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Liu Q, Zhou J, Zeng Q, Sun D, Yu B, Yang L, Zhang Z, Wu J, Zhang Y. Flexible Dry Epidermal Electrophysiological Electrodes Based on One-Dimensional Platinum-Coated Silver Nanowires. ACS APPLIED NANO MATERIALS 2024; 7:18226-18236. [DOI: 10.1021/acsanm.3c03457] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/28/2024]
Affiliation(s)
- Qing Liu
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Jie Zhou
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
- College of Optoelectronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China
| | - Qi Zeng
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
- College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518061, China
| | - Dexin Sun
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Bin Yu
- College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Liangtao Yang
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Zhilin Zhang
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Jinglong Wu
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Yi Zhang
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
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2
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Lin Z, Kireev D, Liu N, Gupta S, LaPaino J, Obaid SN, Chen Z, Akinwande D, Efimov IR. Graphene Biointerface for Cardiac Arrhythmia Diagnosis and Treatment. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2212190. [PMID: 36965107 PMCID: PMC12013714 DOI: 10.1002/adma.202212190] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 02/16/2023] [Indexed: 06/02/2023]
Abstract
Heart rhythm disorders, known as arrhythmias, cause significant morbidity and are one of the leading causes of mortality. Cardiac arrhythmias are frequently treated by implantable devices, such as pacemakers and defibrillators, or by ablation therapy guided by electroanatomical mapping. Both implantable and ablation therapies require sophisticated biointerfaces for electrophysiological measurements of electrograms and delivery of therapeutic stimulation or ablation energy. In this work, a graphene biointerface for in vivo cardiac electrophysiology is reported for the first time. Leveraging sub-micrometer-thick tissue-conformable graphene arrays, sensing and stimulation of the open mammalian heart are demonstrated both in vitro and in vivo. Furthermore, the graphene biointerface treatment of atrioventricular block (the kind of arrhythmia where the electrical conduction from the atria to the ventricles is interrupted) is demonstrated. The graphene arrays show effective electrochemical properties, namely interface impedance down to 40 Ω cm2 at 1 kHz, charge storage capacity up to 63.7 mC cm-2 , and charge injection capacity up to 704 µC cm-2 . Transparency of the graphene structures allows for simultaneous optical mapping of cardiac action potentials, calcium transients, and optogenetic stimulation while performing electrical measurements and stimulation. The report presents evidence of the significant potential of graphene biointerfaces for advanced cardiac electrophysiology and arrhythmia therapy.
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Affiliation(s)
- Zexu Lin
- Department of Biomedical Engineering, The George Washington University, Washington, DC, 20052, USA
| | - Dmitry Kireev
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USA
- Microelectronics Research Center, The University of Texas at Austin, Texas, 78758 USA
| | - Ning Liu
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USA
| | - Shubham Gupta
- Department of Biomedical Engineering, The George Washington University, Washington, DC, 20052, USA
| | - Jessica LaPaino
- MedStar Georgetown University Hospital, Washington, DC, 20007, USA
| | - Sofian N. Obaid
- Department of Biomedical Engineering, The George Washington University, Washington, DC, 20052, USA
| | - Zhiyuan Chen
- Department of Biomedical Engineering, The George Washington University, Washington, DC, 20052, USA
| | - Deji Akinwande
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USA
- Microelectronics Research Center, The University of Texas at Austin, Texas, 78758 USA
| | - Igor R. Efimov
- Department of Biomedical Engineering, The George Washington University, Washington, DC, 20052, USA
- Department of Biomedical Engineering, Northwestern University, Evanston, IL 60208
- Department of Medicine (Cardiology), Northwestern University, Chicago, IL 60611
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Chen Z, Nguyen K, Kowalik G, Shi X, Tian J, Doshi M, Alber BR, Guan X, Liu X, Ning X, Kay MW, Lu L. Transparent and Stretchable Au─Ag Nanowire Recording Microelectrode Arrays. ADVANCED MATERIALS TECHNOLOGIES 2023; 8:2201716. [PMID: 38644939 PMCID: PMC11031257 DOI: 10.1002/admt.202201716] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Indexed: 04/23/2024]
Abstract
Transparent microelectrodes have received much attention from the biomedical community due to their unique advantages in concurrent crosstalk-free electrical and optical interrogation of cell/tissue activity. Despite recent progress in constructing transparent microelectrodes, a major challenge is to simultaneously achieve desirable mechanical stretchability, optical transparency, electrochemical performance, and chemical stability for high-fidelity, conformal, and stable interfacing with soft tissue/organ systems. To address this challenge, we have designed microelectrode arrays (MEAs) with gold-coated silver nanowires (Au─Ag NWs) by combining technical advances in materials, fabrication, and mechanics. The Au coating improves both the chemical stability and electrochemical impedance of the Au─Ag NW microelectrodes with only slight changes in optical properties. The MEAs exhibit a high optical transparency >80% at 550 nm, a low normalized 1 kHz electrochemical impedance of 1.2-7.5 Ω cm2, stable chemical and electromechanical performance after exposure to oxygen plasma for 5 min, and cyclic stretching for 600 cycles at 20% strain, superior to other transparent microelectrode alternatives. The MEAs easily conform to curvilinear heart surfaces for colocalized electrophysiological and optical mapping of cardiac function. This work demonstrates that stretchable transparent metal nanowire MEAs are promising candidates for diverse biomedical science and engineering applications, particularly under mechanically dynamic conditions.
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Affiliation(s)
- Zhiyuan Chen
- Department of Biomedical Engineering, The George Washington University, Washington, DC 20052, USA
| | - Khanh Nguyen
- Department of Biomedical Engineering, The George Washington University, Washington, DC 20052, USA
| | - Grant Kowalik
- Department of Biomedical Engineering, The George Washington University, Washington, DC 20052, USA
| | - Xinyu Shi
- Department of Biomedical Engineering, The George Washington University, Washington, DC 20052, USA
| | - Jinbi Tian
- Department of Biomedical Engineering, The George Washington University, Washington, DC 20052, USA
| | - Mitansh Doshi
- Department of Aerospace Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Bridget R Alber
- Department of Biomedical Engineering, The George Washington University, Washington, DC 20052, USA
| | - Xun Guan
- Department of Civil and Environmental Engineering, The George Washington University, Washington, DC 20052, USA
| | - Xitong Liu
- Department of Civil and Environmental Engineering, The George Washington University, Washington, DC 20052, USA
| | - Xin Ning
- Department of Aerospace Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Matthew W Kay
- Department of Biomedical Engineering, The George Washington University, Washington, DC 20052, USA
| | - Luyao Lu
- Department of Biomedical Engineering, The George Washington University, Washington, DC 20052, USA
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Liu Y, Xu S, Yang Y, Zhang K, He E, Liang W, Luo J, Wu Y, Cai X. Nanomaterial-based microelectrode arrays for in vitro bidirectional brain-computer interfaces: a review. MICROSYSTEMS & NANOENGINEERING 2023; 9:13. [PMID: 36726940 PMCID: PMC9884667 DOI: 10.1038/s41378-022-00479-8] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 10/04/2022] [Accepted: 10/21/2022] [Indexed: 06/18/2023]
Abstract
A bidirectional in vitro brain-computer interface (BCI) directly connects isolated brain cells with the surrounding environment, reads neural signals and inputs modulatory instructions. As a noninvasive BCI, it has clear advantages in understanding and exploiting advanced brain function due to the simplified structure and high controllability of ex vivo neural networks. However, the core of ex vivo BCIs, microelectrode arrays (MEAs), urgently need improvements in the strength of signal detection, precision of neural modulation and biocompatibility. Notably, nanomaterial-based MEAs cater to all the requirements by converging the multilevel neural signals and simultaneously applying stimuli at an excellent spatiotemporal resolution, as well as supporting long-term cultivation of neurons. This is enabled by the advantageous electrochemical characteristics of nanomaterials, such as their active atomic reactivity and outstanding charge conduction efficiency, improving the performance of MEAs. Here, we review the fabrication of nanomaterial-based MEAs applied to bidirectional in vitro BCIs from an interdisciplinary perspective. We also consider the decoding and coding of neural activity through the interface and highlight the various usages of MEAs coupled with the dissociated neural cultures to benefit future developments of BCIs.
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Affiliation(s)
- Yaoyao Liu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Shihong Xu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Yan Yang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Kui Zhang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Enhui He
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Wei Liang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Jinping Luo
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Yirong Wu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Xinxia Cai
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
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Fekete Z, Zátonyi A, Kaszás A, Madarász M, Slézia A. Transparent neural interfaces: challenges and solutions of microengineered multimodal implants designed to measure intact neuronal populations using high-resolution electrophysiology and microscopy simultaneously. MICROSYSTEMS & NANOENGINEERING 2023; 9:66. [PMID: 37213820 PMCID: PMC10195795 DOI: 10.1038/s41378-023-00519-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 02/03/2023] [Accepted: 03/01/2023] [Indexed: 05/23/2023]
Abstract
The aim of this review is to present a comprehensive overview of the feasibility of using transparent neural interfaces in multimodal in vivo experiments on the central nervous system. Multimodal electrophysiological and neuroimaging approaches hold great potential for revealing the anatomical and functional connectivity of neuronal ensembles in the intact brain. Multimodal approaches are less time-consuming and require fewer experimental animals as researchers obtain denser, complex data during the combined experiments. Creating devices that provide high-resolution, artifact-free neural recordings while facilitating the interrogation or stimulation of underlying anatomical features is currently one of the greatest challenges in the field of neuroengineering. There are numerous articles highlighting the trade-offs between the design and development of transparent neural interfaces; however, a comprehensive overview of the efforts in material science and technology has not been reported. Our present work fills this gap in knowledge by introducing the latest micro- and nanoengineered solutions for fabricating substrate and conductive components. Here, the limitations and improvements in electrical, optical, and mechanical properties, the stability and longevity of the integrated features, and biocompatibility during in vivo use are discussed.
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Affiliation(s)
- Z. Fekete
- Research Group for Implantable Microsystems, Faculty of Information Technology & Bionics, Pázmány Péter Catholic University, Budapest, Hungary
- Institute of Cognitive Neuroscience & Psychology, Eotvos Lorand Research Network, Budapest, Hungary
| | - A. Zátonyi
- Research Group for Implantable Microsystems, Faculty of Information Technology & Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - A. Kaszás
- Mines Saint-Etienne, Centre CMP, Département BEL, F - 13541 Gardanne, France
- Institut de Neurosciences de la Timone, CNRS UMR 7289 & Aix-Marseille Université, 13005 Marseille, France
| | - M. Madarász
- János Szentágothai PhD Program of Semmelweis University, Budapest, Hungary
- BrainVision Center, Budapest, Hungary
| | - A. Slézia
- Institut de Neurosciences de la Timone, CNRS UMR 7289 & Aix-Marseille Université, 13005 Marseille, France
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Dijk G, Kaszas A, Pas J, O’Connor RP. Fabrication and in vivo 2-photon microscopy validation of transparent PEDOT:PSS microelectrode arrays. MICROSYSTEMS & NANOENGINEERING 2022; 8:90. [PMID: 36051746 PMCID: PMC9424218 DOI: 10.1038/s41378-022-00434-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 06/02/2022] [Accepted: 06/22/2022] [Indexed: 05/04/2023]
Abstract
Transparent microelectrode arrays enable simultaneous electrical recording and optical imaging of neuronal networks in the brain. Electrodes made of the conducting polymer poly(3,4-ethylenedioxythiophene) doped with polystyrene sulfonate (PEDOT:PSS) are transparent; however, device fabrication necessitates specific processes to avoid deterioration of the organic material. Here, we present an innovative fabrication scheme for a neural probe that consists of transparent PEDOT:PSS electrodes and demonstrate its compatibility with 2-photon microscopy. The electrodes show suitable impedance to record local field potentials from the cortex of mice and sufficient transparency to visualize GCaMP6f-expressing neurons underneath the PEDOT:PSS features. The results validate the performance of the neural probe, which paves the way to study the complex dynamics of in vivo neuronal activity with both a high spatial and temporal resolution to better understand the brain.
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Affiliation(s)
- Gerwin Dijk
- Mines Saint-Etienne, Centre CMP, Department of Bioelectronics, Gardanne, 13541 France
- Panaxium SAS, Aix-en-Provence, 13100 France
| | - Attila Kaszas
- Mines Saint-Etienne, Centre CMP, Department of Bioelectronics, Gardanne, 13541 France
| | - Jolien Pas
- Panaxium SAS, Aix-en-Provence, 13100 France
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Bentzur A, Alon S, Shohat-Ophir G. Behavioral Neuroscience in the Era of Genomics: Tools and Lessons for Analyzing High-Dimensional Datasets. Int J Mol Sci 2022; 23:3811. [PMID: 35409169 PMCID: PMC8998543 DOI: 10.3390/ijms23073811] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 03/26/2022] [Accepted: 03/29/2022] [Indexed: 12/10/2022] Open
Abstract
Behavioral neuroscience underwent a technology-driven revolution with the emergence of machine-vision and machine-learning technologies. These technological advances facilitated the generation of high-resolution, high-throughput capture and analysis of complex behaviors. Therefore, behavioral neuroscience is becoming a data-rich field. While behavioral researchers use advanced computational tools to analyze the resulting datasets, the search for robust and standardized analysis tools is still ongoing. At the same time, the field of genomics exploded with a plethora of technologies which enabled the generation of massive datasets. This growth of genomics data drove the emergence of powerful computational approaches to analyze these data. Here, we discuss the composition of a large behavioral dataset, and the differences and similarities between behavioral and genomics data. We then give examples of genomics-related tools that might be of use for behavioral analysis and discuss concepts that might emerge when considering the two fields together.
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Affiliation(s)
- Assa Bentzur
- The Mina & Everard Goodman Faculty of Life Sciences, Gonda Multidisciplinary Brain Research Center, Institute of Nanotechnology, Bar-Ilan University, Ramat Gan 5290002, Israel;
- The Alexander Kofkin Faculty of Engineering, Gonda Multidisciplinary Brain Research Center, Institute of Nanotechnology and Advanced Materials, Bar-Ilan University, Ramat Gan 5290002, Israel
| | - Shahar Alon
- The Alexander Kofkin Faculty of Engineering, Gonda Multidisciplinary Brain Research Center, Institute of Nanotechnology and Advanced Materials, Bar-Ilan University, Ramat Gan 5290002, Israel
| | - Galit Shohat-Ophir
- The Mina & Everard Goodman Faculty of Life Sciences, Gonda Multidisciplinary Brain Research Center, Institute of Nanotechnology, Bar-Ilan University, Ramat Gan 5290002, Israel;
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Lehtinen K, Nokia MS, Takala H. Red Light Optogenetics in Neuroscience. Front Cell Neurosci 2022; 15:778900. [PMID: 35046775 PMCID: PMC8761848 DOI: 10.3389/fncel.2021.778900] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 12/02/2021] [Indexed: 12/25/2022] Open
Abstract
Optogenetics, a field concentrating on controlling cellular functions by means of light-activated proteins, has shown tremendous potential in neuroscience. It possesses superior spatiotemporal resolution compared to the surgical, electrical, and pharmacological methods traditionally used in studying brain function. A multitude of optogenetic tools for neuroscience have been created that, for example, enable the control of action potential generation via light-activated ion channels. Other optogenetic proteins have been used in the brain, for example, to control long-term potentiation or to ablate specific subtypes of neurons. In in vivo applications, however, the majority of optogenetic tools are operated with blue, green, or yellow light, which all have limited penetration in biological tissues compared to red light and especially infrared light. This difference is significant, especially considering the size of the rodent brain, a major research model in neuroscience. Our review will focus on the utilization of red light-operated optogenetic tools in neuroscience. We first outline the advantages of red light for in vivo studies. Then we provide a brief overview of the red light-activated optogenetic proteins and systems with a focus on new developments in the field. Finally, we will highlight different tools and applications, which further facilitate the use of red light optogenetics in neuroscience.
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Affiliation(s)
- Kimmo Lehtinen
- Department of Biological and Environmental Science, Nanoscience Center, University of Jyväskylä, Jyväskylä, Finland
| | - Miriam S. Nokia
- Department of Psychology, University of Jyväskylä, Jyväskylä, Finland
- Centre for Interdisciplinary Brain Research, University of Jyväskylä, Jyväskylä, Finland
| | - Heikki Takala
- Department of Biological and Environmental Science, Nanoscience Center, University of Jyväskylä, Jyväskylä, Finland
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