and intelligent neural interfaces. Lastly, it proposes novel applications that can be achieved by these developments, ranging from the understanding and reproduction of synaptic learning to live-long multimodal measurements to monitor and treat various neuronal disorders.
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Affiliation(s)
- Csaba Forró
- Institute for Biological Information Processing ‐ Bioelectronics IBI‐3Wilhelm‐Johnen‐Straße52428JülichGermany
- Institute of Materials in Electrical Engineering 1RWTH AachenSommerfeldstr. 2452074AachenGermany
| | - Simon Musall
- Institute for Biological Information Processing ‐ Bioelectronics IBI‐3Wilhelm‐Johnen‐Straße52428JülichGermany
- Institute for ZoologyRWTH Aachen UniversityWorringerweg 352074AachenGermany
| | - Viviana Rincón Montes
- Institute for Biological Information Processing ‐ Bioelectronics IBI‐3Wilhelm‐Johnen‐Straße52428JülichGermany
| | - John Linkhorst
- Chemical Process EngineeringRWTH AachenForckenbeckstr. 5152074AachenGermany
| | - Peter Walter
- Department of OphthalmologyUniversity Hospital RWTH AachenPauwelsstr. 3052074AachenGermany
| | - Matthias Wessling
- Chemical Process EngineeringRWTH AachenForckenbeckstr. 5152074AachenGermany
- DWI Leibniz Institute for Interactive MaterialsRWTH AachenForckenbeckstr. 5052074AachenGermany
| | - Andreas Offenhäusser
- Institute for Biological Information Processing ‐ Bioelectronics IBI‐3Wilhelm‐Johnen‐Straße52428JülichGermany
| | - Sven Ingebrandt
- Institute of Materials in Electrical Engineering 1RWTH AachenSommerfeldstr. 2452074AachenGermany
| | - Yvonne Weber
- Department of EpileptologyNeurology, RWTH AachenPauwelsstr. 3052074AachenGermany
| | - Angelika Lampert
- Institute of NeurophysiologyUniklinik RWTH AachenPauwelsstrasse 3052074AachenGermany
| | - Francesca Santoro
- Institute for Biological Information Processing ‐ Bioelectronics IBI‐3Wilhelm‐Johnen‐Straße52428JülichGermany
- Institute of Materials in Electrical Engineering 1RWTH AachenSommerfeldstr. 2452074AachenGermany
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Chen X, Wang F, Kooijmans R, Klink PC, Boehler C, Asplund M, Roelfsema PR. Chronic stability of a neuroprosthesis comprising multiple adjacent Utah arrays in monkeys. J Neural Eng 2023; 20:036039. [PMID: 37386891 PMCID: PMC7617000 DOI: 10.1088/1741-2552/ace07e] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 06/21/2023] [Indexed: 07/01/2023]
Abstract
Objective. Electrical stimulation of visual cortex via a neuroprosthesis induces the perception of dots of light ('phosphenes'), potentially allowing recognition of simple shapes even after decades of blindness. However, restoration of functional vision requires large numbers of electrodes, and chronic, clinical implantation of intracortical electrodes in the visual cortex has only been achieved using devices of up to 96 channels. We evaluated the efficacy and stability of a 1024-channel neuroprosthesis system in non-human primates (NHPs) over more than 3 years to assess its suitability for long-term vision restoration.Approach.We implanted 16 microelectrode arrays (Utah arrays) consisting of 8 × 8 electrodes with iridium oxide tips in the primary visual cortex (V1) and visual area 4 (V4) of two sighted macaques. We monitored the animals' health and measured electrode impedances and neuronal signal quality by calculating signal-to-noise ratios of visually driven neuronal activity, peak-to-peak voltages of the waveforms of action potentials, and the number of channels with high-amplitude signals. We delivered cortical microstimulation and determined the minimum current that could be perceived, monitoring the number of channels that successfully yielded phosphenes. We also examined the influence of the implant on a visual task after 2-3 years of implantation and determined the integrity of the brain tissue with a histological analysis 3-3.5 years post-implantation.Main results. The monkeys remained healthy throughout the implantation period and the device retained its mechanical integrity and electrical conductivity. However, we observed decreasing signal quality with time, declining numbers of phosphene-evoking electrodes, decreases in electrode impedances, and impaired performance on a visual task at visual field locations corresponding to implanted cortical regions. Current thresholds increased with time in one of the two animals. The histological analysis revealed encapsulation of arrays and cortical degeneration. Scanning electron microscopy on one array revealed degradation of IrOxcoating and higher impedances for electrodes with broken tips.Significance. Long-term implantation of a high-channel-count device in NHP visual cortex was accompanied by deformation of cortical tissue and decreased stimulation efficacy and signal quality over time. We conclude that improvements in device biocompatibility and/or refinement of implantation techniques are needed before future clinical use is feasible.
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Affiliation(s)
- Xing Chen
- Department of Vision and Cognition, Netherlands Institute for Neuroscience, Meibergdreef 47,1105 BA Amsterdam, The Netherlands
- Department of Ophthalmology, University of Pittsburgh School of Medicine, 1622 Locust St, Pittsburgh, PA 15219, United States of America
| | - Feng Wang
- Department of Vision and Cognition, Netherlands Institute for Neuroscience, Meibergdreef 47,1105 BA Amsterdam, The Netherlands
| | - Roxana Kooijmans
- Department of Vision and Cognition, Netherlands Institute for Neuroscience, Meibergdreef 47,1105 BA Amsterdam, The Netherlands
| | - Peter Christiaan Klink
- Department of Vision and Cognition, Netherlands Institute for Neuroscience, Meibergdreef 47,1105 BA Amsterdam, The Netherlands
- Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, The Netherlands
- Laboratory of Visual Brain Therapy, Sorbonne Université, Institut National de la Santé et de la Recherche Médicale, Centre National de la Recherche Scientifique, Institut de la Vision, Paris F-75012, France
| | - Christian Boehler
- Department of Microsystems Engineering (IMTEK), University of Freiburg, Georges-Köhler-Allee 103, 79110 Freiburg, Germany
- BrainLinks-BrainTools Center, University of Freiburg, Georges-Köhler-Allee 201, 79110 Freiburg, Germany
| | - Maria Asplund
- Department of Microsystems Engineering (IMTEK), University of Freiburg, Georges-Köhler-Allee 103, 79110 Freiburg, Germany
- BrainLinks-BrainTools Center, University of Freiburg, Georges-Köhler-Allee 201, 79110 Freiburg, Germany
- Freiburg Institute for Advanced Studies (FRIAS), University of Freiburg, Albertstraße 19, 79104 Freiburg, Germany
- Chalmers University of Technology, Chalmersplatsen 4, 412 96 Gothenburg, Sweden
| | - Pieter Roelf Roelfsema
- Department of Vision and Cognition, Netherlands Institute for Neuroscience, Meibergdreef 47,1105 BA Amsterdam, The Netherlands
- Laboratory of Visual Brain Therapy, Sorbonne Université, Institut National de la Santé et de la Recherche Médicale, Centre National de la Recherche Scientifique, Institut de la Vision, Paris F-75012, France
- Department of Integrative Neurophysiology, VU University, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands
- Department of Psychiatry, Academic Medical Center, Postbus 22660, 1100 DD Amsterdam, The Netherlands
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