1
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Zhang Y, Chen Y, Contera S, Compton RG. Double Electrode Experiments Reveal the Processes Occurring at PEDOT-Coated Neural Electrode Arrays. ACS APPLIED MATERIALS & INTERFACES 2024; 16:29439-29452. [PMID: 38775098 PMCID: PMC11163409 DOI: 10.1021/acsami.4c05204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 05/11/2024] [Accepted: 05/14/2024] [Indexed: 06/07/2024]
Abstract
Neural electrodes have recently been developed with surface modifications of conductive polymers, in particular poly(3,4-ethylenedioxythiophene) (PEDOT), and extensively studied for their roles in recording and stimulation, aiming to improve their biocompatibility. In this work, the implications for the design of practical neural sensors are clarified, and systematic procedures for their preparation are reported. In particular, this study introduces the use of in vitro double electrode experiments to mimic the responses of neural electrodes with a focus on signal-recording electrodes modified with PEDOT. Specifically, potential steps on one unmodified electrode in an array are used to identify the responses for PEDOT doped with different anions and compared with that of a bare platinum (Pt) electrode. The response is shown to be related to the rearrangement of ions in solution near the detector electrode resulting from the potential step, with a current transient seen at the detector electrode. A rapid response for PEDOT doped with chloride (ca. 0.04 s) ions was observed and attributed to the fast movement of chloride ions in and out of the polymer film. In contrast, PEDOT doped with poly(styrenesulfonate) (PSS) responds much slower (ca. 2.2 s), and the essential immobility of polyanion constrains the direction of current flow.
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Affiliation(s)
- Yuanmin Zhang
- Clarendon
Laboratory, Department of Physics, University
of Oxford, Parks Road, Oxford OX1
3PU, Great Britain
- Physical
and Theoretical Chemistry Laboratory, Department of Chemistry, University of Oxford, South Parks Road, Oxford OX1 3QZ, Great Britain
| | - Yuqi Chen
- Physical
and Theoretical Chemistry Laboratory, Department of Chemistry, University of Oxford, South Parks Road, Oxford OX1 3QZ, Great Britain
| | - Sonia Contera
- Clarendon
Laboratory, Department of Physics, University
of Oxford, Parks Road, Oxford OX1
3PU, Great Britain
| | - Richard G. Compton
- Physical
and Theoretical Chemistry Laboratory, Department of Chemistry, University of Oxford, South Parks Road, Oxford OX1 3QZ, Great Britain
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2
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Sun Y, Xiao Z, Chen B, Zhao Y, Dai J. Advances in Material-Assisted Electromagnetic Neural Stimulation. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024:e2400346. [PMID: 38594598 DOI: 10.1002/adma.202400346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 03/26/2024] [Indexed: 04/11/2024]
Abstract
Bioelectricity plays a crucial role in organisms, being closely connected to neural activity and physiological processes. Disruptions in the nervous system can lead to chaotic ionic currents at the injured site, causing disturbances in the local cellular microenvironment, impairing biological pathways, and resulting in a loss of neural functions. Electromagnetic stimulation has the ability to generate internal currents, which can be utilized to counter tissue damage and aid in the restoration of movement in paralyzed limbs. By incorporating implanted materials, electromagnetic stimulation can be targeted more accurately, thereby significantly improving the effectiveness and safety of such interventions. Currently, there have been significant advancements in the development of numerous promising electromagnetic stimulation strategies with diverse materials. This review provides a comprehensive summary of the fundamental theories, neural stimulation modulating materials, material application strategies, and pre-clinical therapeutic effects associated with electromagnetic stimulation for neural repair. It offers a thorough analysis of current techniques that employ materials to enhance electromagnetic stimulation, as well as potential therapeutic strategies for future applications.
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Affiliation(s)
- Yuting Sun
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhifeng Xiao
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Bing Chen
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Yannan Zhao
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Jianwu Dai
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Tianjin Key Laboratory of Biomedical Materials, Institute of Biomedical Engineering, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300192, China
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3
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Lee CH, Park YK, Lee K. Recent strategies for neural dynamics observation at a larger scale and wider scope. Biosens Bioelectron 2023; 240:115638. [PMID: 37647685 DOI: 10.1016/j.bios.2023.115638] [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: 04/14/2023] [Revised: 08/15/2023] [Accepted: 08/24/2023] [Indexed: 09/01/2023]
Abstract
The tremendous technical progress in neuroscience offers opportunities to observe a more minor or/and broader dynamic picture of the brain. Moreover, the large-scale neural activity of individual neurons enables the dissection of detailed mechanistic links between neural populations and behaviors. To measure neural activity in-vivo, multi-neuron recording, and neuroimaging techniques are employed and developed to acquire more neurons. The tools introduced concurrently recorded dozens to hundreds of neurons in the coordinated brain regions and elucidated the neuronal ensembles from a massive population perspective of diverse neurons at cellular resolution. In particular, the increasing spatiotemporal resolution of neuronal monitoring across the whole brain dramatically facilitates our understanding of additional nervous system functions in health and disease. Here, we will introduce state-of-the-art neuroscience tools involving large-scale neural population recording and the long-range connections spanning multiple brain regions. Their synergic effects provide to clarify the controversial circuitry underlying neuroscience. These challenging neural tools present a promising outlook for the fundamental dynamic interplay across levels of synaptic cellular, circuit organization, and brain-wide. Hence, more observations of neural dynamics will provide more clues to elucidate brain functions and push forward innovative technology at the intersection of neural engineering disciplines. We hope this review will provide insight into the use or development of recent neural techniques considering spatiotemporal scales of brain observation.
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Affiliation(s)
- Chang Hak Lee
- Department of Brain Sciences, Daegu Gyeongbuk Institute of Science & Technology (DGIST), Daegu, South Korea
| | - Young Kwon Park
- Department of Brain Sciences, Daegu Gyeongbuk Institute of Science & Technology (DGIST), Daegu, South Korea
| | - Kwang Lee
- Department of Brain Sciences, Daegu Gyeongbuk Institute of Science & Technology (DGIST), Daegu, South Korea.
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4
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Kass RE, Bong H, Olarinre M, Xin Q, Urban KN. Identification of interacting neural populations: methods and statistical considerations. J Neurophysiol 2023; 130:475-496. [PMID: 37465897 PMCID: PMC10642974 DOI: 10.1152/jn.00131.2023] [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: 03/29/2023] [Revised: 07/17/2023] [Accepted: 07/17/2023] [Indexed: 07/20/2023] Open
Abstract
As improved recording technologies have created new opportunities for neurophysiological investigation, emphasis has shifted from individual neurons to multiple populations that form circuits, and it has become important to provide evidence of cross-population coordinated activity. We review various methods for doing so, placing them in six major categories while avoiding technical descriptions and instead focusing on high-level motivations and concerns. Our aim is to indicate what the methods can achieve and the circumstances under which they are likely to succeed. Toward this end, we include a discussion of four cross-cutting issues: the definition of neural populations, trial-to-trial variability and Poisson-like noise, time-varying dynamics, and causality.
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Affiliation(s)
- Robert E Kass
- Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
- Department of Statistics & Data Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
| | - Heejong Bong
- Department of Statistics & Data Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
| | - Motolani Olarinre
- Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
- Department of Statistics & Data Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
| | - Qi Xin
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
- Department of Statistics & Data Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
| | - Konrad N Urban
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
- Department of Statistics & Data Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
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5
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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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6
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Mu X, Chen FD, Dang KM, Brunk MGK, Li J, Wahn H, Stalmashonak A, Ding P, Luo X, Chua H, Lo GQ, Poon JKS, Sacher WD. Implantable photonic neural probes with 3D-printed microfluidics and applications to uncaging. Front Neurosci 2023; 17:1213265. [PMID: 37521687 PMCID: PMC10373094 DOI: 10.3389/fnins.2023.1213265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 06/13/2023] [Indexed: 08/01/2023] Open
Abstract
Advances in chip-scale photonic-electronic integration are enabling a new generation of foundry-manufacturable implantable silicon neural probes incorporating nanophotonic waveguides and microelectrodes for optogenetic stimulation and electrophysiological recording in neuroscience research. Further extending neural probe functionalities with integrated microfluidics is a direct approach to achieve neurochemical injection and sampling capabilities. In this work, we use two-photon polymerization 3D printing to integrate microfluidic channels onto photonic neural probes, which include silicon nitride nanophotonic waveguides and grating emitters. The customizability of 3D printing enables a unique geometry of microfluidics that conforms to the shape of each neural probe, enabling integration of microfluidics with a variety of existing neural probes while avoiding the complexities of monolithic microfluidics integration. We demonstrate the photonic and fluidic functionalities of the neural probes via fluorescein injection in agarose gel and photoloysis of caged fluorescein in solution and in fixed brain tissue.
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Affiliation(s)
- Xin Mu
- Max Planck Institute of Microstructure Physics, Halle, Germany
- Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada
| | - Fu-Der Chen
- Max Planck Institute of Microstructure Physics, Halle, Germany
- Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada
- Max Planck-University of Toronto Centre for Neural Science and Technology, Toronto, ON, Canada
| | - Ka My Dang
- Max Planck Institute of Microstructure Physics, Halle, Germany
- Max Planck-University of Toronto Centre for Neural Science and Technology, Toronto, ON, Canada
| | - Michael G. K. Brunk
- Max Planck Institute of Microstructure Physics, Halle, Germany
- Max Planck-University of Toronto Centre for Neural Science and Technology, Toronto, ON, Canada
| | - Jianfeng Li
- Max Planck Institute of Microstructure Physics, Halle, Germany
- Max Planck-University of Toronto Centre for Neural Science and Technology, Toronto, ON, Canada
| | - Hannes Wahn
- Max Planck Institute of Microstructure Physics, Halle, Germany
| | | | - Peisheng Ding
- Max Planck Institute of Microstructure Physics, Halle, Germany
- Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada
| | - Xianshu Luo
- Advanced Micro Foundry Pte. Ltd., Singapore, Singapore
| | - Hongyao Chua
- Advanced Micro Foundry Pte. Ltd., Singapore, Singapore
| | - Guo-Qiang Lo
- Advanced Micro Foundry Pte. Ltd., Singapore, Singapore
| | - Joyce K. S. Poon
- Max Planck Institute of Microstructure Physics, Halle, Germany
- Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada
- Max Planck-University of Toronto Centre for Neural Science and Technology, Toronto, ON, Canada
| | - Wesley D. Sacher
- Max Planck Institute of Microstructure Physics, Halle, Germany
- Max Planck-University of Toronto Centre for Neural Science and Technology, Toronto, ON, Canada
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7
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Luan L, Yin R, Zhu H, Xie C. Emerging Penetrating Neural Electrodes: In Pursuit of Large Scale and Longevity. Annu Rev Biomed Eng 2023; 25:185-205. [PMID: 37289556 PMCID: PMC11078330 DOI: 10.1146/annurev-bioeng-090622-050507] [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: 06/10/2023]
Abstract
Penetrating neural electrodes provide a powerful approach to decipher brain circuitry by allowing for time-resolved electrical detections of individual action potentials. This unique capability has contributed tremendously to basic and translational neuroscience, enabling both fundamental understandings of brain functions and applications of human prosthetic devices that restore crucial sensations and movements. However, conventional approaches are limited by the scarce number of available sensing channels and compromised efficacy over long-term implantations. Recording longevity and scalability have become the most sought-after improvements in emerging technologies. In this review, we discuss the technological advances in the past 5-10 years that have enabled larger-scale, more detailed, and longer-lasting recordings of neural circuits at work than ever before. We present snapshots of the latest advances in penetration electrode technology, showcase their applications in animal models and humans, and outline the underlying design principles and considerations to fuel future technological development.
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Affiliation(s)
- Lan Luan
- Department of Electrical and Computer Engineering, Rice University, Houston, Texas, USA;
- Rice Neuroengineering Initiative, Rice University, Houston, Texas, USA
- Department of Bioengineering, Rice University, Houston, Texas, USA
| | - Rongkang Yin
- Department of Electrical and Computer Engineering, Rice University, Houston, Texas, USA;
- Rice Neuroengineering Initiative, Rice University, Houston, Texas, USA
| | - Hanlin Zhu
- Department of Electrical and Computer Engineering, Rice University, Houston, Texas, USA;
- Rice Neuroengineering Initiative, Rice University, Houston, Texas, USA
| | - Chong Xie
- Department of Electrical and Computer Engineering, Rice University, Houston, Texas, USA;
- Rice Neuroengineering Initiative, Rice University, Houston, Texas, USA
- Department of Bioengineering, Rice University, Houston, Texas, USA
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8
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Cornuéjols R, Albon A, Joshi S, Taylor JA, Baca M, Drakopoulou S, Rinaldi Barkat T, Bernard C, Rezaei-Mazinani S. Design, Characterization, and In Vivo Application of Multi-Conductive Layer Organic Electrocorticography Probes. ACS APPLIED MATERIALS & INTERFACES 2023; 15:22854-22863. [PMID: 37141163 DOI: 10.1021/acsami.3c00553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Biocompatible and plastic neural interface devices allow for minimally invasive recording of brain activity. Increasing electrode density in such devices is essential for high-resolution neural recordings. Superimposing conductive leads in devices can help multiply the number of recording sites while keeping probes width small and suitable for implantation. However, because of leads' vertical proximity, this can create capacitive coupling (CC) between overlapping channels, which leads to crosstalk. Here, we present a thorough investigation of CC phenomenon in multi-gold layer thin-film multi-electrode arrays with a parylene C (PaC) insulation layer between superimposed leads. We also propose a guideline on the design, fabrication, and characterization of such type of neural interface devices for high spatial resolution recording. Our results demonstrate that the capacitance created through CC between superimposed tracks decreases non-linearly and then linearly with the increase of insulation thickness. We identify an optimal PaC insulation thickness that leads to a drastic reduction of CC between superimposed gold channels while not significantly increasing the overall device thickness. Finally, we show that double gold layer electrocorticography probes with the optimal insulation thickness exhibit similar performances in vivo when compared to single-layer devices. This confirms that these probes are adequate for high-quality neural recordings.
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Affiliation(s)
- Rémy Cornuéjols
- Mines Saint-Etienne, Centre CMP, Departement BEL, F-13541 Gardanne, France
- Aix Marseille University, INSERM, INS, Inst Neurosci Syst, 13005 Marseille, France
| | - Amélie Albon
- Mines Saint-Etienne, Centre CMP, Departement BEL, F-13541 Gardanne, France
| | - Suyash Joshi
- Department of Biomedicine, Basel University, 4056 Basel, Switzerland
| | | | - Martin Baca
- Mines Saint-Etienne, Centre CMP, Departement BEL, F-13541 Gardanne, France
| | - Sofia Drakopoulou
- Mines Saint-Etienne, Centre CMP, Departement BEL, F-13541 Gardanne, France
| | | | - Christophe Bernard
- Aix Marseille University, INSERM, INS, Inst Neurosci Syst, 13005 Marseille, France
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9
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Vatsyayan R, Lee J, Bourhis AM, Tchoe Y, Cleary DR, Tonsfeldt KJ, Lee K, Montgomery-Walsh R, Paulk AC, U HS, Cash SS, Dayeh SA. Electrochemical and electrophysiological considerations for clinical high channel count neural interfaces. MRS BULLETIN 2023; 48:531-546. [PMID: 37476355 PMCID: PMC10357958 DOI: 10.1557/s43577-023-00537-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 04/10/2023] [Indexed: 07/22/2023]
Abstract
Electrophysiological recording and stimulation are the gold standard for functional mapping during surgical and therapeutic interventions as well as capturing cellular activity in the intact human brain. A critical component probing human brain activity is the interface material at the electrode contact that electrochemically transduces brain signals to and from free charge carriers in the measurement system. Here, we summarize state-of-the-art electrode array systems in the context of translation for use in recording and stimulating human brain activity. We leverage parametric studies with multiple electrode materials to shed light on the varied levels of suitability to enable high signal-to-noise electrophysiological recordings as well as safe electrophysiological stimulation delivery. We discuss the effects of electrode scaling for recording and stimulation in pursuit of high spatial resolution, channel count electrode interfaces, delineating the electrode-tissue circuit components that dictate the electrode performance. Finally, we summarize recent efforts in the connectorization and packaging for high channel count electrode arrays and provide a brief account of efforts toward wireless neuronal monitoring systems.
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Affiliation(s)
- Ritwik Vatsyayan
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, USA
| | - Jihwan Lee
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, USA
| | - Andrew M. Bourhis
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, USA
| | - Youngbin Tchoe
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, USA
| | - Daniel R. Cleary
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, USA; Department of Neurological Surgery, School of Medicine, Oregon Health & Science University, Portland, USA
| | - Karen J. Tonsfeldt
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, USA; Department of Obstetrics, Gynecology, and Reproductive Sciences, Center for Reproductive Science and Medicine, University of California, San Diego, San Diego, USA
| | - Keundong Lee
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, USA
| | - Rhea Montgomery-Walsh
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, USA; Department of Bioengineering, University of California, San Diego, San Diego, USA
| | - Angelique C. Paulk
- Department of Neurology, Harvard Medical School, Boston, USA; Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, USA
| | - Hoi Sang U
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, USA
| | - Sydney S. Cash
- Department of Neurology, Harvard Medical School, Boston, USA; Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, USA
| | - Shadi A. Dayeh
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, USA; Department of Bioengineering, University of California, San Diego, San Diego, USA
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10
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Suzuki I, Matsuda N, Han X, Noji S, Shibata M, Nagafuku N, Ishibashi Y. Large-Area Field Potential Imaging Having Single Neuron Resolution Using 236 880 Electrodes CMOS-MEA Technology. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023:e2207732. [PMID: 37088859 PMCID: PMC10369302 DOI: 10.1002/advs.202207732] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 03/21/2023] [Indexed: 05/03/2023]
Abstract
The electrophysiological technology having a high spatiotemporal resolution at the single-cell level and noninvasive measurements of large areas provide insights on underlying neuronal function. Here, a complementary metal-oxide semiconductor (CMOS)-microelectrode array (MEA) is used that uses 236 880 electrodes each with an electrode size of 11.22 × 11.22 µm and 236 880 covering a wide area of 5.5 × 5.9 mm in presenting a detailed and single-cell-level neural activity analysis platform for brain slices, human iPS cell-derived cortical networks, peripheral neurons, and human brain organoids. Propagation pattern characteristics between brain regions changes the synaptic propagation into compounds based on single-cell time-series patterns, classification based on single DRG neuron firing patterns and compound responses, axonal conduction characteristics and changes to anticancer drugs, and network activities and transition to compounds in brain organoids are extracted. This detailed analysis of neural activity at the single-cell level using the CMOS-MEA provides a new understanding of the basic mechanisms of brain circuits in vitro and ex vivo, on human neurological diseases for drug discovery, and compound toxicity assessment.
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Affiliation(s)
- Ikuro Suzuki
- Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
| | - Naoki Matsuda
- Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
| | - Xiaobo Han
- Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
| | - Shuhei Noji
- Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
| | - Mikako Shibata
- Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
| | - Nami Nagafuku
- Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
| | - Yuto Ishibashi
- Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
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11
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Shen K, Chen O, Edmunds JL, Piech DK, Maharbiz MM. Translational opportunities and challenges of invasive electrodes for neural interfaces. Nat Biomed Eng 2023; 7:424-442. [PMID: 37081142 DOI: 10.1038/s41551-023-01021-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 02/15/2023] [Indexed: 04/22/2023]
Abstract
Invasive brain-machine interfaces can restore motor, sensory and cognitive functions. However, their clinical adoption has been hindered by the surgical risk of implantation and by suboptimal long-term reliability. In this Review, we highlight the opportunities and challenges of invasive technology for clinically relevant electrophysiology. Specifically, we discuss the characteristics of neural probes that are most likely to facilitate the clinical translation of invasive neural interfaces, describe the neural signals that can be acquired or produced by intracranial electrodes, the abiotic and biotic factors that contribute to their failure, and emerging neural-interface architectures.
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Affiliation(s)
- Konlin Shen
- University of California, Berkeley - University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA, USA.
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA, USA.
| | - Oliver Chen
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA, USA
| | - Jordan L Edmunds
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA, USA
| | - David K Piech
- University of California, Berkeley - University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA, USA
| | - Michel M Maharbiz
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA, USA
- Department of Bioengineering, University of California, Berkeley, CA, USA
- Chan-Zuckerberg Biohub, San Francisco, CA, USA
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12
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Rogers KE, Nag OK, Susumu K, Oh E, Delehanty JB. Photothermal-Enhanced Modulation of Cellular Membrane Potential Using Long-Wavelength-Activated Gold Nanoflowers. Bioconjug Chem 2023; 34:405-413. [PMID: 36731145 DOI: 10.1021/acs.bioconjchem.2c00567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
In mammalian cells, plasma membrane potential plays vital roles in both physiology and pathology and it is controlled by a network of membrane-resident ion channels. There is considerable interest in the use of nanoparticles (NPs) to control biological functions, including the modulation of membrane potential. The photoexcitation of gold NPs (AuNPs) tethered close to the plasma membrane has been shown to induce membrane depolarization via localized heating of the AuNP surface coupled with the opening of voltage-gated sodium channels. Previous work has employed spherical AuNPs (AuNS) with absorption in the 500-600 nm range for this purpose. However, AuNP materials with absorption at longer wavelengths [e.g., near-infrared (NIR)] would enable greater tissue penetration depth in vivo. We show here the use of new anisotropic-shaped AuNPs [gold nanoflowers (AuNFs)] with broad absorption spanning into the NIR part of the spectrum (∼650-1000 nm). The AuNFs are directly synthesized with bidentate thiolate ligands, which preserves the AuNF's shape and colloidal stability, while facilitating conjugation to biomolecules. We describe the characterization of the AuNF particles and demonstrate that they adhere to the plasma membrane when bioconjugated to PEGylated cholesterol (PEG-Chol) moieties. The AuNF-PEG-Chol mediated the depolarization of rat adrenal medulla pheochromocytoma (PC-12) neuron-like cells more effectively than AuNS-PEG-Chol and unconjugated AuNS and AuNF when photoexcited at ∼561 or ∼640 nm. Importantly, AuNF induction of depolarization had no impact on cellular viability. This work demonstrates anisotropic AuNFs as an enabling nanomaterial for use in cellular depolarization and the spatiotemporal control of cellular activity.
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Affiliation(s)
- Katherine E Rogers
- Center for Bio/Molecular Science and Engineering, U.S. Naval Research Laboratory, Washington, District of Columbia 20375, United States.,Fischell Department of Bioengineering, University of Maryland, College Park, Maryland 20742, United States
| | - Okhil K Nag
- Center for Bio/Molecular Science and Engineering, U.S. Naval Research Laboratory, Washington, District of Columbia 20375, United States
| | - Kimihiro Susumu
- Optical Sciences Division, U.S. Naval Research Laboratory, Washington, District of Columbia 20375, United States.,Jacobs Corporation, Hanover, Maryland 21076, United States
| | - Eunkeu Oh
- Optical Sciences Division, U.S. Naval Research Laboratory, Washington, District of Columbia 20375, United States
| | - James B Delehanty
- Center for Bio/Molecular Science and Engineering, U.S. Naval Research Laboratory, Washington, District of Columbia 20375, United States
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13
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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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14
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Zhao C, Man T, Cao Y, Weiss PS, Monbouquette HG, Andrews AM. Flexible and Implantable Polyimide Aptamer-Field-Effect Transistor Biosensors. ACS Sens 2022; 7:3644-3653. [PMID: 36399772 PMCID: PMC9982941 DOI: 10.1021/acssensors.2c01909] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Monitoring neurochemical signaling across time scales is critical to understanding how brains encode and store information. Flexible (vs stiff) devices have been shown to improve in vivo monitoring, particularly over longer times, by reducing tissue damage and immunological responses. Here, we report our initial steps toward developing flexible and implantable neuroprobes with aptamer-field-effect transistor (FET) biosensors for neurotransmitter monitoring. A high-throughput process was developed to fabricate thin, flexible polyimide probes using microelectromechanical-system (MEMS) technologies, where 150 flexible probes were fabricated on each 4 in. Si wafer. Probes were 150 μm wide and 7 μm thick with two FETs per tip. The bending stiffness was 1.2 × 10-11 N·m2. Semiconductor thin films (3 nm In2O3) were functionalized with DNA aptamers for target recognition, which produces aptamer conformational rearrangements detected via changes in FET conductance. Flexible aptamer-FET neuroprobes detected serotonin at femtomolar concentrations in high-ionic strength artificial cerebrospinal fluid. A straightforward implantation process was developed, where microfabricated Si carrier devices assisted with implantation such that flexible neuroprobes detected physiological relevant serotonin in a tissue-hydrogel brain mimic.
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Affiliation(s)
- Chuanzhen Zhao
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, California 90095, United States,California NanoSystems Institute, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Tianxing Man
- Department of Mechanical and Aerospace Engineering, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Yan Cao
- California NanoSystems Institute, University of California, Los Angeles, Los Angeles, California 90095, United States,Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Paul S. Weiss
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, California 90095, United States,California NanoSystems Institute, University of California, Los Angeles, Los Angeles, California 90095, United States,Departments of Bioengineering and Materials Science and Engineering, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Harold G. Monbouquette
- California NanoSystems Institute, University of California, Los Angeles, Los Angeles, California 90095, United States,Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Anne M. Andrews
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, California 90095, United States,California NanoSystems Institute, University of California, Los Angeles, Los Angeles, California 90095, United States,Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience & Human Behavior, and Hatos Center for Neuropharmacology, University of California, Los Angeles, Los Angeles, California 90095, United States,To whom correspondence should be addressed to:
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15
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Wang Y, Liu S, Wang H, Zhao Y, Zhang XD. Neuron devices: emerging prospects in neural interfaces and recognition. MICROSYSTEMS & NANOENGINEERING 2022; 8:128. [PMID: 36507057 PMCID: PMC9726942 DOI: 10.1038/s41378-022-00453-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 08/28/2022] [Accepted: 08/30/2022] [Indexed: 06/17/2023]
Abstract
Neuron interface devices can be used to explore the relationships between neuron firing and synaptic transmission, as well as to diagnose and treat neurological disorders, such as epilepsy and Alzheimer's disease. It is crucial to exploit neuron devices with high sensitivity, high biocompatibility, multifunctional integration and high-speed data processing. During the past decades, researchers have made significant progress in neural electrodes, artificial sensory neuron devices, and neuromorphic optic neuron devices. The main part of the review is divided into two sections, providing an overview of recently developed neuron interface devices for recording electrophysiological signals, as well as applications in neuromodulation, simulating the human sensory system, and achieving memory and recognition. We mainly discussed the development, characteristics, functional mechanisms, and applications of neuron devices and elucidated several key points for clinical translation. The present review highlights the advances in neuron devices on brain-computer interfaces and neuroscience research.
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Affiliation(s)
- Yang Wang
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, 300072 Tianjin, China
| | - Shuangjie Liu
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, 300072 Tianjin, China
| | - Hao Wang
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, 300072 Tianjin, China
| | - Yue Zhao
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, 300072 Tianjin, China
| | - Xiao-Dong Zhang
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, 300072 Tianjin, China
- Tianjin Key Laboratory of Low Dimensional Materials Physics and Preparing Technology, Institute of Advanced Materials Physics, School of Sciences, Tianjin University, 300350 Tianjin, China
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16
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Cha JH, Park JH, Park Y, Shin H, Hwang KS, Cho IJ, Kim SJ. A CMOS Microelectrode Array System With Reconfigurable Sub-Array Multiplexing Architecture Integrating 24,320 Electrodes and 380 Readout Channels. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2022; 16:1044-1056. [PMID: 36191109 DOI: 10.1109/tbcas.2022.3211275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
This article presents a CMOS microelectrode array (MEA) system with a reconfigurable sub-array multiplexing architecture using the time-division multiplexing (TDM) technique. The system consists of 24,320 TiN electrodes with 17.7 μm-pitch pixels and 380 column-parallel readout channels including a low-noise amplifier, a programmable gain amplifier, and a 10-b successive approximation register analog to digital converter. Readout channels are placed outside the pixel for high spatial resolution, and a flexible structure to acquire neural signals from electrodes selected by configuring in-pixel memory is realized. In this structure, a single channel can handle 8 to 32 electrodes, guaranteeing a temporal resolution from 5 kS/s to 20 kS/s for each electrode. A 128 × 190 MEA system was fabricated in a 110-nm CMOS process, and each readout channel consumes 81 μW at 1.5-V supply voltage featuring input-referred noise of 1.48 μVrms without multiplexing and 5.4 μVrms with multiplexing at the action-potential band (300 Hz-10 kHz).
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17
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Erofeev A, Antifeev I, Bolshakova A, Bezprozvanny I, Vlasova O. In Vivo Penetrating Microelectrodes for Brain Electrophysiology. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22239085. [PMID: 36501805 PMCID: PMC9735502 DOI: 10.3390/s22239085] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 11/14/2022] [Accepted: 11/22/2022] [Indexed: 05/13/2023]
Abstract
In recent decades, microelectrodes have been widely used in neuroscience to understand the mechanisms behind brain functions, as well as the relationship between neural activity and behavior, perception and cognition. However, the recording of neuronal activity over a long period of time is limited for various reasons. In this review, we briefly consider the types of penetrating chronic microelectrodes, as well as the conductive and insulating materials for microelectrode manufacturing. Additionally, we consider the effects of penetrating microelectrode implantation on brain tissue. In conclusion, we review recent advances in the field of in vivo microelectrodes.
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Affiliation(s)
- Alexander Erofeev
- Laboratory of Molecular Neurodegeneration, Graduate School of Biomedical Systems and Technologies, Institute of Biomedical Systems and Biotechnology, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia
- Correspondence: (A.E.); (O.V.)
| | - Ivan Antifeev
- Laboratory of Methods and Instruments for Genetic and Immunoassay Analysis, Institute for Analytical Instrumentation of the Russian Academy of Sciences, 198095 Saint Petersburg, Russia
| | - Anastasia Bolshakova
- Laboratory of Molecular Neurodegeneration, Graduate School of Biomedical Systems and Technologies, Institute of Biomedical Systems and Biotechnology, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia
| | - Ilya Bezprozvanny
- Laboratory of Molecular Neurodegeneration, Graduate School of Biomedical Systems and Technologies, Institute of Biomedical Systems and Biotechnology, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia
- Department of Physiology, University of Texas Southwestern Medical Center at Dallas, Dallas, TX 75390, USA
| | - Olga Vlasova
- Laboratory of Molecular Neurodegeneration, Graduate School of Biomedical Systems and Technologies, Institute of Biomedical Systems and Biotechnology, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia
- Correspondence: (A.E.); (O.V.)
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18
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Lee JM, Lin D, Hong G, Kim KH, Park HG, Lieber CM. Scalable Three-Dimensional Recording Electrodes for Probing Biological Tissues. NANO LETTERS 2022; 22:4552-4559. [PMID: 35583378 DOI: 10.1021/acs.nanolett.2c01444] [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] [Indexed: 06/15/2023]
Abstract
Electrophysiological recording technologies can provide critical insight into the function of the nervous system and other biological tissues. Standard silicon-based probes have limitations, including single-sided recording sites and intrinsic instabilities due to the probe stiffness. Here, we demonstrate high-performance neural recording using double-sided three-dimensional (3D) electrodes integrated in an ultraflexible bioinspired open mesh structure, allowing electrodes to sample fully the 3D interconnected tissue of the brain. In vivo electrophysiological recording using 3D electrodes shows statistically significant increases in the number of neurons per electrode, average spike amplitudes, and signal to noise ratios in comparison to standard two-dimensional electrodes, while achieving stable detection of single-neuron activity over months. The capability of these 3D electrodes is further shown for chronic recording from retinal ganglion cells in mice. This approach opens new opportunities for a comprehensive 3D interrogation, stimulation, and understanding of the complex circuitry of the brain and other electrogenic tissues in live animals over extended time periods.
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Affiliation(s)
- Jung Min Lee
- Department of Physics, Korea University, Seoul 02841, Republic of Korea
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Dingchang Lin
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
- Department of Materials Science and Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Guosong Hong
- Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, United States
| | - Kyoung-Ho Kim
- Department of Physics, Korea University, Seoul 02841, Republic of Korea
- Department of Physics, Chungbuk National University, Cheongju 28644, Republic of Korea
| | - Hong-Gyu Park
- Department of Physics, Korea University, Seoul 02841, Republic of Korea
- KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul 02841, Republic of Korea
| | - Charles M Lieber
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
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19
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Bhaskara S, Sakorikar T, Chatterjee S, Shabari Girishan K, Pandya HJ. Recent advancements in Micro-engineered devices for surface and deep brain animal studies: A review. SENSING AND BIO-SENSING RESEARCH 2022. [DOI: 10.1016/j.sbsr.2022.100483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
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20
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Wei C, Wang Y, Pei W, Han X, Lin L, Liu Z, Ming G, Chen R, Wu P, Yang X, Zheng L, Wang Y. Distributed implantation of a flexible microelectrode array for neural recording. MICROSYSTEMS & NANOENGINEERING 2022; 8:50. [PMID: 35572780 PMCID: PMC9098495 DOI: 10.1038/s41378-022-00366-2] [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: 11/08/2021] [Revised: 01/14/2022] [Accepted: 02/02/2022] [Indexed: 06/15/2023]
Abstract
Flexible multichannel electrode arrays (fMEAs) with multiple filaments can be flexibly implanted in various patterns. It is necessary to develop a method for implanting the fMEA in different locations and at various depths based on the recording demands. This study proposed a strategy for reducing the microelectrode volume with integrated packaging. An implantation system was developed specifically for semiautomatic distributed implantation. The feasibility and convenience of the fMEA and implantation platform were verified in rodents. The acute and chronic recording results provied the effectiveness of the packaging and implantation methods. These methods could provide a novel strategy for developing fMEAs with more filaments and recording sites to measure functional interactions across multiple brain regions.
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Affiliation(s)
- Chunrong Wei
- State Key Laboratory of Integrated Optoelectronics, Institute of Semiconductors, Chinese Academy of Sciences, 100083 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- School of Future Technologies, University of Chinese Academy of Sciences, 100049 Beijing, China
| | - Yang Wang
- State Key Laboratory of Integrated Optoelectronics, Institute of Semiconductors, Chinese Academy of Sciences, 100083 Beijing, China
- School of Microelectronics, University of Sciences and Technology of China, 230000 Hefei, China
| | - Weihua Pei
- State Key Laboratory of Integrated Optoelectronics, Institute of Semiconductors, Chinese Academy of Sciences, 100083 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
| | - Xinyong Han
- Institute of Automation, Chinese Academy of Sciences, 100190 Beijing, China
| | - Longnian Lin
- Key Laboratory of Brain Functional Genomics, East China Normal University, 200062 Shanghai, China
| | - Zhiduo Liu
- State Key Laboratory of Integrated Optoelectronics, Institute of Semiconductors, Chinese Academy of Sciences, 100083 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
| | - Gege Ming
- State Key Laboratory of Integrated Optoelectronics, Institute of Semiconductors, Chinese Academy of Sciences, 100083 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- School of Future Technologies, University of Chinese Academy of Sciences, 100049 Beijing, China
| | - Ruru Chen
- Brain Machine Fusion Intelligence Institute, 215131 Suzhou, China
| | - Pingping Wu
- University of Chinese Academy of Sciences, 100049 Beijing, China
- School of Future Technologies, University of Chinese Academy of Sciences, 100049 Beijing, China
- Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, 100190 Beijing, China
| | - Xiaowei Yang
- State Key Laboratory of Integrated Optoelectronics, Institute of Semiconductors, Chinese Academy of Sciences, 100083 Beijing, China
| | - Li Zheng
- State Key Laboratory of Integrated Optoelectronics, Institute of Semiconductors, Chinese Academy of Sciences, 100083 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- School of Future Technologies, University of Chinese Academy of Sciences, 100049 Beijing, China
| | - Yijun Wang
- State Key Laboratory of Integrated Optoelectronics, Institute of Semiconductors, Chinese Academy of Sciences, 100083 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
- Chinese Institute for Brain Research, 102206 Beijing, China
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21
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Lim J, Lee J, Moon E, Barrow M, Atzeni G, Letner JG, Costello JT, Nason SR, Patel PR, Sun Y, Patil PG, Kim HS, Chestek CA, Phillips J, Blaauw D, Sylvester D, Jang T. A Light-Tolerant Wireless Neural Recording IC for Motor Prediction With Near-Infrared-Based Power and Data Telemetry. IEEE JOURNAL OF SOLID-STATE CIRCUITS 2022; 57:1061-1074. [PMID: 36186085 PMCID: PMC9518712 DOI: 10.1109/jssc.2022.3141688] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Miniaturized and wireless near-infrared (NIR) based neural recorders with optical powering and data telemetry have been introduced as a promising approach for safe long-term monitoring with the smallest physical dimension among state-of-the-art standalone recorders. However, a main challenge for the NIR based neural recording ICs is to maintain robust operation in the presence of light-induced parasitic short circuit current from junction diodes. This is especially true when the signal currents are kept small to reduce power consumption. In this work, we present a light-tolerant and low-power neural recording IC for motor prediction that can fully function in up to 300 μW/mm2 of light exposure. It achieves best-in-class power consumption of 0.57 μW at 38° C with a 4.1 NEF pseudo-resistorless amplifier, an on-chip neural feature extractor, and individual mote level gain control. Applying the 20-channel pre-recorded neural signals of a monkey, the IC predicts finger position and velocity with correlation coefficient up to 0.870 and 0.569, respectively, with individual mote level gain control enabled. In addition, wireless measurement is demonstrated through optical power and data telemetry using a custom PV/LED GaAs chip wire bonded to the proposed IC.
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Affiliation(s)
- Jongyup Lim
- Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI, 48109 USA
| | - Jungho Lee
- Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI, 48109 USA
| | - Eunseong Moon
- Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI, 48109 USA
| | - Michael Barrow
- Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI, 48109 USA
| | - Gabriele Atzeni
- Department of Information Technology and Electrical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - Joseph G Letner
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, 48109 USA
| | - Joseph T Costello
- Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI, 48109 USA
| | - Samuel R Nason
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, 48109 USA
| | - Paras R Patel
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, 48109 USA
| | - Yi Sun
- Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI, 48109 USA
| | - Parag G Patil
- Department of Neurological Surgery, Neurology, Anesthesiology, and Biomedical Engineering, University of Michigan, Ann Arbor, MI, 48109 USA
| | - Hun-Seok Kim
- Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI, 48109 USA
| | - Cynthia A Chestek
- Department of Biomedical Engineering and Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, 48109 USA
| | - Jamie Phillips
- Department of Electrical and Computer Engineering, University of Delaware, Newark, DE 19716 USA
| | - David Blaauw
- Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI, 48109 USA
| | - Dennis Sylvester
- Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI, 48109 USA
| | - Taekwang Jang
- Department of Information Technology and Electrical Engineering, ETH Zürich, 8092 Zürich, Switzerland
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22
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Wang L, Ge C, Wang F, Guo Z, Hong W, Jiang C, Ji B, Wang M, Li C, Sun B, Liu J. Dense Packed Drivable Optrode Array for Precise Optical Stimulation and Neural Recording in Multiple-Brain Regions. ACS Sens 2021; 6:4126-4135. [PMID: 34779610 DOI: 10.1021/acssensors.1c01650] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
The input-output function of neural networks is complicated due to the huge number of neurons and synapses, and some high-density implantable electrophysiology recording tools with a plane structure have been developed for neural circuit studies in recent years. However, traditional plane probes are limited by the record-only function and inability to monitor multiple-brain regions simultaneously, and the complete cognition of neural networks still has a long way away. Herein, we develop a three-dimensional (3D) high-density drivable optrode array for multiple-brain recording and precise optical stimulation simultaneously. The optrode array contains four-layer probes with 1024 microelectrodes and two thinned optical fibers assembled into a 3D-printed drivable module. The recording performance of microelectrodes is optimized by electrochemical modification, and precise implantation depth control of drivable optrodes is verified in agar. Moreover, in vivo experiments indicate neural activities from CA1 and dentate gyrus regions are monitored, and a tracking of the neuron firing for 2 weeks is achieved. The suppression of neuron firing by blue light has been realized through high-density optrodes during optogenetics experiments. With the feature of large-scale recording, optoelectronic integration, and 3D assembly, the high-density drivable optrode array possesses an important value in the research of brain diseases and neural networks.
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Affiliation(s)
- Longchun Wang
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Chaofan Ge
- Institute of Neuroscience and Key Laboratory of Primate Neurobiology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Fang Wang
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200020, China
| | - Zhejun Guo
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Wen Hong
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Chunpeng Jiang
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Bowen Ji
- Unmanned System Research Institute, Northwestern Polytechnical University, Xi’an 710072, China
| | - Minghao Wang
- College of Electronics and Information Hangzhou Dianzi University, Hangzhou 310018, China
| | - Chengyu Li
- Institute of Neuroscience and Key Laboratory of Primate Neurobiology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Bomin Sun
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200020, China
| | - Jingquan Liu
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Shanghai Jiao Tong University, Shanghai 200240, China
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23
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Zhao C, Cheung KM, Huang IW, Yang H, Nakatsuka N, Liu W, Cao Y, Man T, Weiss PS, Monbouquette HG, Andrews AM. Implantable aptamer-field-effect transistor neuroprobes for in vivo neurotransmitter monitoring. SCIENCE ADVANCES 2021; 7:eabj7422. [PMID: 34818033 PMCID: PMC8612678 DOI: 10.1126/sciadv.abj7422] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
While tools for monitoring in vivo electrophysiology have been extensively developed, neurochemical recording technologies remain limited. Nevertheless, chemical communication via neurotransmitters plays central roles in brain information processing. We developed implantable aptamer–field-effect transistor (FET) neuroprobes for monitoring neurotransmitters. Neuroprobes were fabricated using high-throughput microelectromechanical system (MEMS) technologies, where 150 probes with shanks of either 150- or 50-μm widths and thicknesses were fabricated on 4-inch Si wafers. Nanoscale FETs with ultrathin (~3 to 4 nm) In2O3 semiconductor films were prepared using sol-gel processing. The In2O3 surfaces were coupled with synthetic oligonucleotide receptors (aptamers) to recognize and to detect the neurotransmitter serotonin. Aptamer-FET neuroprobes enabled femtomolar serotonin detection limits in brain tissue with minimal biofouling. Stimulated serotonin release was detected in vivo. This study opens opportunities for integrated neural activity recordings at high spatiotemporal resolution by combining these aptamer-FET sensors with other types of Si-based implantable probes to advance our understanding of brain function.
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Affiliation(s)
- Chuanzhen Zhao
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
- California NanoSystems Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Kevin M. Cheung
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
- California NanoSystems Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - I-Wen Huang
- California NanoSystems Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Hongyan Yang
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, Hatos Center for Neuropharmacology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Nako Nakatsuka
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
- California NanoSystems Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Wenfei Liu
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
- California NanoSystems Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Yan Cao
- California NanoSystems Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Tianxing Man
- Department of Mechanical and Aerospace Engineering, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Paul S. Weiss
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
- California NanoSystems Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Materials Science and Engineering, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Harold G. Monbouquette
- California NanoSystems Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Anne M. Andrews
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
- California NanoSystems Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, Hatos Center for Neuropharmacology, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Corresponding author.
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24
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Clay M, Monbouquette HG. Simulated Performance of Electroenzymatic Glutamate Biosensors In Vivo Illuminates the Complex Connection to Calibration In Vitro. ACS Chem Neurosci 2021; 12:4275-4285. [PMID: 34734695 DOI: 10.1021/acschemneuro.1c00365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Detailed simulations show that the relationship between electroenzymatic glutamate (Glut) sensor performance in vitro and that modeled in vivo is complicated by the influence of both resistances to mass transfer and clearance rates of Glut and H2O2 in the brain extracellular space (ECS). Mathematical modeling provides a powerful means to illustrate how these devices are expected to respond to a variety of conditions in vivo in ways that cannot be accomplished readily using existing experimental techniques. Through the use of transient model simulations in one spatial dimension, it is shown that the sensor response in vivo may exhibit much greater dependence on H2O2 mass transfer and clearance in the surrounding tissue than previously thought. This dependence may lead to sensor signals more than double the expected values (based on prior sensor calibration in vitro) for Glut release events within a few microns of the sensor surface. The sensor response in general is greatly affected by the distance between the device and location of Glut release, and apparent concentrations reported by simulated sensors consistently are well below the actual Glut levels for events occurring at distances greater than a few microns. Simulations of transient Glut concentrations, including a physiologically relevant bolus release, indicate that detection of Glut signaling likely is limited to events within 30 μm of the sensor surface based on representative sensor detection limits. It follows that important limitations also exist with respect to interpretation of decays in sensor signals, including relation of such data to actual Glut concentration declines in vivo. Thus, the use of sensor signal data to determine quantitatively the rates of Glut uptake from the brain ECS likely is problematic. The model is designed to represent a broad range of relevant physiological conditions, and although limited to one dimension, provides much needed guidance regarding the interpretation in general of electroenzymatic sensor data gathered in vivo.
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Affiliation(s)
- Mackenzie Clay
- Chemical and Biomolecular Engineering Department, University of California, Los Angeles, California 90095−1592, United States
| | - Harold G. Monbouquette
- Chemical and Biomolecular Engineering Department, University of California, Los Angeles, California 90095−1592, United States
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25
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Antonini MJ, Sahasrabudhe A, Tabet A, Schwalm M, Rosenfeld D, Garwood I, Park J, Loke G, Khudiyev T, Kanik M, Corbin N, Canales A, Jasanoff AP, Fink Y, Anikeeva P. Customizing MRI-Compatible Multifunctional Neural Interfaces through Fiber Drawing. ADVANCED FUNCTIONAL MATERIALS 2021; 31:2104857. [PMID: 34924913 PMCID: PMC8673858 DOI: 10.1002/adfm.202104857] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Indexed: 05/11/2023]
Abstract
Fiber drawing enables scalable fabrication of multifunctional flexible fibers that integrate electrical, optical and microfluidic modalities to record and modulate neural activity. Constraints on thermomechanical properties of materials, however, have prevented integrated drawing of metal electrodes with low-loss polymer waveguides for concurrent electrical recording and optical neuromodulation. Here we introduce two fabrication approaches: (1) an iterative thermal drawing with a soft, low melting temperature (Tm) metal indium, and (2) a metal convergence drawing with traditionally non-drawable high Tm metal tungsten. Both approaches deliver multifunctional flexible neural interfaces with low-impedance metallic electrodes and low-loss waveguides, capable of recording optically-evoked and spontaneous neural activity in mice over several weeks. We couple these fibers with a light-weight mechanical microdrive (1g) that enables depth-specific interrogation of neural circuits in mice following chronic implantation. Finally, we demonstrate the compatibility of these fibers with magnetic resonance imaging (MRI) and apply them to visualize the delivery of chemical payloads through the integrated channels in real time. Together, these advances expand the domains of application of the fiber-based neural probes in neuroscience and neuroengineering.
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Affiliation(s)
- Marc-Joseph Antonini
- Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Harvard/MIT Health Science & Technology Graduate Program, Cambridge, MA, 02139, USA
| | - Atharva Sahasrabudhe
- Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Anthony Tabet
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Miriam Schwalm
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Dekel Rosenfeld
- Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Indie Garwood
- Harvard/MIT Health Science & Technology Graduate Program, Cambridge, MA, 02139, USA
| | - Jimin Park
- Department of Materials Science & Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Gabriel Loke
- Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Tural Khudiyev
- Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Mehmet Kanik
- Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Kinetik Therapeutics LLC, Newton, MA, 02459, USA
| | - Nathan Corbin
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | | | - Alan P. Jasanoff
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Nuclear Science & Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Yoel Fink
- Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Advanced Functional Fabrics of America, Cambridge, MA, 02139 USA
- Department of Materials Science & Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Institute for Soldier Nanotechnologies, Massachusetts Institute of Technology, Cambridge, MA, 02139 USA
| | - Polina Anikeeva
- Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Materials Science & Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
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26
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Lee KH, Ni YL, Colonell J, Karsh B, Putzeys J, Pachitariu M, Harris TD, Meister M. Electrode pooling can boost the yield of extracellular recordings with switchable silicon probes. Nat Commun 2021; 12:5245. [PMID: 34475396 PMCID: PMC8413349 DOI: 10.1038/s41467-021-25443-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 07/28/2021] [Indexed: 11/09/2022] Open
Abstract
State-of-the-art silicon probes for electrical recording from neurons have thousands of recording sites. However, due to volume limitations there are typically many fewer wires carrying signals off the probe, which restricts the number of channels that can be recorded simultaneously. To overcome this fundamental constraint, we propose a method called electrode pooling that uses a single wire to serve many recording sites through a set of controllable switches. Here we present the framework behind this method and an experimental strategy to support it. We then demonstrate its feasibility by implementing electrode pooling on the Neuropixels 1.0 electrode array and characterizing its effect on signal and noise. Finally we use simulations to explore the conditions under which electrode pooling saves wires without compromising the content of the recordings. We make recommendations on the design of future devices to take advantage of this strategy.
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Affiliation(s)
- Kyu Hyun Lee
- Division of Biology and Biological Engineering, Caltech, Pasadena, CA, USA
| | - Yu-Li Ni
- Division of Biology and Biological Engineering, Caltech, Pasadena, CA, USA
| | | | - Bill Karsh
- HHMI Janelia Research Campus, Ashburn, VA, USA
| | | | | | | | - Markus Meister
- Division of Biology and Biological Engineering, Caltech, Pasadena, CA, USA.
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27
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Qiang Y, Gu W, Liu Z, Liang S, Ryu JH, Seo KJ, Liu W, Fang H. Crosstalk in Polymer Microelectrode Arrays. NANO RESEARCH 2021; 14:3240-3247. [PMID: 34394850 PMCID: PMC8361849 DOI: 10.1007/s12274-021-3442-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Thin-film polymer microelectrode arrays (MEAs) facilitate the high-resolution neural recording with its superior mechanical compliance. However, the densely packed electrodes and interconnects along with the ultra-thin polymeric encapsulation/substrate layers give rise to non-negligible crosstalk, which could result in severe interference in the neural signal recording. Due to the lack of standardized characterization or modeling of crosstalk in neural electrode arrays, to date, crosstalk in polymer MEAs remains poorly understood. In this work, the crosstalk between two adjacent polymer microelectrodes is measured experimentally and modeled using equivalent circuits. Importantly, this study demonstrated a two-well measuring platform and systematically characterized the crosstalk in polymer microelectrodes with true isolation of the victim channel and precise control of its grounding condition. A simple, unified equation from detailed circuit modeling was proposed to calculate the crosstalk in different environments. Finite element analysis (FEA) analysis was conducted further to explore the crosstalk in more aggressively scaled polymer electrode threads. In addition to standardizing neural electrode array crosstalk characterization, this study not only reveals the dependence of the crosstalk in polymer MEAs on a variety of key device parameters but also provides general guidelines for the design of thin polymer MEAs for high-quality neural signal recording.
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Affiliation(s)
- Yi Qiang
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA 02115, USA
- These authors contributed equally to this work
| | - Wen Gu
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA 02115, USA
- These authors contributed equally to this work
| | - Zehua Liu
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA 02115, USA
| | - Shanchuan Liang
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA 02115, USA
| | - Jae Hyeon Ryu
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA 02115, USA
| | - Kyung Jin Seo
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA 02115, USA
| | - Wentai Liu
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Hui Fang
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA 02115, USA
- Department of Bioengineering, Northeastern University, Boston, MA 02115, USA
- Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, USA
- Correspondence and requests for materials should be addressed to H.F. ()
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28
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Shokur S, Mazzoni A, Schiavone G, Weber DJ, Micera S. A modular strategy for next-generation upper-limb sensory-motor neuroprostheses. MED 2021; 2:912-937. [DOI: 10.1016/j.medj.2021.05.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Revised: 04/28/2021] [Accepted: 05/10/2021] [Indexed: 02/06/2023]
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29
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Wang D, Tan J, Zhu H, Mei Y, Liu X. Biomedical Implants with Charge-Transfer Monitoring and Regulating Abilities. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2021; 8:e2004393. [PMID: 34166584 PMCID: PMC8373130 DOI: 10.1002/advs.202004393] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 05/12/2021] [Indexed: 05/06/2023]
Abstract
Transmembrane charge (ion/electron) transfer is essential for maintaining cellular homeostasis and is involved in many biological processes, from protein synthesis to embryonic development in organisms. Designing implant devices that can detect or regulate cellular transmembrane charge transfer is expected to sense and modulate the behaviors of host cells and tissues. Thus, charge transfer can be regarded as a bridge connecting living systems and human-made implantable devices. This review describes the mode and mechanism of charge transfer between organisms and nonliving materials, and summarizes the strategies to endow implants with charge-transfer regulating or monitoring abilities. Furthermore, three major charge-transfer controlling systems, including wired, self-activated, and stimuli-responsive biomedical implants, as well as the design principles and pivotal materials are systematically elaborated. The clinical challenges and the prospects for future development of these implant devices are also discussed.
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Affiliation(s)
- Donghui Wang
- State Key Laboratory of High Performance Ceramics and Superfine MicrostructureShanghai Institutes of CeramicsChinese Academy of SciencesShanghai200050China
- School of Materials Science and EngineeringHebei University of TechnologyTianjin300130China
| | - Ji Tan
- State Key Laboratory of High Performance Ceramics and Superfine MicrostructureShanghai Institutes of CeramicsChinese Academy of SciencesShanghai200050China
| | - Hongqin Zhu
- State Key Laboratory of High Performance Ceramics and Superfine MicrostructureShanghai Institutes of CeramicsChinese Academy of SciencesShanghai200050China
- Department of Materials ScienceFudan UniversityShanghai200433China
| | - Yongfeng Mei
- Department of Materials ScienceFudan UniversityShanghai200433China
| | - Xuanyong Liu
- State Key Laboratory of High Performance Ceramics and Superfine MicrostructureShanghai Institutes of CeramicsChinese Academy of SciencesShanghai200050China
- School of Chemistry and Materials ScienceHangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou310024China
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30
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Chen L, Hartner J, Dong T, Li A, Watson B, Shih A. Flexible High-Resolution Force and Dimpling Measurement System for Pia and Dura Penetration During In Vivo Microelectrode Insertion Into Rat Brain. IEEE Trans Biomed Eng 2021; 68:2602-2612. [PMID: 33798065 PMCID: PMC8323825 DOI: 10.1109/tbme.2021.3070781] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
OBJECTIVE Understanding the in vivo force and tissue dimpling during micro-electrode implantation into the brain are important for neuro-electrophysiology to minimize damage while enabling accurate placement and stable chronic extracellular electrophysiological recordings. Prior studies were unable to measure the sub-mN forces exerted during in vivo insertion of small electrodes. Here, we have investigated the in vivo force and dimpling depth profiles during brain surface membrane rupture (including dura) in anesthetized rats. METHODS A μN-resolution cantilever beam-based measurement system was designed, built, and calibrated and adapted for in vivo use. A total of 244 in vivo insertion tests were conducted on 8 anesthetized rats with 121 through pia mater and 123 through dura and pia combined. RESULTS Both microwire tip sharpening and diameter reduction reduced membrane rupture force (insertion force) and eased brain surface penetration. But dimpling depth and rupture force are not always strongly correlated. Multi-shank silicon probes showed smaller dimpling and rupture force per shank than single shank devices. CONCLUSION A force measurement system with flexible range and μN-level resolution (up to 0.032 μN) was achieved and proved feasible. For both pia-only and dura-pia penetrations in anesthetized rats, the rupture force and membrane dimpling depth at rupture are linearly related to the microwire diameter. SIGNIFICANCE We have developed a new system with both μN-level resolution and capacity to be used in vivo for measurement of force profiles of various neural interfaces into the brain. This allows quantification of brain tissue cutting and provides design guidelines for optimal neural interfaces.
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31
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Chen ZS, Pesaran B. Improving scalability in systems neuroscience. Neuron 2021; 109:1776-1790. [PMID: 33831347 PMCID: PMC8178195 DOI: 10.1016/j.neuron.2021.03.025] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Revised: 03/11/2021] [Accepted: 03/16/2021] [Indexed: 12/30/2022]
Abstract
Emerging technologies to acquire data at increasingly greater scales promise to transform discovery in systems neuroscience. However, current exponential growth in the scale of data acquisition is a double-edged sword. Scaling up data acquisition can speed up the cycle of discovery but can also misinterpret the results or possibly slow down the cycle because of challenges presented by the curse of high-dimensional data. Active, adaptive, closed-loop experimental paradigms use hardware and algorithms optimized to enable time-critical computation to provide feedback that interprets the observations and tests hypotheses to actively update the stimulus or stimulation parameters. In this perspective, we review important concepts of active and adaptive experiments and discuss how selectively constraining the dimensionality and optimizing strategies at different stages of discovery loop can help mitigate the curse of high-dimensional data. Active and adaptive closed-loop experimental paradigms can speed up discovery despite an exponentially increasing data scale, offering a road map to timely and iterative hypothesis revision and discovery in an era of exponential growth in neuroscience.
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Affiliation(s)
- Zhe Sage Chen
- Department of Psychiatry, Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY 10016, USA; Neuroscience Institute, NYU School of Medicine, New York, NY 10016, USA.
| | - Bijan Pesaran
- Neuroscience Institute, NYU School of Medicine, New York, NY 10016, USA; Center for Neural Science, New York University, New York, NY 10003, USA; Department of Neurology, New York University School of Medicine, New York, NY 10016, USA.
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32
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Liew YJ, Pala A, Whitmire CJ, Stoy WA, Forest CR, Stanley GB. Inferring thalamocortical monosynaptic connectivity in vivo. J Neurophysiol 2021; 125:2408-2431. [PMID: 33978507 PMCID: PMC8285656 DOI: 10.1152/jn.00591.2020] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Revised: 04/12/2021] [Accepted: 04/29/2021] [Indexed: 11/22/2022] Open
Abstract
As the tools to simultaneously record electrophysiological signals from large numbers of neurons within and across brain regions become increasingly available, this opens up for the first time the possibility of establishing the details of causal relationships between monosynaptically connected neurons and the patterns of neural activation that underlie perception and behavior. Although recorded activity across synaptically connected neurons has served as the cornerstone for much of what we know about synaptic transmission and plasticity, this has largely been relegated to ex vivo preparations that enable precise targeting under relatively well-controlled conditions. Analogous studies in vivo, where image-guided targeting is often not yet possible, rely on indirect, data-driven measures, and as a result such studies have been sparse and the dependence upon important experimental parameters has not been well studied. Here, using in vivo extracellular single-unit recordings in the topographically aligned rodent thalamocortical pathway, we sought to establish a general experimental and computational framework for inferring synaptic connectivity. Specifically, attacking this problem within a statistical signal detection framework utilizing experimentally recorded data in the ventral-posterior medial (VPm) region of the thalamus and the homologous region in layer 4 of primary somatosensory cortex (S1) revealed a trade-off between network activity levels needed for the data-driven inference and synchronization of nearby neurons within the population that results in masking of synaptic relationships. Here, we provide a framework for establishing connectivity in multisite, multielectrode recordings based on statistical inference, setting the stage for large-scale assessment of synaptic connectivity within and across brain structures.NEW & NOTEWORTHY Despite the fact that all brain function relies on the long-range transfer of information across different regions, the tools enabling us to measure connectivity across brain structures are lacking. Here, we provide a statistical framework for identifying and assessing potential monosynaptic connectivity across neuronal circuits from population spiking activity that generalizes to large-scale recording technologies that will help us to better understand the signaling within networks that underlies perception and behavior.
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Affiliation(s)
- Yi Juin Liew
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia
- Joint PhD Program in Biomedical Engineering, Georgia Institute of Technology-Emory University-Peking University, Atlanta, Georgia
| | - Aurélie Pala
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia
| | - Clarissa J Whitmire
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia
| | - William A Stoy
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia
| | - Craig R Forest
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia
| | - Garrett B Stanley
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia
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33
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Steinmetz NA, Aydin C, Lebedeva A, Okun M, Pachitariu M, Bauza M, Beau M, Bhagat J, Böhm C, Broux M, Chen S, Colonell J, Gardner RJ, Karsh B, Kloosterman F, Kostadinov D, Mora-Lopez C, O'Callaghan J, Park J, Putzeys J, Sauerbrei B, van Daal RJJ, Vollan AZ, Wang S, Welkenhuysen M, Ye Z, Dudman JT, Dutta B, Hantman AW, Harris KD, Lee AK, Moser EI, O'Keefe J, Renart A, Svoboda K, Häusser M, Haesler S, Carandini M, Harris TD. Neuropixels 2.0: A miniaturized high-density probe for stable, long-term brain recordings. Science 2021. [PMID: 33859006 DOI: 10.1101/2020.10.27.358291] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
Measuring the dynamics of neural processing across time scales requires following the spiking of thousands of individual neurons over milliseconds and months. To address this need, we introduce the Neuropixels 2.0 probe together with newly designed analysis algorithms. The probe has more than 5000 sites and is miniaturized to facilitate chronic implants in small mammals and recording during unrestrained behavior. High-quality recordings over long time scales were reliably obtained in mice and rats in six laboratories. Improved site density and arrangement combined with newly created data processing methods enable automatic post hoc correction for brain movements, allowing recording from the same neurons for more than 2 months. These probes and algorithms enable stable recordings from thousands of sites during free behavior, even in small animals such as mice.
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Affiliation(s)
- Nicholas A Steinmetz
- UCL Institute of Ophthalmology, University College London, London, UK.
- Department of Biological Structure, University of Washington, Seattle, WA, USA
| | | | - Anna Lebedeva
- Sainsbury Wellcome Centre, University College London, London, UK
| | - Michael Okun
- Centre for Systems Neuroscience and Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, UK
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Marius Pachitariu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Marius Bauza
- Sainsbury Wellcome Centre, University College London, London, UK
| | - Maxime Beau
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Jai Bhagat
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Claudia Böhm
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Susu Chen
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Jennifer Colonell
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Richard J Gardner
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - Bill Karsh
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Fabian Kloosterman
- Neuroelectronics Research Flanders, Leuven, Belgium
- IMEC, Leuven, Belgium
- Vlaams Instituut voor Biotechnologie (VIB), Leuven, Belgium
- Brain and Cognition, KU Leuven, Leuven, Belgium
| | - Dimitar Kostadinov
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | | | | | - Junchol Park
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Britton Sauerbrei
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Rik J J van Daal
- ATLAS Neuroengineering, Leuven, Belgium
- Neuroelectronics Research Flanders, Leuven, Belgium
- Micro- and Nanosystems, KU Leuven, Leuven, Belgium
| | - Abraham Z Vollan
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | | | | | - Zhiwen Ye
- Department of Biological Structure, University of Washington, Seattle, WA, USA
| | - Joshua T Dudman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Adam W Hantman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Kenneth D Harris
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Albert K Lee
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Edvard I Moser
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - John O'Keefe
- Sainsbury Wellcome Centre, University College London, London, UK
| | | | - Karel Svoboda
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Michael Häusser
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Sebastian Haesler
- Neuroelectronics Research Flanders, Leuven, Belgium
- Vlaams Instituut voor Biotechnologie (VIB), Leuven, Belgium
| | - Matteo Carandini
- UCL Institute of Ophthalmology, University College London, London, UK.
| | - Timothy D Harris
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
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Steinmetz NA, Aydin C, Lebedeva A, Okun M, Pachitariu M, Bauza M, Beau M, Bhagat J, Böhm C, Broux M, Chen S, Colonell J, Gardner RJ, Karsh B, Kloosterman F, Kostadinov D, Mora-Lopez C, O'Callaghan J, Park J, Putzeys J, Sauerbrei B, van Daal RJJ, Vollan AZ, Wang S, Welkenhuysen M, Ye Z, Dudman JT, Dutta B, Hantman AW, Harris KD, Lee AK, Moser EI, O'Keefe J, Renart A, Svoboda K, Häusser M, Haesler S, Carandini M, Harris TD. Neuropixels 2.0: A miniaturized high-density probe for stable, long-term brain recordings. Science 2021; 372:eabf4588. [PMID: 33859006 PMCID: PMC8244810 DOI: 10.1126/science.abf4588] [Citation(s) in RCA: 317] [Impact Index Per Article: 105.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 03/01/2021] [Indexed: 12/22/2022]
Abstract
Measuring the dynamics of neural processing across time scales requires following the spiking of thousands of individual neurons over milliseconds and months. To address this need, we introduce the Neuropixels 2.0 probe together with newly designed analysis algorithms. The probe has more than 5000 sites and is miniaturized to facilitate chronic implants in small mammals and recording during unrestrained behavior. High-quality recordings over long time scales were reliably obtained in mice and rats in six laboratories. Improved site density and arrangement combined with newly created data processing methods enable automatic post hoc correction for brain movements, allowing recording from the same neurons for more than 2 months. These probes and algorithms enable stable recordings from thousands of sites during free behavior, even in small animals such as mice.
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Affiliation(s)
- Nicholas A Steinmetz
- UCL Institute of Ophthalmology, University College London, London, UK.
- Department of Biological Structure, University of Washington, Seattle, WA, USA
| | | | - Anna Lebedeva
- Sainsbury Wellcome Centre, University College London, London, UK
| | - Michael Okun
- Centre for Systems Neuroscience and Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, UK
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Marius Pachitariu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Marius Bauza
- Sainsbury Wellcome Centre, University College London, London, UK
| | - Maxime Beau
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Jai Bhagat
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Claudia Böhm
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Susu Chen
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Jennifer Colonell
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Richard J Gardner
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - Bill Karsh
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Fabian Kloosterman
- Neuroelectronics Research Flanders, Leuven, Belgium
- IMEC, Leuven, Belgium
- Vlaams Instituut voor Biotechnologie (VIB), Leuven, Belgium
- Brain and Cognition, KU Leuven, Leuven, Belgium
| | - Dimitar Kostadinov
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | | | | | - Junchol Park
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Britton Sauerbrei
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Rik J J van Daal
- ATLAS Neuroengineering, Leuven, Belgium
- Neuroelectronics Research Flanders, Leuven, Belgium
- Micro- and Nanosystems, KU Leuven, Leuven, Belgium
| | - Abraham Z Vollan
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | | | | | - Zhiwen Ye
- Department of Biological Structure, University of Washington, Seattle, WA, USA
| | - Joshua T Dudman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Adam W Hantman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Kenneth D Harris
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Albert K Lee
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Edvard I Moser
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - John O'Keefe
- Sainsbury Wellcome Centre, University College London, London, UK
| | | | - Karel Svoboda
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Michael Häusser
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Sebastian Haesler
- Neuroelectronics Research Flanders, Leuven, Belgium
- Vlaams Instituut voor Biotechnologie (VIB), Leuven, Belgium
| | - Matteo Carandini
- UCL Institute of Ophthalmology, University College London, London, UK.
| | - Timothy D Harris
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
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Huang IW, Clay M, Cao Y, Nie J, Guo Y, Monbouquette HG. Electroenzymatic choline sensing at near the theoretical performance limit. Analyst 2021; 146:1040-1047. [PMID: 33325460 DOI: 10.1039/d0an01939a] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
A high performance, electroenzymatic microsensor for choline based on choline oxidase (ChOx) immobilized on Pt coated with permselective polymer layers has been created that exhibits sensitivity approaching the theoretical performance limit. Sensor construction was guided by simulations performed with a detailed mathematical model. Implantable microsensors with an array of electroenzymatic sensing sites provide a means to record concentration changes of choline, an effective surrogate for acetylcholine due to its very rapid turnover in the brain, and other neurochemicals in vivo. However, electroenzymatic sensors generally have insufficient sensitivity and response time to monitor neurotransmitter signaling on the millisecond timescale with cellular-level spatial resolution. Model simulations suggested that choline sensor performance can be improved significantly by optimizing immobilized ChOx layer thickness and minimizing the thicknesses of permselective polymer coatings as well. Electroenzymatic choline sensors constructed with a ∼5 μm-thick crosslinked ChOx layer atop 200 nm-thick permselective films (poly(m-phenylenediamine) and Nafion) exhibited unprecedented sensitivity and response time of 660 ± 40 nA μM-1 cm-2 at 37 °C and 0.36 ± 0.05 s, respectively, while maintaining excellent selectivity. Such performance characteristics provide greater flexibility in the design of microelectrode array (MEA) probes with near cellular-scale sensing sites arranged in more dense arrays. Also, faster response times enable better resolution of transient acetylcholine signals and better correlation of these events with electrophysiological recordings so as to advance study of brain function.
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Affiliation(s)
- I-Wen Huang
- Chemical and Biomolecular Engineering Department, University of California, Los Angeles, Los Angeles, CA 90095, USA.
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36
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Li H, Liu H, Sun M, Huang Y, Xu L. 3D Interfacing between Soft Electronic Tools and Complex Biological Tissues. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2021; 33:e2004425. [PMID: 33283351 DOI: 10.1002/adma.202004425] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 08/08/2020] [Indexed: 06/12/2023]
Abstract
Recent developments in soft functional materials have created opportunities for building bioelectronic devices with tissue-like mechanical properties. Their integration with the human body could enable advanced sensing and stimulation for medical diagnosis and therapies. However, most of the available soft electronics are constructed as planar sheets, which are difficult to interface with the target organs and tissues that have complex 3D structures. Here, the recent approaches are highlighted to building 3D interfaces between soft electronic tools and complex biological organs and tissues. Examples involve mesh devices for conformal contact, imaging-guided fabrication of organ-specific electronics, miniaturized probes for neurointerfaces, instrumented scaffold for tissue engineering, and many other soft 3D systems. They represent diverse routes for reconciling the interfacial mismatches between electronic tools and biological tissues. The remaining challenges include device scaling to approach the complexity of target organs, biological data acquisition and processing, 3D manufacturing techniques, etc., providing a range of opportunities for scientific research and technological innovation.
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Affiliation(s)
- Hegeng Li
- Department of Mechanical Engineering, The University of Hong Kong, Hong Kong SAR, 999077, China
- State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Hongzhen Liu
- Department of Mechanical Engineering, The University of Hong Kong, Hong Kong SAR, 999077, China
| | - Mingze Sun
- Department of Mechanical Engineering, The University of Hong Kong, Hong Kong SAR, 999077, China
| | - YongAn Huang
- State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Lizhi Xu
- Department of Mechanical Engineering, The University of Hong Kong, Hong Kong SAR, 999077, China
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37
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Spatially expandable fiber-based probes as a multifunctional deep brain interface. Nat Commun 2020; 11:6115. [PMID: 33257708 PMCID: PMC7704647 DOI: 10.1038/s41467-020-19946-9] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 10/29/2020] [Indexed: 11/28/2022] Open
Abstract
Understanding the cytoarchitecture and wiring of the brain requires improved methods to record and stimulate large groups of neurons with cellular specificity. This requires miniaturized neural interfaces that integrate into brain tissue without altering its properties. Existing neural interface technologies have been shown to provide high-resolution electrophysiological recording with high signal-to-noise ratio. However, with single implantation, the physical properties of these devices limit their access to one, small brain region. To overcome this limitation, we developed a platform that provides three-dimensional coverage of brain tissue through multisite multifunctional fiber-based neural probes guided in a helical scaffold. Chronic recordings from the spatially expandable fiber probes demonstrate the ability of these fiber probes capturing brain activities with a single-unit resolution for long observation times. Furthermore, using Thy1-ChR2-YFP mice we demonstrate the application of our probes in simultaneous recording and optical/chemical modulation of brain activities across distant regions. Similarly, varying electrographic brain activities from different brain regions were detected by our customizable probes in a mouse model of epilepsy, suggesting the potential of using these probes for the investigation of brain disorders such as epilepsy. Ultimately, this technique enables three-dimensional manipulation and mapping of brain activities across distant regions in the deep brain with minimal tissue damage, which can bring new insights for deciphering complex brain functions and dynamics in the near future. Existing neural interfaces are limited in accessing one, small brain region. Here, the authors introduce a scaffold with helix hollow channels, which direct multisite multifunctional fibre probes into the brain at different angles, allowing for simultaneous recording and stimulation across distant regions.
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38
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Luan L, Robinson JT, Aazhang B, Chi T, Yang K, Li X, Rathore H, Singer A, Yellapantula S, Fan Y, Yu Z, Xie C. Recent Advances in Electrical Neural Interface Engineering: Minimal Invasiveness, Longevity, and Scalability. Neuron 2020; 108:302-321. [PMID: 33120025 PMCID: PMC7646678 DOI: 10.1016/j.neuron.2020.10.011] [Citation(s) in RCA: 60] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 10/03/2020] [Accepted: 10/08/2020] [Indexed: 12/16/2022]
Abstract
Electrical neural interfaces serve as direct communication pathways that connect the nervous system with the external world. Technological advances in this domain are providing increasingly more powerful tools to study, restore, and augment neural functions. Yet, the complexities of the nervous system give rise to substantial challenges in the design, fabrication, and system-level integration of these functional devices. In this review, we present snapshots of the latest progresses in electrical neural interfaces, with an emphasis on advances that expand the spatiotemporal resolution and extent of mapping and manipulating brain circuits. We include discussions of large-scale, long-lasting neural recording; wireless, miniaturized implants; signal transmission, amplification, and processing; as well as the integration of interfaces with optical modalities. We outline the background and rationale of these developments and share insights into the future directions and new opportunities they enable.
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Affiliation(s)
- Lan Luan
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA; Department of Bioengineering, Rice University, Houston, TX, USA; NeuroEngineering Initiative, Rice University, Houston, TX, USA
| | - Jacob T Robinson
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA; Department of Bioengineering, Rice University, Houston, TX, USA; NeuroEngineering Initiative, Rice University, Houston, TX, USA
| | - Behnaam Aazhang
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA; NeuroEngineering Initiative, Rice University, Houston, TX, USA
| | - Taiyun Chi
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA
| | - Kaiyuan Yang
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA
| | - Xue Li
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA; NeuroEngineering Initiative, Rice University, Houston, TX, USA
| | - Haad Rathore
- NeuroEngineering Initiative, Rice University, Houston, TX, USA; Applied Physics Graduate Program, Rice University, Houston, TX, USA
| | - Amanda Singer
- NeuroEngineering Initiative, Rice University, Houston, TX, USA; Applied Physics Graduate Program, Rice University, Houston, TX, USA
| | - Sudha Yellapantula
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA; NeuroEngineering Initiative, Rice University, Houston, TX, USA
| | - Yingying Fan
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA
| | - Zhanghao Yu
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA
| | - Chong Xie
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA; Department of Bioengineering, Rice University, Houston, TX, USA; NeuroEngineering Initiative, Rice University, Houston, TX, USA.
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39
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Moreaux LC, Yatsenko D, Sacher WD, Choi J, Lee C, Kubat NJ, Cotton RJ, Boyden ES, Lin MZ, Tian L, Tolias AS, Poon JKS, Shepard KL, Roukes ML. Integrated Neurophotonics: Toward Dense Volumetric Interrogation of Brain Circuit Activity-at Depth and in Real Time. Neuron 2020; 108:66-92. [PMID: 33058767 PMCID: PMC8061790 DOI: 10.1016/j.neuron.2020.09.043] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 08/18/2020] [Accepted: 09/28/2020] [Indexed: 12/17/2022]
Abstract
We propose a new paradigm for dense functional imaging of brain activity to surmount the limitations of present methodologies. We term this approach "integrated neurophotonics"; it combines recent advances in microchip-based integrated photonic and electronic circuitry with those from optogenetics. This approach has the potential to enable lens-less functional imaging from within the brain itself to achieve dense, large-scale stimulation and recording of brain activity with cellular resolution at arbitrary depths. We perform a computational study of several prototype 3D architectures for implantable probe-array modules that are designed to provide fast and dense single-cell resolution (e.g., within a 1-mm3 volume of mouse cortex comprising ∼100,000 neurons). We describe progress toward realizing integrated neurophotonic imaging modules, which can be produced en masse with current semiconductor foundry protocols for chip manufacturing. Implantation of multiple modules can cover extended brain regions.
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Affiliation(s)
- Laurent C Moreaux
- Division of Physics, Mathematics and Astronomy, California Institute of Technology, Pasadena, CA 91125, USA.
| | - Dimitri Yatsenko
- Vathes LLC, Houston, TX 77030, USA; Center for Neuroscience and Artificial Intelligence and Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA
| | - Wesley D Sacher
- Kavli Nanoscience Institute, California Institute of Technology, Pasadena, CA 91125, USA; Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA 91125, USA; Max Planck Institute for Microstructure Physics, Halle, Germany
| | - Jaebin Choi
- Departments of Electrical Engineering and Biomedical Engineering, Columbia University, New York, NY 10027, USA
| | - Changhyuk Lee
- Departments of Electrical Engineering and Biomedical Engineering, Columbia University, New York, NY 10027, USA; Center for BioMicrosystems, Brain Science Institute, Korea Institute of Science and Technology, Korea
| | - Nicole J Kubat
- Division of Physics, Mathematics and Astronomy, California Institute of Technology, Pasadena, CA 91125, USA
| | - R James Cotton
- Shirley Ryan AbilityLab, Northwestern University, Chicago, IL 60611, USA; Center for Neuroscience and Artificial Intelligence and Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA
| | - Edward S Boyden
- Howard Hughes Medical Institute, Cambridge, MA, USA; McGovern Institute, MIT, Cambridge, USA; Koch Institute, MIT, Cambridge, USA; Departments of Brain and Cognitive Sciences, Media Arts and Sciences, and Biological Engineering, MIT, Cambridge, USA
| | - Michael Z Lin
- Departments of Neurobiology and Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Lin Tian
- Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, CA 95616, USA
| | - Andreas S Tolias
- Vathes LLC, Houston, TX 77030, USA; Center for Neuroscience and Artificial Intelligence and Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA; Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA
| | - Joyce K S Poon
- Max Planck Institute for Microstructure Physics, Halle, Germany; Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Rd., Toronto, ON M5S 3G4, Canada
| | - Kenneth L Shepard
- Departments of Electrical Engineering and Biomedical Engineering, Columbia University, New York, NY 10027, USA
| | - Michael L Roukes
- Division of Physics, Mathematics and Astronomy, California Institute of Technology, Pasadena, CA 91125, USA; Kavli Nanoscience Institute, California Institute of Technology, Pasadena, CA 91125, USA; Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA 91125, USA; Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA.
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40
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Woods GA, Rommelfanger NJ, Hong G. Bioinspired Materials for In Vivo Bioelectronic Neural Interfaces. MATTER 2020; 3:1087-1113. [PMID: 33103115 PMCID: PMC7583599 DOI: 10.1016/j.matt.2020.08.002] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
The success of in vivo neural interfaces relies on their long-term stability and large scale in interrogating and manipulating neural activity after implantation. Conventional neural probes, owing to their limited spatiotemporal resolution and scale, face challenges for studying the massive, interconnected neural network in its native state. In this review, we argue that taking inspiration from biology will unlock the next generation of in vivo bioelectronic neural interfaces. Reducing the feature sizes of bioelectronic neural interfaces to mimic those of neurons enables high spatial resolution and multiplexity. Additionally, chronic stability at the device-tissue interface is realized by matching the mechanical properties of bioelectronic neural interfaces to those of the endogenous tissue. Further, modeling the design of neural interfaces after the endogenous topology of the neural circuitry enables new insights into the connectivity and dynamics of the brain. Lastly, functionalization of neural probe surfaces with coatings inspired by biology leads to enhanced tissue acceptance over extended timescales. Bioinspired neural interfaces will facilitate future developments in neuroscience studies and neurological treatments by leveraging bidirectional information transfer and integrating neuromorphic computing elements.
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Affiliation(s)
- Grace A. Woods
- Department of Applied Physics, Stanford University, Stanford, California, 94305, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, California, 94305, USA
| | - Nicholas J. Rommelfanger
- Department of Applied Physics, Stanford University, Stanford, California, 94305, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, California, 94305, USA
| | - Guosong Hong
- Department of Materials Science and Engineering, Stanford University, Stanford, California, 94305, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, California, 94305, USA
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41
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Scholten K, Larson CE, Xu H, Song D, Meng E. A 512-Channel Multi-Layer Polymer-Based Neural Probe Array. JOURNAL OF MICROELECTROMECHANICAL SYSTEMS : A JOINT IEEE AND ASME PUBLICATION ON MICROSTRUCTURES, MICROACTUATORS, MICROSENSORS, AND MICROSYSTEMS 2020; 29:1054-1058. [PMID: 33746477 PMCID: PMC7978043 DOI: 10.1109/jmems.2020.2999550] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
We present for the first time the design, fabrication, and preliminary bench-top characterization of a high-density, polymer-based penetrating microelectrode array, developed for chronic, large-scale recording in the cortices and hippocampi of behaving rats. We present two architectures for these targeted brain regions, both featuring 512 Pt recording electrodes patterned front-and-back on micromachined eight-shank arrays of thin-film Parylene C. These devices represent an order of magnitude improvement in both number and density of recording electrodes compared with prior work on polymer-based microelectrode arrays. We present enabling advances in polymer micro-machining related to lithographic resolution and a new method for back-side patterning of electrodes. In vitro electrochemical data verifies suitable electrode function and surface properties. Finally, we describe next steps toward the implementation of these arrays in chronic, large-scale recording studies in free-moving animal models.
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Affiliation(s)
- Kee Scholten
- Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089 USA
| | - Christopher E Larson
- Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089 USA
| | - Huijing Xu
- Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089 USA
| | - Dong Song
- Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089 USA
| | - Ellis Meng
- Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089 USA
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42
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Nurmikko A. Challenges for Large-Scale Cortical Interfaces. Neuron 2020; 108:259-269. [DOI: 10.1016/j.neuron.2020.10.015] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 10/10/2020] [Accepted: 10/12/2020] [Indexed: 12/21/2022]
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43
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Egert D, Pettibone JR, Lemke S, Patel PR, Caldwell CM, Cai D, Ganguly K, Chestek CA, Berke JD. Cellular-scale silicon probes for high-density, precisely localized neurophysiology. J Neurophysiol 2020; 124:1578-1587. [PMID: 32965150 DOI: 10.1152/jn.00352.2020] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Neural implants with large numbers of electrodes have become an important tool for examining brain functions. However, these devices typically displace a large intracranial volume compared with the neurons they record. This large size limits the density of implants, provokes tissue reactions that degrade chronic performance, and impedes the ability to accurately visualize recording sites within intact circuits. Here we report next-generation silicon-based neural probes at a cellular scale (5 × 10 µm cross section), with ultra-high-density packing (as little as 66 µm between shanks) and 64 or 256 closely spaced recording sites per probe. We show that these probes can be inserted into superficial or deep brain structures and record large spikes in freely behaving rats for many weeks. Finally, we demonstrate a slice-in-place approach for the precise registration of recording sites relative to nearby neurons and anatomical features, including striatal µ-opioid receptor patches. This scalable technology provides a valuable tool for examining information processing within neural circuits and potentially for human brain-machine interfaces.NEW & NOTEWORTHY Devices with many electrodes penetrating into the brain are an important tool for investigating neural information processing, but they are typically large compared with neurons. This results in substantial damage and makes it harder to reconstruct recording locations within brain circuits. This paper presents high-channel-count silicon probes with much smaller features and a method for slicing through probe, brain, and skull all together. This allows probe tips to be directly observed relative to immunohistochemical markers.
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Affiliation(s)
- Daniel Egert
- Department of Neurology, University of California, San Francisco, California
| | - Jeffrey R Pettibone
- Department of Neurology, University of California, San Francisco, California
| | - Stefan Lemke
- Neuroscience Graduate Program, University of California, San Francisco, California
| | - Paras R Patel
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
| | - Ciara M Caldwell
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
| | - Dawen Cai
- Department of Molecular and Cell Biology, University of Michigan, Ann Arbor, Michigan
| | - Karunesh Ganguly
- Department of Neurology, University of California, San Francisco, California.,Veterans Affairs Medical Center, San Francisco, California.,Weill Institute for Neurosciences and Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, California
| | - Cynthia A Chestek
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan.,Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan.,Neurosciences Program, University of Michigan, Ann Arbor, Michigan.,Robotics Program, University of Michigan, Ann Arbor, Michigan
| | - Joshua D Berke
- Department of Neurology, University of California, San Francisco, California.,Weill Institute for Neurosciences and Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, California
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44
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Kim D, Kang H, Nam Y. Compact 256-channel multi-well microelectrode array system for in vitro neuropharmacology test. LAB ON A CHIP 2020; 20:3410-3422. [PMID: 32785330 DOI: 10.1039/d0lc00384k] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Microelectrode arrays (MEAs) have been extensively used to measure extracellular spike activity from cultured neurons using multiple electrodes embedded in a planar glass substrate. This system has been implemented to investigate drug effects by detecting pharmacological perturbation reflected in spontaneous network activity. By configuring multiple wells in an MEA, a high-throughput electrophysiological assay has become available, speeding up drug tests. Despite its merits in acquiring massive amounts of electrophysiological data, the high cost and the bulky size of commercial multi-well MEA systems and most importantly its lack of customizability prevent potential users from fully implementing the system in drug experiments. In this work, we have developed a microelectrode array based drug testing platform by incorporating a custom-made compact 256-channel multi-well MEA in a standard microscope slide and commercial application-specific integrated circuit (ASIC) chip based recording system. We arranged 256 electrodes in 16 wells to maximize data collection from a single chip. The multi-well MEA in this work has a more compact design with reduced chip size compared to previously reported multi-well MEAs. Four synaptic modulators (NMDA, AMPA, bicuculline (BIC) and ATP) were applied to a multi-well MEA and neural spike activity was analyzed to study their neurophysiological effects on cultured neurons. Analyzing various neuropharmacological compounds has become much more accessible by utilizing commercially available digital amplifier chips and customizing a user-preferred analog-front-end interface design with additional benefits in reduced platform size and cost.
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Affiliation(s)
- Daejeong Kim
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea.
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Du M, Huang L, Zheng J, Xi Y, Dai Y, Zhang W, Yan W, Tao G, Qiu J, So K, Ren C, Zhou S. Flexible Fiber Probe for Efficient Neural Stimulation and Detection. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2020; 7:2001410. [PMID: 32775173 PMCID: PMC7404151 DOI: 10.1002/advs.202001410] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Indexed: 05/24/2023]
Abstract
Functional probes are a leading contender for the recognition and manipulation of nervous behavior and are characterized by substantial scientific and technological potential. Despite the recent development of functional neural probes, a flexible biocompatible probe unit that allows for long-term simultaneous stimulation and signaling is still an important task. Here, a category of flexible tiny multimaterial fiber probes (<0.3 g) is described in which the metal electrodes are regularly embedded inside a biocompatible polymer fiber with a double-clad optical waveguide by thermal drawing. Significantly, this arrangement enables great improvement in mechanical properties, achieves high optical transmission (>90%), and effectively minimizes the impedance (by up to one order of magnitude) of the probe. This ability allows to realize long-term (at least 10 weeks) simultaneous optical stimulation and neural recording at the single-cell level in behaving mice with signal-to-noise ratio (SNR = 30 dB) that is more than 6 times that of the benchmark probe such as an all-polymer fiber.
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Affiliation(s)
- Minghui Du
- State Key Laboratory of Luminescent Materials and DevicesSchool of Materials Science and EngineeringSouth China University of TechnologyGuangzhou510640China
- Guangdong Provincial Key Laboratory of Fibre Laser Materials and Applied TechniquesGuangdong Engineering Technology Research and Development Center of Special Optical Fibre Materials and DevicesGuangzhou510640China
| | - Lu Huang
- Guangdong‐Hongkong‐Macau Institute of CNS RegenerationMinistry of Education CNS Regeneration Collaborative Joint LaboratoryJinan UniversityGuangzhou510632China
- Department of Neurology and Stroke CenterThe First Affiliated Hospital of Jinan UniversityGuangzhou510632China
| | - Jiajun Zheng
- Guangdong‐Hongkong‐Macau Institute of CNS RegenerationMinistry of Education CNS Regeneration Collaborative Joint LaboratoryJinan UniversityGuangzhou510632China
| | - Yue Xi
- Guangdong‐Hongkong‐Macau Institute of CNS RegenerationMinistry of Education CNS Regeneration Collaborative Joint LaboratoryJinan UniversityGuangzhou510632China
| | - Yi Dai
- State Key Laboratory of Luminescent Materials and DevicesSchool of Materials Science and EngineeringSouth China University of TechnologyGuangzhou510640China
- Guangdong Provincial Key Laboratory of Fibre Laser Materials and Applied TechniquesGuangdong Engineering Technology Research and Development Center of Special Optical Fibre Materials and DevicesGuangzhou510640China
| | - Weida Zhang
- State Key Laboratory of Luminescent Materials and DevicesSchool of Materials Science and EngineeringSouth China University of TechnologyGuangzhou510640China
- Guangdong Provincial Key Laboratory of Fibre Laser Materials and Applied TechniquesGuangdong Engineering Technology Research and Development Center of Special Optical Fibre Materials and DevicesGuangzhou510640China
| | - Wei Yan
- Research Laboratory of ElectronicsMassachusetts Institute of Technology (MIT)CambridgeMA02139USA
| | - Guangming Tao
- School of Optical and Electronic InformationWuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan430074China
| | - Jianrong Qiu
- College of Optical Science and EngineeringState Key Laboratory of Modern Optical InstrumentationZhejiang UniversityHangzhou310027China
| | - Kwok‐Fai So
- Guangdong‐Hongkong‐Macau Institute of CNS RegenerationMinistry of Education CNS Regeneration Collaborative Joint LaboratoryJinan UniversityGuangzhou510632China
| | - Chaoran Ren
- Guangdong‐Hongkong‐Macau Institute of CNS RegenerationMinistry of Education CNS Regeneration Collaborative Joint LaboratoryJinan UniversityGuangzhou510632China
- Guangzhou Regenerative Medicine and Health Guangdong LaboratoryGuangzhou510530China
- Co‐innovation Center of NeuroregenerationNantong UniversityNantong226001China
- Center for Brain Science and Brain‐Inspired IntelligenceGuangdong‐Hong Kong‐Macao Greater Bay AreaGuangzhou510000China
| | - Shifeng Zhou
- State Key Laboratory of Luminescent Materials and DevicesSchool of Materials Science and EngineeringSouth China University of TechnologyGuangzhou510640China
- Guangdong Provincial Key Laboratory of Fibre Laser Materials and Applied TechniquesGuangdong Engineering Technology Research and Development Center of Special Optical Fibre Materials and DevicesGuangzhou510640China
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Guo L. Principles of functional neural mapping using an intracortical ultra-density microelectrode array (ultra-density MEA). J Neural Eng 2020; 17:036018. [PMID: 32365334 DOI: 10.1088/1741-2552/ab8fc5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
OBJECTIVE Intracortical electrical neural recording using solid-state electrodes is a prevalent approach in addressing neurophysiological queries and implementing brain-computer interfacing systems. As a variety of ultra-density microelectrode arrays (ultra-density MEAs) are being created more recently, this paper answers to the rising demand for a more rigorous theory concerning this new type of neural electrode technology, both to guide the proper design and to inform the proper usage. APPROACH This design and use problem of ultra-density MEAs for functional intracortical neuronal circuit mapping is approached from a signal analysis perspective. Starting with quantitative derivations of key basic concepts, the concept of ultra-density MEA is defined in the context for fully resolving the voltage sources within its view volume. Then, the principle of using such an ultra-density MEA for functional neural mapping is elaborated, and a recursive approach to completely resolve all voltage sources from the ultra-density MEA's recordings is proposed. This approach is further validated using a simulated experiment. Last, the limitations and implications of this work are discussed. MAIN RESULTS MEAs can only be used to map the extracellular somatic action potential (esAP) sources in a neural microcircuit, and AP propagation along individual axons cannot be detected. The key for the ultra-density MEA design is to make sure that each spatial unit of analysis (SUA) contains no more than one active esAP source. The unique neural resolving capability of ultra-density MEAs comparing to conventional MEAs is to be able to spatiotemporally resolve each esAP source within its view volume. SIGNIFICANCE The ultimate capability and limitation of neural electrode array technology at such an unprecedented fabrication resolution is unraveled. This work strives to further the discussions on this topic into a more quantitative and rational direction, while providing a theoretical guideline for the rational development and neuroscientific application of an ultra-density MEA for intracortical functional mapping.
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Affiliation(s)
- Liang Guo
- Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH, United States of America
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Das R, Moradi F, Heidari H. Biointegrated and Wirelessly Powered Implantable Brain Devices: A Review. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2020; 14:343-358. [PMID: 31944987 DOI: 10.1109/tbcas.2020.2966920] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
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Nag OK, Muroski ME, Hastman DA, Almeida B, Medintz IL, Huston AL, Delehanty JB. Nanoparticle-Mediated Visualization and Control of Cellular Membrane Potential: Strategies, Progress, and Remaining Issues. ACS NANO 2020; 14:2659-2677. [PMID: 32078291 DOI: 10.1021/acsnano.9b10163] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
The interfacing of nanoparticle (NP) materials with cells, tissues, and organisms for a range of applications including imaging, sensing, and drug delivery continues at a rampant pace. An emerging theme in this area is the use of NPs and nanostructured surfaces for the imaging and/or control of cellular membrane potential (MP). Given the important role that MP plays in cellular biology, both in normal physiology and in disease, new materials and methods are continually being developed to probe the activity of electrically excitable cells such as neurons and muscle cells. In this Review, we highlight the current state of the art for both the visualization and control of MP using traditional materials and techniques, discuss the advantageous features of NPs for performing these functions, and present recent examples from the literature of how NP materials have been implemented for the visualization and control of the activity of electrically excitable cells. We conclude with a forward-looking perspective of how we expect to see this field progress in the near term and further into the future.
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Affiliation(s)
- Okhil K Nag
- Center for Bio/Molecular Science and Engineering, Code 6900, U.S. Naval Research Laboratory, Washington, DC 20375, United States
| | - Megan E Muroski
- Center for Bio/Molecular Science and Engineering, Code 6900, U.S. Naval Research Laboratory, Washington, DC 20375, United States
- American Society for Engineering Education, Washington, D.C. 20036, United States
| | - David A Hastman
- Center for Bio/Molecular Science and Engineering, Code 6900, U.S. Naval Research Laboratory, Washington, DC 20375, United States
- Fischell Department of Bioengineering, University of Maryland, College Park, Maryland 20742, United States
| | - Bethany Almeida
- Center for Bio/Molecular Science and Engineering, Code 6900, U.S. Naval Research Laboratory, Washington, DC 20375, United States
- American Society for Engineering Education, Washington, D.C. 20036, United States
| | - Igor L Medintz
- Center for Bio/Molecular Science and Engineering, Code 6900, U.S. Naval Research Laboratory, Washington, DC 20375, United States
| | - Alan L Huston
- Division of Optical Sciences, Code 5600, U.S. Naval Research Laboratory, Washington, D.C. 20375, United States
| | - James B Delehanty
- Center for Bio/Molecular Science and Engineering, Code 6900, U.S. Naval Research Laboratory, Washington, DC 20375, United States
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Yang L, Lee K, Villagracia J, Masmanidis SC. Open source silicon microprobes for high throughput neural recording. J Neural Eng 2020; 17:016036. [PMID: 31731284 DOI: 10.1088/1741-2552/ab581a] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
OBJECTIVE Microfabricated multielectrode arrays are widely used for high throughput recording of extracellular neural activity, which is transforming our understanding of brain function in health and disease. Currently there is a plethora of electrode-based tools being developed at higher education and research institutions. However, taking such tools from the initial research and development phase to widespread adoption by the neuroscience community is often hindered by several obstacles. The objective of this work is to describe the development, application, and open dissemination of silicon microprobes for recording neural activity in vivo. APPROACH We propose an open source dissemination platform as an alternative to commercialization. This framework promotes recording tools that are openly and inexpensively available to the community. The silicon microprobes are designed in house, but the fabrication and assembly processes are carried out by third party companies. This enables mass production, a key requirement for large-scale dissemination. MAIN RESULTS We demonstrate the operation of silicon microprobes containing up to 256 electrodes in conjunction with optical fibers for optogenetic manipulations or fiber photometry. These data provide new insights about the relationship between calcium activity and neural spiking activity. We also describe the current state of dissemination of these tools. A file repository of resources related to designing, using, and sharing these tools is maintained online. SIGNIFICANCE This paper is likely to be a valuable resource for both current and prospective users, as well as developers of silicon microprobes. Based on their extensive usage by a number of labs including ours, these tools present a promising alternative to other types of electrode-based technologies aimed at high throughput recording in head-fixed animals. This work also demonstrates the importance of validating fiber photometry measurements with simultaneous electrophysiological recordings.
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Takeuchi Y, Berényi A. Oscillotherapeutics - Time-targeted interventions in epilepsy and beyond. Neurosci Res 2020; 152:87-107. [PMID: 31954733 DOI: 10.1016/j.neures.2020.01.002] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Revised: 12/18/2019] [Accepted: 12/19/2019] [Indexed: 02/09/2023]
Abstract
Oscillatory brain activities support many physiological functions from motor control to cognition. Disruptions of the normal oscillatory brain activities are commonly observed in neurological and psychiatric disorders including epilepsy, Parkinson's disease, Alzheimer's disease, schizophrenia, anxiety/trauma-related disorders, major depressive disorders, and drug addiction. Therefore, these disorders can be considered as common oscillation defects despite having distinct behavioral manifestations and genetic causes. Recent technical advances of neuronal activity recording and analysis have allowed us to study the pathological oscillations of each disorder as a possible biomarker of symptoms. Furthermore, recent advances in brain stimulation technologies enable time- and space-targeted interventions of the pathological oscillations of both neurological disorders and psychiatric disorders as possible targets for regulating their symptoms.
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Affiliation(s)
- Yuichi Takeuchi
- MTA-SZTE 'Momentum' Oscillatory Neuronal Networks Research Group, Department of Physiology, University of Szeged, Szeged, 6720, Hungary; Department of Neuropharmacology, Graduate School of Pharmaceutical Sciences, Nagoya City University, Nagoya, 467-8603, Japan.
| | - Antal Berényi
- MTA-SZTE 'Momentum' Oscillatory Neuronal Networks Research Group, Department of Physiology, University of Szeged, Szeged, 6720, Hungary; HCEMM-SZTE Magnetotherapeutics Research Group, University of Szeged, Szeged, 6720, Hungary; Neuroscience Institute, New York University, New York, NY 10016, USA.
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