1
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Mintz Hemed N, Hwang FJ, Zhao ET, Ding JB, Melosh NA. Multiplexed neurochemical sensing with sub-nM sensitivity across 2.25 mm 2 area. Biosens Bioelectron 2024; 261:116474. [PMID: 38870827 DOI: 10.1016/j.bios.2024.116474] [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: 03/21/2024] [Revised: 05/20/2024] [Accepted: 06/05/2024] [Indexed: 06/15/2024]
Abstract
Multichannel arrays capable of real-time sensing of neuromodulators in the brain are crucial for gaining insights into new aspects of neural communication. However, measuring neurochemicals, such as dopamine, at low concentrations over large areas has proven challenging. In this research, we demonstrate a novel approach that leverages the scalability and processing power offered by microelectrode array devices integrated with a functionalized, high-density microwire bundle, enabling electrochemical sensing at an unprecedented scale and spatial resolution. The sensors demonstrate outstanding selective molecular recognition by incorporating a selective polymeric membrane. By combining cutting-edge commercial multiplexing, digitization, and data acquisition hardware with a bio-compatible and highly sensitive neurochemical interface array, we establish a powerful platform for neurochemical analysis. This multichannel array has been successfully utilized in vitro and ex vivo systems. Notably, our results show a sensing area of 2.25 mm2 with an impressive detection limit of 820 pM for dopamine. This new approach paves the way for investigating complex neurochemical processes and holds promise for advancing our understanding of brain function and neurological disorders.
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Affiliation(s)
- Nofar Mintz Hemed
- Department of Materials Science and Engineering, Stanford University, Stanford, CA, USA
| | - Fuu-Jiun Hwang
- Department of Neurosurgery, Stanford University, Stanford, CA, 94305, USA
| | - Eric T Zhao
- Department of Chemical Engineering, Stanford University, Stanford, CA, 94305, USA
| | - Jun B Ding
- Department of Neurosurgery, Stanford University, Stanford, CA, 94305, USA; Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, 94305, USA
| | - Nicholas A Melosh
- Department of Materials Science and Engineering, Stanford University, Stanford, CA, USA.
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2
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Liu Y, Jia H, Sun H, Jia S, Yang Z, Li A, Jiang A, Naya Y, Yang C, Xue S, Li X, Chen B, Zhu J, Zhou C, Li M, Duan X. A high-density 1,024-channel probe for brain-wide recordings in non-human primates. Nat Neurosci 2024:10.1038/s41593-024-01692-6. [PMID: 38914829 DOI: 10.1038/s41593-024-01692-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 05/23/2024] [Indexed: 06/26/2024]
Abstract
Large-scale neural population recordings with single-cell resolution across the primate brain remain challenging. Here we introduce the Neuroscroll probe that isolates single neuronal activities simultaneously from 1,024 densely spaced channels that are flexibly distributed across the shank of the probe. The Neuroscroll probe length is easily tunable for individual probes from 10 mm to 90 mm, covering the brain size of non-human primates and humans, and the probes remain intact and functional after repeated bending deformations. The Neuroscroll probes provided reliable recordings from large neural populations with high chronic stability up to 105 weeks in rats. Recording with each Neuroscroll probe yielded hundreds of well-isolated single units simultaneously from multiple brain regions distributed across the entire depth of the rhesus macaque brain. With the thousand simultaneously recorded channels, unprecedented probe length, excellent mechanical stability and flexible recording site distribution, the Neuroscroll probes enable a wide range of new experimental paradigms in system neuroscience studies with great versatility.
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Affiliation(s)
- Yang Liu
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
| | - Huilin Jia
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
| | - Hongji Sun
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
| | - Shengyi Jia
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
| | - Ziqian Yang
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Ao Li
- School of Psychological and Cognitive Sciences, Peking University, Beijing, China
| | - Anqi Jiang
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
| | - Yuji Naya
- School of Psychological and Cognitive Sciences, Peking University, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Beijing Key Laboratory of Behavioral and Mental Health, Peking University, Beijing, China
| | - Cen Yang
- School of Psychological and Cognitive Sciences, Peking University, Beijing, China
| | - Shengyuan Xue
- School of Psychological and Cognitive Sciences, Peking University, Beijing, China
| | - Xiaojian Li
- CAS Key Laboratory of Brain Connectome and Manipulation, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, China
| | - Bingyan Chen
- CAS Key Laboratory of Brain Connectome and Manipulation, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, China
| | - Jingjun Zhu
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
- National Biomedical Imaging Centre, Peking University, Beijing, China
| | - Chenghao Zhou
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Minning Li
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Xiaojie Duan
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China.
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
- National Biomedical Imaging Centre, Peking University, Beijing, China.
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3
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Zhang K, Tang C, Yu S, Guan H, Sun X, Cao M, Zhang S, Sun X, Peng H. High-performing fiber electrodes based on a gold-shelled silver nanowire framework for bioelectronics. J Mater Chem B 2024; 12:5594-5599. [PMID: 38818741 DOI: 10.1039/d4tb00789a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2024]
Abstract
Flexible fiber electrodes offer new opportunities for bioelectronics and are reliable in vivo applications, high flexibility, high electrical conductivity, and satisfactory biocompatibility are typically required. Herein, we present an all-metal flexible and biocompatible fiber electrode based on a metal nanowire hybrid strategy, i.e., silver nanowires were assembled on a freestanding framework, and further to render them inert, they were plated with a gold nanoshell. Our fiber electrodes exhibited a low modulus of ∼75 MPa and electrical conductivity up to ∼4.8 × 106 S m-1. They can resist chemical erosion with negligible leakage of biotoxic silver ions in the physiological environment, thus ensuring satisfactory biocompatibility. Finally, we demonstrated the hybrid fiber as a neural electrode that stimulated the sciatic nerve of a mouse, proving its potential for applications in bioelectronics.
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Affiliation(s)
- Kailin Zhang
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Institute of Fiber Materials and Devices, and Laboratory of Advanced Materials, Fudan University, Shanghai 200438, China.
| | - Chengqiang Tang
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Institute of Fiber Materials and Devices, and Laboratory of Advanced Materials, Fudan University, Shanghai 200438, China.
| | - Sihui Yu
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Institute of Fiber Materials and Devices, and Laboratory of Advanced Materials, Fudan University, Shanghai 200438, China.
| | - Hang Guan
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Institute of Fiber Materials and Devices, and Laboratory of Advanced Materials, Fudan University, Shanghai 200438, China.
| | - Xiao Sun
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Institute of Fiber Materials and Devices, and Laboratory of Advanced Materials, Fudan University, Shanghai 200438, China.
| | - Mingjie Cao
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Institute of Fiber Materials and Devices, and Laboratory of Advanced Materials, Fudan University, Shanghai 200438, China.
| | - Songlin Zhang
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Institute of Fiber Materials and Devices, and Laboratory of Advanced Materials, Fudan University, Shanghai 200438, China.
| | - Xuemei Sun
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Institute of Fiber Materials and Devices, and Laboratory of Advanced Materials, Fudan University, Shanghai 200438, China.
| | - Huisheng Peng
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Institute of Fiber Materials and Devices, and Laboratory of Advanced Materials, Fudan University, Shanghai 200438, China.
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4
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Wang D, Jin K, Ji J, Hu C, Du M, Belgaid Y, Shi S, Li J, Hu S, Nathan A, Yu J, Ma H. Active-matrix digital microfluidics design for field programmable high-throughput digitalized liquid handling. iScience 2024; 27:109324. [PMID: 38706854 PMCID: PMC11067379 DOI: 10.1016/j.isci.2024.109324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 01/12/2024] [Accepted: 02/20/2024] [Indexed: 05/07/2024] Open
Abstract
Digital liquid sample handling is an enabling tool for cutting-edge life-sciences research. We present here an active-matrix thin-film transistor (TFT) based digital microfluidics system, referred to as Field Programmable Droplet Array (FPDA). The system contains 256 × 256 pixels in an active area of 10.65 cm2, which can manipulate thousands of addressable liquid droplets simultaneously. By leveraging a novel TFT device and circuits design solution, we manage to programmatically manipulate droplets at single-pixel level. The minimum achievable droplet volume is around 0.5 nL, which is two orders of magnitude smaller than the smallest droplet ever reported on active-matrix digital microfluidics. The movement of droplets can be either pre-programmed or controlled in real-time. The FPDA system shows great potential of the ubiquitous thin-film electronics technology in digital liquid handling. These efforts will make it possible to create a true programmable lab-on-a-chip device to enable great advances in life science research.
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Affiliation(s)
- Dongping Wang
- CAS Key Laboratory of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, P.R. China
| | - Kai Jin
- CAS Key Laboratory of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, P.R. China
| | - Jiajian Ji
- CAS Key Laboratory of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, P.R. China
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, P.R. China
| | - Chenxuan Hu
- CAS Key Laboratory of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, P.R. China
| | - Maohua Du
- Guangdong ACXEL Micro & Nano Tech Co., Ltd, Foshan 528000, P.R. China
| | | | - Subao Shi
- Guangdong ACXEL Micro & Nano Tech Co., Ltd, Foshan 528000, P.R. China
| | - Jiahao Li
- ACX Instruments Ltd, Cambridge CB4 0WS, UK
| | - Siyi Hu
- CAS Key Laboratory of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, P.R. China
| | - Arokia Nathan
- School of Information Science and Engineering, Shandong University, Qingdao 266237, P.R. China
| | - Jun Yu
- School of Information Science and Engineering, Shandong University, Qingdao 266237, P.R. China
| | - Hanbin Ma
- CAS Key Laboratory of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, P.R. China
- Guangdong ACXEL Micro & Nano Tech Co., Ltd, Foshan 528000, P.R. China
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5
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Xu K, Yang Y, Ding J, Wang J, Fang Y, Tian H. Spatially Precise Genetic Engineering at the Electrode-Tissue Interface. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024:e2401327. [PMID: 38692704 DOI: 10.1002/adma.202401327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 04/17/2024] [Indexed: 05/03/2024]
Abstract
The interface between electrodes and neural tissues plays a pivotal role in determining the efficacy and fidelity of neural activity recording and modulation. While considerable efforts have been made to improve the electrode-tissue interface, the majority of studies have primarily concentrated on the development of biocompatible neural electrodes through abiotic materials and structural engineering. In this study, an approach is presented that seamlessly integrates abiotic and biotic engineering principles into the electrode-tissue interface. Specifically, ultraflexible neural electrodes with short hairpin RNAs (shRNAs) designed to silence the expression of endogenous genes within neural tissues are combined. The system facilitates shRNA-mediated knockdown of phosphatase and tensin homolog deleted on chromosome 10 (PTEN) and polypyrimidine tract-binding protein 1 (PTBP1), two essential genes associated in neural survival/growth and neurogenesis, within specific cell populations located at the electrode-tissue interface. Additionally, it is demonstrated that the downregulation of PTEN in neurons can result in an enlargement of neuronal cell bodies at the electrode-tissue interface. Furthermore, the system enables long-term monitoring of neuronal activities following PTEN knockdown in a mouse model of Parkinson's disease and traumatic brain injury. The system provides a versatile approach for genetically engineering the electrode-tissue interface with unparalleled precision, paving the way for the development of regenerative electronics and next-generation brain-machine interfaces.
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Affiliation(s)
- Ke Xu
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, 100190, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
- School of Nanoscience and Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yinan Yang
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, 100190, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
- School of Nanoscience and Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jianfei Ding
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, 100190, China
| | - Jinfen Wang
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, 100190, China
- Chinese Institute for Brain Research, Beijing, 102206, China
| | - Ying Fang
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, 100190, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
- School of Nanoscience and Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China
- Chinese Institute for Brain Research, Beijing, 102206, China
| | - Huihui Tian
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, 100190, China
- Chinese Institute for Brain Research, Beijing, 102206, China
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6
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Zhou C, Tian Y, Li G, Ye Y, Gao L, Li J, Liu Z, Su H, Lu Y, Li M, Zhou Z, Wei X, Qin L, Tao TH, Sun L. Through-polymer, via technology-enabled, flexible, lightweight, and integrated devices for implantable neural probes. MICROSYSTEMS & NANOENGINEERING 2024; 10:54. [PMID: 38654844 PMCID: PMC11035623 DOI: 10.1038/s41378-024-00691-8] [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: 12/28/2023] [Revised: 02/29/2024] [Accepted: 03/11/2024] [Indexed: 04/26/2024]
Abstract
In implantable electrophysiological recording systems, the headstage typically comprises neural probes that interface with brain tissue and integrated circuit chips for signal processing. While advancements in MEMS and CMOS technology have significantly improved these components, their interconnection still relies on conventional printed circuit boards and sophisticated adapters. This conventional approach adds considerable weight and volume to the package, especially for high channel count systems. To address this issue, we developed a through-polymer via (TPV) method inspired by the through-silicon via (TSV) technique in advanced three-dimensional packaging. This innovation enables the vertical integration of flexible probes, amplifier chips, and PCBs, realizing a flexible, lightweight, and integrated device (FLID). The total weight of the FLIDis only 25% that of its conventional counterparts relying on adapters, which significantly increased the activity levels of animals wearing the FLIDs to nearly match the levels of control animals without implants. Furthermore, by incorporating a platinum-iridium alloy as the top layer material for electrical contact, the FLID realizes exceptional electrical performance, enabling in vivo measurements of both local field potentials and individual neuron action potentials. These findings showcase the potential of FLIDs in scaling up implantable neural recording systems and mark a significant advancement in the field of neurotechnology.
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Grants
- This work was partially supported by the National Key R & D Program of China (Grant Nos. 2021ZD0201600, 2022YFF0706504, 2022ZD0209300, 2019YFA0905200, 2021YFC2501500, 2021YFF1200700, 2022ZD0212300), National Natural Science Foundation of China (Grant No. 61974154), Key Research Program of Frontier Sciences, CAS (Grant No. ZDBS-LY-JSC024), Shanghai Pilot Program for Basic Research-Chinese Academy of Science, Shanghai Branch (Grant No. JCYJ-SHFY-2022-01 and JCYJ-SHFY-2022-0xx), Shanghai Municipal Science and Technology Major Project (Grant No. 2021SHZDZX), CAS Pioneer Hundred Talents Program, Shanghai Pujiang Program (Grant Nos. 21PJ1415100, 19PJ1410900), the Science and Technology Commission Foundation of Shanghai (Nos. 21JM0010200 and 21142200300), Shanghai Rising-Star Program (Grant No. 22QA1410900), Shanghai Sailing Program (No. 22YF1454700), the Innovative Research Team of High-level Local Universities in Shanghai, the Jiangxi Province 03 Special Project and 5G Project (Grant No. 20212ABC03W07), Fund for Central Government in Guidance of Local Science and Technology Development (Grant No. 20201ZDE04013), Special Fund for Science and Technology Innovation Strategy of Guangdong Province (Grant Nos. 2021B0909060002, 2021B0909050004).
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Affiliation(s)
- Cunkai Zhou
- College of Electronics and Information Engineering, Shanghai University of Electric Power, Shanghai, China
- 2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
| | - Ye Tian
- 2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
- School of Graduate Study, University of Chinese Academy of Sciences, Beijing, China
| | - Gen Li
- 2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
- School of Graduate Study, University of Chinese Academy of Sciences, Beijing, China
| | - Yifei Ye
- 2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
| | - Lusha Gao
- 2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
| | - Jiazhi Li
- 2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
| | - Ziwei Liu
- 2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
| | - Haoyang Su
- School of Graduate Study, University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
| | - Yunxiao Lu
- College of Electronics and Information Engineering, Shanghai University of Electric Power, Shanghai, China
- 2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
| | - Meng Li
- School of Graduate Study, University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
| | - Zhitao Zhou
- School of Graduate Study, University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
| | - Xiaoling Wei
- School of Graduate Study, University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
| | - Lunming Qin
- College of Electronics and Information Engineering, Shanghai University of Electric Power, Shanghai, China
| | - Tiger H. Tao
- 2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
- School of Graduate Study, University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
- Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing, China
- School of Physical Science and Technology, ShanghaiTech University, Shanghai, China
- Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
- Neuroxess Co., Ltd. (Jiangxi), Nanchang, Jiangxi China
- Guangdong Institute of Intelligence Science and Technology, Hengqin, Zhuhai, Guangdong China
- Tianqiao and Chrissy Chen Institute for Translational Research, Shanghai, China
| | - Liuyang Sun
- College of Electronics and Information Engineering, Shanghai University of Electric Power, Shanghai, China
- 2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
- School of Graduate Study, University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China
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7
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McNamara IN, Wellman SM, Li L, Eles JR, Savya S, Sohal HS, Angle MR, Kozai TDY. Electrode sharpness and insertion speed reduce tissue damage near high-density penetrating arrays. J Neural Eng 2024; 21:026030. [PMID: 38518365 DOI: 10.1088/1741-2552/ad36e1] [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: 11/22/2023] [Accepted: 03/22/2024] [Indexed: 03/24/2024]
Abstract
Objective. Over the past decade, neural electrodes have played a crucial role in bridging biological tissues with electronic and robotic devices. This study focuses on evaluating the optimal tip profile and insertion speed for effectively implanting Paradromics' high-density fine microwire arrays (FμA) prototypes into the primary visual cortex (V1) of mice and rats, addressing the challenges associated with the 'bed-of-nails' effect and tissue dimpling.Approach. Tissue response was assessed by investigating the impact of electrodes on the blood-brain barrier (BBB) and cellular damage, with a specific emphasis on tailored insertion strategies to minimize tissue disruption during electrode implantation.Main results.Electro-sharpened arrays demonstrated a marked reduction in cellular damage within 50μm of the electrode tip compared to blunt and angled arrays. Histological analysis revealed that slow insertion speeds led to greater BBB compromise than fast and pneumatic methods. Successful single-unit recordings validated the efficacy of the optimized electro-sharpened arrays in capturing neural activity.Significance.These findings underscore the critical role of tailored insertion strategies in minimizing tissue damage during electrode implantation, highlighting the suitability of electro-sharpened arrays for long-term implant applications. This research contributes to a deeper understanding of the complexities associated with high-channel-count microelectrode array implantation, emphasizing the importance of meticulous assessment and optimization of key parameters for effective integration and minimal tissue disruption. By elucidating the interplay between insertion parameters and tissue response, our study lays a strong foundation for the development of advanced implantable devices with a reduction in reactive gliosis and improved performance in neural recording applications.
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Affiliation(s)
- Ingrid N McNamara
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Steven M Wellman
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Lehong Li
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - James R Eles
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Sajishnu Savya
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America
| | | | | | - Takashi D Y Kozai
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America
- Center of the Basis of Neural Cognition, Pittsburgh, PA, United States of America
- McGowan Institute of Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America
- NeuroTech Center, University of Pittsburgh Brain Institute, Pittsburgh, PA, United States of America
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8
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Abu Shihada J, Jung M, Decke S, Koschinski L, Musall S, Rincón Montes V, Offenhäusser A. Highly Customizable 3D Microelectrode Arrays for In Vitro and In Vivo Neuronal Tissue Recordings. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2305944. [PMID: 38240370 PMCID: PMC10987114 DOI: 10.1002/advs.202305944] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 12/05/2023] [Indexed: 02/16/2024]
Abstract
Planar microelectrode arrays (MEAs) for - in vitro or in vivo - neuronal signal recordings lack the spatial resolution and sufficient signal-to-noise ratio (SNR) required for a detailed understanding of neural network function and synaptic plasticity. To overcome these limitations, a highly customizable three-dimensional (3D) printing process is used in combination with thin film technology and a self-aligned template-assisted electrochemical deposition process to fabricate 3D-printed-based MEAs on stiff or flexible substrates. Devices with design flexibility and physical robustness are shown for recording neural activity in different in vitro and in vivo applications, achieving high-aspect ratio 3D microelectrodes of up to 33:1. Here, MEAs successfully record neural activity in 3D neuronal cultures, retinal explants, and the cortex of living mice, thereby demonstrating the versatility of the 3D MEA while maintaining high-quality neural recordings. Customizable 3D MEAs provide unique opportunities to study neural activity under regular or various pathological conditions, both in vitro and in vivo, and contribute to the development of drug screening and neuromodulation systems that can accurately monitor the activity of large neural networks over time.
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Affiliation(s)
- J. Abu Shihada
- Institute of Biological Information Processing (IBI‐3) – BioelectronicsForschungszentrum52428JülichGermany
- RWTH Aachen University52062AachenGermany
| | - M. Jung
- Institute of Biological Information Processing (IBI‐3) – BioelectronicsForschungszentrum52428JülichGermany
- RWTH Aachen University52062AachenGermany
| | - S. Decke
- Institute of Biological Information Processing (IBI‐3) – BioelectronicsForschungszentrum52428JülichGermany
| | - L. Koschinski
- Institute of Biological Information Processing (IBI‐3) – BioelectronicsForschungszentrum52428JülichGermany
- RWTH Aachen University52062AachenGermany
- Helmholtz Nano Facility (HNF)Forschungszentrum Jülich52428JülichGermany
| | - S. Musall
- Institute of Biological Information Processing (IBI‐3) – BioelectronicsForschungszentrum52428JülichGermany
- RWTH Aachen University52062AachenGermany
- Faculty of MedicineInstitute of Experimental Epileptology and Cognition ResearchUniversity of Bonn53127BonnGermany
- University Hospital Bonn53127BonnGermany
| | - V. Rincón Montes
- Institute of Biological Information Processing (IBI‐3) – BioelectronicsForschungszentrum52428JülichGermany
| | - A. Offenhäusser
- Institute of Biological Information Processing (IBI‐3) – BioelectronicsForschungszentrum52428JülichGermany
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9
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Richie J, Letner JG, Mclane-Svoboda A, Huan Y, Ghaffari DH, Valle ED, Patel PR, Chiel HJ, Pelled G, Weiland JD, Chestek CA. Fabrication and Validation of Sub-Cellular Carbon Fiber Electrodes. IEEE Trans Neural Syst Rehabil Eng 2024; 32:739-749. [PMID: 38294928 PMCID: PMC10919889 DOI: 10.1109/tnsre.2024.3360866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2024]
Abstract
Multielectrode arrays for interfacing with neurons are of great interest for a wide range of medical applications. However, current electrodes cause damage over time. Ultra small carbon fibers help to address issues but controlling the electrode site geometry is difficult. Here we propose a methodology to create small, pointed fiber electrodes (SPFe). We compare the SPFe to previously made blowtorched fibers in characterization. The SPFe result in small site sizes [Formula: see text] with consistently sharp points (20.8 ± 7.64°). Additionally, these electrodes were able to record and/or stimulate neurons multiple animal models including rat cortex, mouse retina, Aplysia ganglia and octopus axial cord. In rat cortex, these electrodes recorded significantly higher peak amplitudes than the traditional blowtorched fibers. These SPFe may be applicable to a wide range of applications requiring a highly specific interface with individual neurons.
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10
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Wang L, Liu S, Zhao W, Li J, Zeng H, Kang S, Sheng X, Wang L, Fan Y, Yin L. Recent Advances in Implantable Neural Interfaces for Multimodal Electrical Neuromodulation. Adv Healthc Mater 2024:e2303316. [PMID: 38323711 DOI: 10.1002/adhm.202303316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 01/29/2024] [Indexed: 02/08/2024]
Abstract
Electrical neuromodulation plays a pivotal role in enhancing patient outcomes among individuals suffering from neurological disorders. Implantable neural interfaces are vital components of the electrical neuromodulation system to ensure desirable performance; However, conventional devices are limited to a single function and are constructed with bulky and rigid materials, which often leads to mechanical incompatibility with soft tissue and an inability to adapt to the dynamic and complex 3D structures of biological systems. In addition, current implantable neural interfaces utilized in clinical settings primarily rely on wire-based techniques, which are associated with complications such as increased risk of infection, limited positioning options, and movement restrictions. Here, the state-of-art applications of electrical neuromodulation are presented. Material schemes and device structures that can be employed to develop robust and multifunctional neural interfaces, including flexibility, stretchability, biodegradability, self-healing, self-rolling, or morphing are discussed. Furthermore, multimodal wireless neuromodulation techniques, including optoelectronics, mechano-electrics, magnetoelectrics, inductive coupling, and electrochemically based self-powered devices are reviewed. In the end, future perspectives are given.
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Affiliation(s)
- Liu Wang
- Key Laboratory of Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, and with the School of Engineering Medicine, Beihang University, Beijing, 100083, P. R. China
| | - Shengnan Liu
- School of Materials Science and Engineering, The Key Laboratory of Advanced Materials of Ministry of Education, State Key Laboratory of New Ceramics and Fine Processing, Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing, 100084, P. R. China
| | - Wentai Zhao
- Key Laboratory of Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, and with the School of Engineering Medicine, Beihang University, Beijing, 100083, P. R. China
| | - Jiakun Li
- Key Laboratory of Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, and with the School of Engineering Medicine, Beihang University, Beijing, 100083, P. R. China
| | - Haoxuan Zeng
- Key Laboratory of Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, and with the School of Engineering Medicine, Beihang University, Beijing, 100083, P. R. China
| | - Shaoyang Kang
- Key Laboratory of Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, and with the School of Engineering Medicine, Beihang University, Beijing, 100083, P. R. China
| | - Xing Sheng
- Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Institute for Precision Medicine, Laboratory of Flexible Electronics Technology, IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, 100084, China
| | - Lizhen Wang
- Key Laboratory of Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, and with the School of Engineering Medicine, Beihang University, Beijing, 100083, P. R. China
| | - Yubo Fan
- Key Laboratory of Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, and with the School of Engineering Medicine, Beihang University, Beijing, 100083, P. R. China
| | - Lan Yin
- School of Materials Science and Engineering, The Key Laboratory of Advanced Materials of Ministry of Education, State Key Laboratory of New Ceramics and Fine Processing, Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing, 100084, P. R. China
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11
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Gao L, Lv S, Shang Y, Guan S, Tian H, Fang Y, Wang J, Li H. Free-Standing Carbon Nanotube Embroidered Graphene Film Electrode Array for Stable Neural Interfacing. NANO LETTERS 2024; 24:829-835. [PMID: 38117186 DOI: 10.1021/acs.nanolett.3c03421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Implantable neural probes that are mechanically flexible yet robust are attractive candidates for achieving stable neural interfacing in the brain. Current flexible neural probes consist mainly of metal thin-film electrodes integrated on micrometer-thick polymer substrates, making it challenging to achieve electrode-tissue interfacing on the cellular scale. Here, we describe implantable neural probes that consist of robust carbon nanotube network embroidered graphene (CeG) films as free-standing recording microelectrodes. Our CeG film microelectrode arrays (CeG_MEAs) are ultraflexible yet mechanically robust, thus enabling cellular-scale electrode-tissue interfacing. Chronically implanted CeG_MEAs can stably track the activities of the same population of neurons over two months. Our results highlight the potential of ultraflexible and free-standing carbon nanofilms for stable neural interfacing in the brain.
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Affiliation(s)
- Lei Gao
- CAS Key Laboratory of Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
- Chinese Institute for Brain Research, Beijing 102206, China
| | - Suye Lv
- CAS Key Laboratory of Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuanyuan Shang
- School of Physics and Microelectronics, Zhengzhou University, Zhengzhou 450052, China
| | - Shouliang Guan
- CAS Key Laboratory of Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
| | - Huihui Tian
- CAS Key Laboratory of Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
| | - Ying Fang
- CAS Key Laboratory of Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
- Chinese Institute for Brain Research, Beijing 102206, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Jinfen Wang
- CAS Key Laboratory of Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
| | - Hongbian Li
- CAS Key Laboratory of Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
- Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Austin, Texas 78712, United States
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12
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Moslehi S, Rowland C, Smith JH, Watterson WJ, Griffiths W, Montgomery RD, Philliber S, Marlow CA, Perez MT, Taylor RP. Fractal Electronics for Stimulating and Sensing Neural Networks: Enhanced Electrical, Optical, and Cell Interaction Properties. ADVANCES IN NEUROBIOLOGY 2024; 36:849-875. [PMID: 38468067 DOI: 10.1007/978-3-031-47606-8_43] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
Imagine a world in which damaged parts of the body - an arm, an eye, and ultimately a region of the brain - can be replaced by artificial implants capable of restoring or even enhancing human performance. The associated improvements in the quality of human life would revolutionize the medical world and produce sweeping changes across society. In this chapter, we discuss several approaches to the fabrication of fractal electronics designed to interface with neural networks. We consider two fundamental functions - stimulating electrical signals in the neural networks and sensing the location of the signals as they pass through the network. Using experiments and simulations, we discuss the favorable electrical performances that arise from adopting fractal rather than traditional Euclidean architectures. We also demonstrate how the fractal architecture induces favorable physical interactions with the cells they interact with, including the ability to direct the growth of neurons and glia to specific regions of the neural-electronic interface.
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Affiliation(s)
- S Moslehi
- Physics Department, University of Oregon, Eugene, OR, USA
| | - C Rowland
- Physics Department, University of Oregon, Eugene, OR, USA
| | - J H Smith
- Physics Department, University of Oregon, Eugene, OR, USA
| | - W J Watterson
- Physics Department, University of Oregon, Eugene, OR, USA
| | - W Griffiths
- Physics Department, University of Oregon, Eugene, OR, USA
| | - R D Montgomery
- Physics Department, University of Oregon, Eugene, OR, USA
| | - S Philliber
- Physics Department, University of Oregon, Eugene, OR, USA
| | - C A Marlow
- Physics Department, California Polytechnic State University, San Luis Obispo, CA, USA
| | - M-T Perez
- Department of Clinical Sciences Lund, Division of Ophthalmology, Lund University, Lund, Sweden
| | - R P Taylor
- Physics Department, University of Oregon, Eugene, OR, USA.
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13
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Park W, Kim EM, Jeon Y, Lee J, Yi J, Jeong J, Kim B, Jeong BG, Kim DR, Kong H, Lee CH. Transparent Intracellular Sensing Platform with Si Needles for Simultaneous Live Imaging. ACS NANO 2023; 17:25014-25026. [PMID: 38059775 DOI: 10.1021/acsnano.3c07527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/08/2023]
Abstract
Vertically ordered Si needles are of particular interest for long-term intracellular recording owing to their capacity to infiltrate living cells with negligible damage and minimal toxicity. Such intracellular recordings could greatly benefit from simultaneous live cell imaging without disrupting their culture, contributing to an in-depth understanding of cellular function and activity. However, the use of standard live imaging techniques, such as inverted and confocal microscopy, is currently impeded by the opacity of Si wafers, typically employed for fabricating vertical Si needles. Here, we introduce a transparent intracellular sensing platform that combines vertical Si needles with a percolated network of Au-Ag nanowires on a transparent elastomeric substrate. This sensing platform meets all prerequisites for simultaneous intracellular recording and imaging, including electrochemical impedance, optical transparency, mechanical compliance, and cell viability. Proof-of-concept demonstrations of this sensing platform include monitoring electrical potentials in cardiomyocyte cells and in three-dimensionally engineered cardiovascular tissue, all while conducting live imaging with inverted and confocal microscopes. This sensing platform holds wide-ranging potential applications for intracellular research across various disciplines such as neuroscience, cardiology, muscle physiology, and drug screening.
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Affiliation(s)
- Woohyun Park
- School of Mechanical Engineering, Purdue University, West Lafayette, Indiana 47907, United States
| | - Eun Mi Kim
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Yale Jeon
- School of Mechanical Engineering, Hanyang University, Seoul 04763, Republic of Korea
| | - Junsang Lee
- School of Mechanical Engineering, Hanyang University, Seoul 04763, Republic of Korea
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana 47907, United States
| | - Jonghun Yi
- School of Mechanical Engineering, Hanyang University, Seoul 04763, Republic of Korea
| | - Jinheon Jeong
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana 47907, United States
| | - Bongjoong Kim
- School of Mechanical Engineering, Purdue University, West Lafayette, Indiana 47907, United States
- Department of Mechanical and System Design Engineering, Hongik University, Seoul 04066, Republic of Korea
| | - Byeong Guk Jeong
- School of Mechanical Engineering, Hanyang University, Seoul 04763, Republic of Korea
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana 47907, United States
| | - Dong Rip Kim
- School of Mechanical Engineering, Hanyang University, Seoul 04763, Republic of Korea
| | - Hyunjoon Kong
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Chi Hwan Lee
- School of Mechanical Engineering, Purdue University, West Lafayette, Indiana 47907, United States
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana 47907, United States
- Department of Materials Engineering, Purdue University, West Lafayette, Indiana 47907, United States
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14
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Duru J, Rüfenacht A, Löhle J, Pozzi M, Forró C, Ledermann L, Bernardi A, Matter M, Renia A, Simona B, Tringides CM, Bernhard S, Ihle SJ, Hengsteler J, Maurer B, Zhang X, Nakatsuka N. Driving electrochemical reactions at the microscale using CMOS microelectrode arrays. LAB ON A CHIP 2023; 23:5047-5058. [PMID: 37916299 PMCID: PMC10661664 DOI: 10.1039/d3lc00630a] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 10/25/2023] [Indexed: 11/03/2023]
Abstract
Precise control of pH values at electrode interfaces enables the systematic investigation of pH-dependent processes by electrochemical means. In this work, we employed high-density complementary metal-oxide-semiconductor (CMOS) microelectrode arrays (MEAs) as miniaturized systems to induce and confine electrochemical reactions in areas corresponding to the pitch of single electrodes (17.5 μm). First, we present a strategy for generating localized pH patterns on the surface of the CMOS MEA with unprecedented spatial resolution. Leveraging the versatile routing capabilities of the switch matrix beneath the CMOS MEA, we created arbitrary combinations of anodic and cathodic electrodes and hence pH patterns. Moreover, we utilized the system to produce polymeric surface patterns by additive and subtractive methods. For additive patterning, we controlled the in situ formation of polydopamine at the microelectrode surface through oxidation of free dopamine above a threshold pH > 8.5. For subtractive patterning, we removed cell-adhesive poly-L-lysine from the electrode surface and backfilled the voids with antifouling polymers. Such polymers were chosen to provide a proof-of-concept application of controlling neuronal growth via electrochemically-induced patterns on the CMOS MEA surface. Importantly, our platform is compatible with commercially available high-density MEAs and requires no custom equipment, rendering the findings generalizable and accessible.
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Affiliation(s)
- Jens Duru
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Arielle Rüfenacht
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Josephine Löhle
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Marcello Pozzi
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Csaba Forró
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Linus Ledermann
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Aeneas Bernardi
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Michael Matter
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - André Renia
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | | | - Christina M Tringides
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Stéphane Bernhard
- Macromolecular Engineering Laboratory, Department of Mechanical and Process Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland
| | - Stephan J Ihle
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Julian Hengsteler
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Benedikt Maurer
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Xinyu Zhang
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Nako Nakatsuka
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
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15
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Okatan M, Kocatürk M. Decoding the Spike-Band Subthreshold Motor Cortical Activity. J Mot Behav 2023; 56:161-183. [PMID: 37964432 DOI: 10.1080/00222895.2023.2280263] [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: 01/23/2023] [Accepted: 10/25/2023] [Indexed: 11/16/2023]
Abstract
Intracortical Brain-Computer Interfaces (iBCI) use single-unit activity (SUA), multiunit activity (MUA) and local field potentials (LFP) to control neuroprosthetic devices. SUA and MUA are usually extracted from the bandpassed recording through amplitude thresholding, while subthreshold data are ignored. Here, we show that subthreshold data can actually be decoded to determine behavioral variables with test set accuracy of up to 100%. Although the utility of SUA, MUA and LFP for decoding behavioral variables has been explored previously, this study investigates the utility of spike-band subthreshold activity exclusively. We provide evidence suggesting that this activity can be used to keep decoding performance at acceptable levels even when SUA quality is reduced over time. To the best of our knowledge, the signals that we derive from the subthreshold activity may be the weakest neural signals that have ever been extracted from extracellular neural recordings, while still being decodable with test set accuracy of up to 100%. These results are relevant for the development of fully data-driven and automated methods for amplitude thresholding spike-band extracellular neural recordings in iBCIs containing thousands of electrodes.
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Affiliation(s)
- Murat Okatan
- Informatics Institute, Istanbul Technical University, Istanbul, Türkiye
- Artificial Intelligence and Data Engineering Department, Istanbul Technical University, Istanbul, Türkiye
| | - Mehmet Kocatürk
- Biomedical Engineering Department, Istanbul Medipol University, Istanbul, Türkiye
- Research Institute for Health Sciences and Technologies (SABITA), Istanbul Medipol University, Istanbul, Türkiye
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16
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Perna A, Angotzi GN, Berdondini L, Ribeiro JF. Advancing the interfacing performances of chronically implantable neural probes in the era of CMOS neuroelectronics. Front Neurosci 2023; 17:1275908. [PMID: 38027514 PMCID: PMC10644322 DOI: 10.3389/fnins.2023.1275908] [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: 08/10/2023] [Accepted: 10/10/2023] [Indexed: 12/01/2023] Open
Abstract
Tissue penetrating microelectrode neural probes can record electrophysiological brain signals at resolutions down to single neurons, making them invaluable tools for neuroscience research and Brain-Computer-Interfaces (BCIs). The known gradual decrease of their electrical interfacing performances in chronic settings, however, remains a major challenge. A key factor leading to such decay is Foreign Body Reaction (FBR), which is the cascade of biological responses that occurs in the brain in the presence of a tissue damaging artificial device. Interestingly, the recent adoption of Complementary Metal Oxide Semiconductor (CMOS) technology to realize implantable neural probes capable of monitoring hundreds to thousands of neurons simultaneously, may open new opportunities to face the FBR challenge. Indeed, this shift from passive Micro Electro-Mechanical Systems (MEMS) to active CMOS neural probe technologies creates important, yet unexplored, opportunities to tune probe features such as the mechanical properties of the probe, its layout, size, and surface physicochemical properties, to minimize tissue damage and consequently FBR. Here, we will first review relevant literature on FBR to provide a better understanding of the processes and sources underlying this tissue response. Methods to assess FBR will be described, including conventional approaches based on the imaging of biomarkers, and more recent transcriptomics technologies. Then, we will consider emerging opportunities offered by the features of CMOS probes. Finally, we will describe a prototypical neural probe that may meet the needs for advancing clinical BCIs, and we propose axial insertion force as a potential metric to assess the influence of probe features on acute tissue damage and to control the implantation procedure to minimize iatrogenic injury and subsequent FBR.
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Affiliation(s)
- Alberto Perna
- Microtechnology for Neuroelectronics Lab, Fondazione Istituto Italiano di Tecnologia, Neuroscience and Brain Technologies, Genova, Italy
- The Open University Affiliated Research Centre at Istituto Italiano di Tecnologia (ARC@IIT), Istituto Italiano di Tecnologia, Genova, Italy
| | - Gian Nicola Angotzi
- Microtechnology for Neuroelectronics Lab, Fondazione Istituto Italiano di Tecnologia, Neuroscience and Brain Technologies, Genova, Italy
| | - Luca Berdondini
- Microtechnology for Neuroelectronics Lab, Fondazione Istituto Italiano di Tecnologia, Neuroscience and Brain Technologies, Genova, Italy
| | - João Filipe Ribeiro
- Microtechnology for Neuroelectronics Lab, Fondazione Istituto Italiano di Tecnologia, Neuroscience and Brain Technologies, Genova, Italy
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17
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Qin Y, Zhang Y, Zhang Y, Liu S, Guo X. Application and Development of EEG Acquisition and Feedback Technology: A Review. BIOSENSORS 2023; 13:930. [PMID: 37887123 PMCID: PMC10605290 DOI: 10.3390/bios13100930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 10/05/2023] [Accepted: 10/16/2023] [Indexed: 10/28/2023]
Abstract
This review focuses on electroencephalogram (EEG) acquisition and feedback technology and its core elements, including the composition and principles of the acquisition devices, a wide range of applications, and commonly used EEG signal classification algorithms. First, we describe the construction of EEG acquisition and feedback devices encompassing EEG electrodes, signal processing, and control and feedback systems, which collaborate to measure faint EEG signals from the scalp, convert them into interpretable data, and accomplish practical applications using control feedback systems. Subsequently, we examine the diverse applications of EEG acquisition and feedback across various domains. In the medical field, EEG signals are employed for epilepsy diagnosis, brain injury monitoring, and sleep disorder research. EEG acquisition has revealed associations between brain functionality, cognition, and emotions, providing essential insights for psychologists and neuroscientists. Brain-computer interface technology utilizes EEG signals for human-computer interaction, driving innovation in the medical, engineering, and rehabilitation domains. Finally, we introduce commonly used EEG signal classification algorithms. These classification tasks can identify different cognitive states, emotional states, brain disorders, and brain-computer interface control and promote further development and application of EEG technology. In conclusion, EEG acquisition technology can deepen the understanding of EEG signals while simultaneously promoting developments across multiple domains, such as medicine, science, and engineering.
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Affiliation(s)
- Yong Qin
- Institute of Advanced Structure Technology, Beijing Institute of Technology, Beijing 100081, China;
| | - Yanpeng Zhang
- Beijing Perfect-Protection Technology Co., Ltd., Beijing 101601, China; (Y.Z.); (Y.Z.); (S.L.)
| | - Yan Zhang
- Beijing Perfect-Protection Technology Co., Ltd., Beijing 101601, China; (Y.Z.); (Y.Z.); (S.L.)
| | - Sheng Liu
- Beijing Perfect-Protection Technology Co., Ltd., Beijing 101601, China; (Y.Z.); (Y.Z.); (S.L.)
| | - Xiaogang Guo
- Institute of Advanced Structure Technology, Beijing Institute of Technology, Beijing 100081, China;
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18
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Khatib M, Zhao ET, Wei S, Abramson A, Bishop ES, Chen CH, Thomas AL, Xu C, Park J, Lee Y, Hamnett R, Yu W, Root SE, Yuan L, Chakhtoura D, Kim KK, Zhong D, Nishio Y, Zhao C, Wu C, Jiang Y, Zhang A, Li J, Wang W, Salimi-Jazi F, Rafeeqi TA, Hemed NM, Tok JBH, Chen X, Kaltschmidt JA, Dunn JC, Bao Z. Spiral NeuroString: High-Density Soft Bioelectronic Fibers for Multimodal Sensing and Stimulation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.02.560482. [PMID: 37873341 PMCID: PMC10592902 DOI: 10.1101/2023.10.02.560482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Bioelectronic fibers hold promise for both research and clinical applications due to their compactness, ease of implantation, and ability to incorporate various functionalities such as sensing and stimulation. However, existing devices suffer from bulkiness, rigidity, limited functionality, and low density of active components. These limitations stem from the difficulty to incorporate many components on one-dimensional (1D) fiber devices due to the incompatibility of conventional microfabrication methods (e.g., photolithography) with curved, thin and long fiber structures. Herein, we introduce a fabrication approach, ‶spiral transformation″, to convert two-dimensional (2D) films containing microfabricated devices into 1D soft fibers. This approach allows for the creation of high density multimodal soft bioelectronic fibers, termed Spiral NeuroString (S-NeuroString), while enabling precise control over the longitudinal, angular, and radial positioning and distribution of the functional components. We show the utility of S-NeuroString for motility mapping, serotonin sensing, and tissue stimulation within the dynamic and soft gastrointestinal (GI) system, as well as for single-unit recordings in the brain. The described bioelectronic fibers hold great promises for next-generation multifunctional implantable electronics.
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Affiliation(s)
- Muhammad Khatib
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Eric Tianjiao Zhao
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Shiyuan Wei
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Alex Abramson
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Division of Digestive Diseases, Emory University School of Medicine, Atlanta, GA 30332, USA
| | - Estelle Spear Bishop
- Division of Gastroenterology and Hepatology, Stanford University School of Medicine, Stanford, California, USA
| | - Chih-Hsin Chen
- Department of Surgery/Pediatric Surgery, Stanford University, Stanford, CA, USA
| | - Anne-Laure Thomas
- Department of Surgery/Pediatric Surgery, Stanford University, Stanford, CA, USA
| | - Chengyi Xu
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Jaeho Park
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Yeongjun Lee
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Ryan Hamnett
- Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, 94305, USA
| | - Weilai Yu
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Samuel E. Root
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Lei Yuan
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Dorine Chakhtoura
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Kyun Kyu Kim
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Donglai Zhong
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Yuya Nishio
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Chuanzhen Zhao
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Can Wu
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Yuanwen Jiang
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Anqi Zhang
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Jinxing Li
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
- Department of Biomedical Engineering and Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI 48823, USA
| | - Weichen Wang
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | | | - Talha A. Rafeeqi
- Department of Surgery/Pediatric Surgery, Stanford University, Stanford, CA, USA
| | - Nofar Mintz Hemed
- Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, United States
| | - Jeffrey B.-H. Tok
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Xiaoke Chen
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Julia A. Kaltschmidt
- Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, 94305, USA
| | - James C.Y. Dunn
- Department of Surgery/Pediatric Surgery, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Zhenan Bao
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
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19
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Yang Y, Xu K, Guan S, Ding J, Wang J, Fang Y, Tian H. Ultraflexible Neural Probes for Multidirectional Neuronal Activity Recordings over Large Spatial and Temporal Scales. NANO LETTERS 2023; 23:8568-8575. [PMID: 37669149 DOI: 10.1021/acs.nanolett.3c02348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/07/2023]
Abstract
The widespread dissemination of ultraflexible neural probes depends on the development of advanced materials and implementation strategies that can allow reliable implantation of ultraflexible neural probes into targeted brain regions, especially deep and difficult-to-access brain regions. Here, we report ultraflexible and multidirectional probes that are encapsulated in a biocompatible polymer alloy with controllable dissolution kinetics. Our probes can be reliably implanted into targeted brain regions over large spatial scales, including deep hindbrain regions that are anatomically difficult-to-access in vivo. Chronically implanted probes can enable long-term, multidirectional recordings from several hundreds of neurons across distributed brain regions. In particular, our results show that 87.0% of chronically recorded neurons in the hindbrain are interneurons, whereas only 41.9% of chronically recorded neurons in the cortex are interneurons. These results demonstrate that our ultraflexible neural probes are a promising tool for large-scale, long-term neural circuit dissection in the brain.
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Affiliation(s)
- Yinan Yang
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ke Xu
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shouliang Guan
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
| | - Jianfei Ding
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
| | - Jinfen Wang
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
| | - Ying Fang
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Huihui Tian
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
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20
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Zhou Y, Yang H, Wang X, Yang H, Sun K, Zhou Z, Sun L, Zhao J, Tao TH, Wei X. A mosquito mouthpart-like bionic neural probe. MICROSYSTEMS & NANOENGINEERING 2023; 9:88. [PMID: 37448967 PMCID: PMC10336119 DOI: 10.1038/s41378-023-00565-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Revised: 05/05/2023] [Accepted: 05/29/2023] [Indexed: 07/18/2023]
Abstract
Advancements in microscale electrode technology have revolutionized the field of neuroscience and clinical applications by offering high temporal and spatial resolution of recording and stimulation. Flexible neural probes, with their mechanical compliance to brain tissue, have been shown to be superior to rigid devices in terms of stability and longevity in chronic recordings. Shuttle devices are commonly used to assist flexible probe implantation; however, the protective membrane of the brain still makes penetration difficult. Hidden damage to brain vessels during implantation is a significant risk. Inspired by the anatomy of the mosquito mouthparts, we present a biomimetic neuroprobe system that integrates high-sensitivity sensors with a high-fidelity multichannel flexible electrode array. This customizable system achieves distributed and minimally invasive implantation across brain regions. Most importantly, the system's nonvisual monitoring capability provides an early warning detection for intracranial soft tissues, such as vessels, reducing the potential for injury during implantation. The neural probe system demonstrates exceptional sensitivity and adaptability to environmental stimuli, as well as outstanding performance in postoperative and chronic recordings. These findings suggest that our biomimetic neural-probe device offers promising potential for future applications in neuroscience and brain-machine interfaces. A mosquito mouthpart-like bionic neural probe consisting of a highly sensitive tactile sensor module, a flexible microelectrode array, and implanted modules that mimic the structure of mosquito mouthparts. The system enables distributed implantation of electrode arrays across multiple brain regions while making the implantation minimally invasive and avoiding additional dural removal. The tactile sensor array can monitor the implantation process to achieve early warning of vascular damage. The excellent postoperative short-term recording performance and long-term neural activity tracking ability demonstrate that the system is a promising tool in the field of brain-computer interfaces.
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Affiliation(s)
- Yu Zhou
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, 200050 Shanghai, China
- School of Graduate Study, University of Chinese Academy of Sciences, 100049 Beijing, China
| | - Huiran Yang
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, 200050 Shanghai, China
- School of Graduate Study, University of Chinese Academy of Sciences, 100049 Beijing, China
| | - Xueying Wang
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, 200050 Shanghai, China
- School of Graduate Study, University of Chinese Academy of Sciences, 100049 Beijing, China
| | - Heng Yang
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, 200050 Shanghai, China
- School of Graduate Study, University of Chinese Academy of Sciences, 100049 Beijing, China
| | - Ke Sun
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, 200050 Shanghai, China
- School of Graduate Study, University of Chinese Academy of Sciences, 100049 Beijing, China
| | - Zhitao Zhou
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, 200050 Shanghai, China
- School of Graduate Study, University of Chinese Academy of Sciences, 100049 Beijing, China
| | - Liuyang Sun
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, 200050 Shanghai, China
- School of Graduate Study, University of Chinese Academy of Sciences, 100049 Beijing, China
- 2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, 200050 Shanghai, China
| | - Jianlong Zhao
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, 200050 Shanghai, China
- School of Graduate Study, University of Chinese Academy of Sciences, 100049 Beijing, China
| | - Tiger H. Tao
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, 200050 Shanghai, China
- School of Graduate Study, University of Chinese Academy of Sciences, 100049 Beijing, China
- 2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, 200050 Shanghai, China
- Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, 100049 Beijing, China
- Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, 200031 Shanghai, China
- Neuroxess Co., Ltd. (Jiangxi), 330029 Nanchang, Jiangxi China
- Guangdong Institute of Intelligence Science and Technology, Hengqin, 519031 Zhuhai, Guangdong China
- Tianqiao and Chrissy Chen Institute for Translational Research, Shanghai, China
| | - Xiaoling Wei
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, 200050 Shanghai, China
- School of Graduate Study, University of Chinese Academy of Sciences, 100049 Beijing, China
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21
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Zhao ET, Hull JM, Mintz Hemed N, Uluşan H, Bartram J, Zhang A, Wang P, Pham A, Ronchi S, Huguenard JR, Hierlemann A, Melosh NA. A CMOS-based highly scalable flexible neural electrode interface. SCIENCE ADVANCES 2023; 9:eadf9524. [PMID: 37285436 PMCID: PMC10246892 DOI: 10.1126/sciadv.adf9524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 05/03/2023] [Indexed: 06/09/2023]
Abstract
Perception, thoughts, and actions are encoded by the coordinated activity of large neuronal populations spread over large areas. However, existing electrophysiological devices are limited by their scalability in capturing this cortex-wide activity. Here, we developed an electrode connector based on an ultra-conformable thin-film electrode array that self-assembles onto silicon microelectrode arrays enabling multithousand channel counts at a millimeter scale. The interconnects are formed using microfabricated electrode pads suspended by thin support arms, termed Flex2Chip. Capillary-assisted assembly drives the pads to deform toward the chip surface, and van der Waals forces maintain this deformation, establishing Ohmic contact. Flex2Chip arrays successfully measured extracellular action potentials ex vivo and resolved micrometer scale seizure propagation trajectories in epileptic mice. We find that seizure dynamics in absence epilepsy in the Scn8a+/- model do not have constant propagation trajectories.
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Affiliation(s)
- Eric T. Zhao
- Department of Chemical Engineering, Stanford University, Stanford, CA, USA
| | - Jacob M. Hull
- Department of Neurology, Stanford University, Stanford, CA, USA
| | - Nofar Mintz Hemed
- Department of Materials Science and Engineering, Stanford University, Stanford, CA, USA
| | - Hasan Uluşan
- Department of Biosystems Engineering, ETH Zürich, Basel, Switzerland
| | - Julian Bartram
- Department of Biosystems Engineering, ETH Zürich, Basel, Switzerland
| | - Anqi Zhang
- Department of Chemical Engineering, Stanford University, Stanford, CA, USA
| | - Pingyu Wang
- Department of Materials Science and Engineering, Stanford University, Stanford, CA, USA
| | - Albert Pham
- Department of Materials Science and Engineering, Stanford University, Stanford, CA, USA
| | - Silvia Ronchi
- Department of Biosystems Engineering, ETH Zürich, Basel, Switzerland
| | | | | | - Nicholas A. Melosh
- Department of Materials Science and Engineering, Stanford University, Stanford, CA, USA
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22
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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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23
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Wang P, Wu EG, Uluşan H, Phillips A, Rose Hays M, Kling A, Zhao ET, Madugula S, Vilkhu RS, Vasireddy PK, Hier- lemann A, Hong G, Chichilnisky E, Melosh NA. Direct-print three-dimensional electrodes for large- scale, high-density, and customizable neural inter- faces. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.30.542925. [PMID: 37398164 PMCID: PMC10312573 DOI: 10.1101/2023.05.30.542925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Silicon-based planar microelectronics is a powerful tool for scalably recording and modulating neural activity at high spatiotemporal resolution, but it remains challenging to target neural structures in three dimensions (3D). We present a method for directly fabricating 3D arrays of tissue-penetrating microelectrodes onto silicon microelectronics. Leveraging a high-resolution 3D printing technology based on 2-photon polymerization and scalable microfabrication processes, we fabricated arrays of 6,600 microelectrodes 10-130 μm tall and at 35-μm pitch onto a planar silicon-based microelectrode array. The process enables customizable electrode shape, height and positioning for precise targeting of neuron populations distributed in 3D. As a proof of concept, we addressed the challenge of specifically targeting retinal ganglion cell (RGC) somas when interfacing with the retina. The array was customized for insertion into the retina and recording from somas while avoiding the axon layer. We verified locations of the microelectrodes with confocal microscopy and recorded high-resolution spontaneous RGC activity at cellular resolution. This revealed strong somatic and dendritic components with little axon contribution, unlike recordings with planar microelectrode arrays. The technology could be a versatile solution for interfacing silicon microelectronics with neural structures and modulating neural activity at large scale with single-cell resolution.
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Affiliation(s)
- Pingyu Wang
- Department of Materials Science and Engineering, Stanford University
| | - Eric G. Wu
- Department of Electrical Engineering, Stanford University, Stanford University
| | - Hasan Uluşan
- Department of Biosystems Science and Engineering in Basel, ETH Zürich
| | - A.J. Phillips
- Department of Electrical Engineering, Stanford University, Stanford University
| | | | | | - Eric T. Zhao
- Department of Chemical Engineering, Stanford University
| | | | - Ramandeep S. Vilkhu
- Department of Electrical Engineering, Stanford University, Stanford University
| | | | | | - Guosong Hong
- Department of Materials Science and Engineering, Stanford University
| | - E.J. Chichilnisky
- Department of Neurosurgery, Stanford University
- Hansen Experimental Physics Laboratory, Stanford University
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24
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Guan S, Tian H, Yang Y, Liu M, Ding J, Wang J, Fang Y. Self-assembled ultraflexible probes for long-term neural recordings and neuromodulation. Nat Protoc 2023; 18:1712-1744. [PMID: 37248393 DOI: 10.1038/s41596-023-00824-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Accepted: 02/14/2023] [Indexed: 05/31/2023]
Abstract
Ultraflexible microelectrode arrays (MEAs) that can stably record from a large number of neurons after their chronic implantation offer opportunities for understanding neural circuit mechanisms and developing next-generation brain-computer interfaces. The implementation of ultraflexible MEAs requires their reliable implantation into deep brain tissues in a minimally invasive manner, as well as their precise integration with optogenetic tools to enable the simultaneous recording of neural activity and neuromodulation. Here, we describe the process for the preparation of elastocapillary self-assembled ultraflexible MEAs, their use in combination with adeno-associated virus vectors carrying opsin genes and promoters to form an optrode probe and their in vivo experimental use in the brains of rodents, enabling electrophysiological recordings and optical modulation of neuronal activity over long periods of time (on the order of weeks to months). The procedures, including device fabrication, probe assembly and implantation, can be completed within 3 weeks. The protocol is intended to facilitate the applications of ultraflexible MEAs for long-term neuronal activity recording and combined electrophysiology and optogenetics. The protocol requires users with expertise in clean room facilities for the fabrication of ultraflexible MEAs.
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Affiliation(s)
- Shouliang Guan
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
| | - Huihui Tian
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, China
| | - Yinan Yang
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Mengcheng Liu
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, China
| | - Jianfei Ding
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, China
| | - Jinfen Wang
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, China
| | - Ying Fang
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, China.
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China.
- University of Chinese Academy of Sciences, Beijing, China.
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25
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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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26
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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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27
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Letner JG, Patel PR, Hsieh JC, Smith Flores IM, della Valle E, Walker LA, Weiland JD, Chestek CA, Cai D. Post-explant profiling of subcellular-scale carbon fiber intracortical electrodes and surrounding neurons enables modeling of recorded electrophysiology. J Neural Eng 2023; 20:026019. [PMID: 36848679 PMCID: PMC10022369 DOI: 10.1088/1741-2552/acbf78] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 01/12/2023] [Accepted: 02/27/2023] [Indexed: 03/01/2023]
Abstract
Objective.Characterizing the relationship between neuron spiking and the signals that electrodes record is vital to defining the neural circuits driving brain function and informing clinical brain-machine interface design. However, high electrode biocompatibility and precisely localizing neurons around the electrodes are critical to defining this relationship.Approach.Here, we demonstrate consistent localization of the recording site tips of subcellular-scale (6.8µm diameter) carbon fiber electrodes and the positions of surrounding neurons. We implanted male rats with carbon fiber electrode arrays for 6 or 12+ weeks targeting layer V motor cortex. After explanting the arrays, we immunostained the implant site and localized putative recording site tips with subcellular-cellular resolution. We then 3D segmented neuron somata within a 50µm radius from implanted tips to measure neuron positions and health and compare to healthy cortex with symmetric stereotaxic coordinates.Main results.Immunostaining of astrocyte, microglia, and neuron markers confirmed that overall tissue health was indicative of high biocompatibility near the tips. While neurons near implanted carbon fibers were stretched, their number and distribution were similar to hypothetical fibers placed in healthy contralateral brain. Such similar neuron distributions suggest that these minimally invasive electrodes demonstrate the potential to sample naturalistic neural populations. This motivated the prediction of spikes produced by nearby neurons using a simple point source model fit using recorded electrophysiology and the mean positions of the nearest neurons observed in histology. Comparing spike amplitudes suggests that the radius at which single units can be distinguished from others is near the fourth closest neuron (30.7 ± 4.6µm,X-± S) in layer V motor cortex.Significance.Collectively, these data and simulations provide the first direct evidence that neuron placement in the immediate vicinity of the recording site influences how many spike clusters can be reliably identified by spike sorting.
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Affiliation(s)
- Joseph G Letner
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Paras R Patel
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Jung-Chien Hsieh
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Israel M Smith Flores
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Elena della Valle
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Logan A Walker
- Biophysics Program, University of Michigan, Ann Arbor, MI 48109, United States of America
- Department of Computational Medicine and Bioinformatics, Michigan Medicine, Ann Arbor, MI 48109, United States of America
| | - James D Weiland
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, United States of America
- Department of Ophthalmology and Visual Sciences, Kellogg Eye Center, University of Michigan, Ann Arbor, MI 48105, United States of America
| | - Cynthia A Chestek
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, United States of America
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109, United States of America
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, United States of America
- Robotics Department, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Dawen Cai
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109, United States of America
- Biophysics Program, University of Michigan, Ann Arbor, MI 48109, United States of America
- Department of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, MI 48109, United States of America
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Mintz Hemed N, Melosh NA. An integrated perspective for the diagnosis and therapy of neurodevelopmental disorders - From an engineering point of view. Adv Drug Deliv Rev 2023; 194:114723. [PMID: 36746077 DOI: 10.1016/j.addr.2023.114723] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 12/14/2022] [Accepted: 01/29/2023] [Indexed: 02/05/2023]
Abstract
Neurodevelopmental disorders (NDDs) are complex conditions with largely unknown pathophysiology. While many NDD symptoms are familiar, the cause of these disorders remains unclear and may involve a combination of genetic, biological, psychosocial, and environmental risk factors. Current diagnosis relies heavily on behaviorally defined criteria, which may be biased by the clinical team's professional and cultural expectations, thus a push for new biological-based biomarkers for NDDs diagnosis is underway. Emerging new research technologies offer an unprecedented view into the electrical, chemical, and physiological activity in the brain and with further development in humans may provide clinically relevant diagnoses. These could also be extended to new treatment options, which can start to address the underlying physiological issues. When combined with current speech, language, occupational therapy, and pharmacological treatment these could greatly improve patient outcomes. The current review will discuss the latest technologies that are being used or may be used for NDDs diagnosis and treatment. The aim is to provide an inspiring and forward-looking view for future research in the field.
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Affiliation(s)
- Nofar Mintz Hemed
- Department of Materials Science and Engineering, Stanford University, Stanford, CA 94305, USA.
| | - Nicholas A Melosh
- Department of Materials Science and Engineering, Stanford University, Stanford, CA 94305, USA
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Chen C, Feng J, Li J, Guo Y, Shi X, Peng H. Functional Fiber Materials to Smart Fiber Devices. Chem Rev 2023; 123:613-662. [PMID: 35977344 DOI: 10.1021/acs.chemrev.2c00192] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
The development of fiber materials has accompanied the evolution of human civilization for centuries. Recent advances in materials science and chemistry offered fibers new applications with various functions, including energy harvesting, energy storing, displaying, health monitoring and treating, and computing. The unique one-dimensional shape of fiber devices endows them advantages to work as human-interfaced electronics due to the small size, lightweight, flexibility, and feasibility for integration into large-scale textile systems. In this review, we first present a discussion of the basics of fiber materials and the design principles of fiber devices, followed by a comprehensive analysis on recently developed fiber devices. Finally, we provide the current challenges facing this field and give an outlook on future research directions. With novel fiber devices and new applications continuing to be discovered after two decades of research, we envision that new fiber devices could have an important impact on our life in the near future.
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Affiliation(s)
- Chuanrui Chen
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, and Laboratory of Advanced Materials, Fudan University, Shanghai 200438, P. R. China
| | - Jianyou Feng
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, and Laboratory of Advanced Materials, Fudan University, Shanghai 200438, P. R. China
| | - Jiaxin Li
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, and Laboratory of Advanced Materials, Fudan University, Shanghai 200438, P. R. China
| | - Yue Guo
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, and Laboratory of Advanced Materials, Fudan University, Shanghai 200438, P. R. China
| | - Xiang Shi
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, and Laboratory of Advanced Materials, Fudan University, Shanghai 200438, P. R. China
| | - Huisheng Peng
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, and Laboratory of Advanced Materials, Fudan University, Shanghai 200438, P. R. China
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Wang Y, Yang X, Zhang X, Wang Y, Pei W. Implantable intracortical microelectrodes: reviewing the present with a focus on the future. MICROSYSTEMS & NANOENGINEERING 2023; 9:7. [PMID: 36620394 PMCID: PMC9814492 DOI: 10.1038/s41378-022-00451-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/07/2022] [Revised: 08/08/2022] [Accepted: 08/22/2022] [Indexed: 06/17/2023]
Abstract
Implantable intracortical microelectrodes can record a neuron's rapidly changing action potentials (spikes). In vivo neural activity recording methods often have either high temporal or spatial resolution, but not both. There is an increasing need to record more neurons over a longer duration in vivo. However, there remain many challenges to overcome before achieving long-term, stable, high-quality recordings and realizing comprehensive, accurate brain activity analysis. Based on the vision of an idealized implantable microelectrode device, the performance requirements for microelectrodes are divided into four aspects, including recording quality, recording stability, recording throughput, and multifunctionality, which are presented in order of importance. The challenges and current possible solutions for implantable microelectrodes are given from the perspective of each aspect. The current developments in microelectrode technology are analyzed and summarized.
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Affiliation(s)
- Yang 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
| | - Xinze Yang
- 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
| | - Xiwen Zhang
- 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
| | - 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
| | - 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
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31
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Farnum A, Parnas M, Hoque Apu E, Cox E, Lefevre N, Contag CH, Saha D. Harnessing insect olfactory neural circuits for detecting and discriminating human cancers. Biosens Bioelectron 2023; 219:114814. [PMID: 36327558 DOI: 10.1016/j.bios.2022.114814] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 10/04/2022] [Accepted: 10/11/2022] [Indexed: 11/06/2022]
Abstract
There is overwhelming evidence that presence of cancer alters cellular metabolic processes, and these changes are manifested in emitted volatile organic compound (VOC) compositions of cancer cells. Here, we take a novel forward engineering approach by developing an insect olfactory neural circuit-based VOC sensor for cancer detection. We obtained oral cancer cell culture VOC-evoked extracellular neural responses from in vivo insect (locust) antennal lobe neurons. We employed biological neural computations of the antennal lobe circuitry for generating spatiotemporal neuronal response templates corresponding to each cell culture VOC mixture, and employed these neuronal templates to distinguish oral cancer cell lines (SAS, Ca9-22, and HSC-3) vs. a non-cancer cell line (HaCaT). Our results demonstrate that three different human oral cancers can be robustly distinguished from each other and from a non-cancer oral cell line. By using high-dimensional population neuronal response analysis and leave-one-trial-out methodology, our approach yielded high classification success for each cell line tested. Our analyses achieved 76-100% success in identifying cell lines by using the population neural response (n = 194) collected for the entire duration of the cell culture study. We also demonstrate this cancer detection technique can distinguish between different types of oral cancers and non-cancer at different time-matched points of growth. This brain-based cancer detection approach is fast as it can differentiate between VOC mixtures within 250 ms of stimulus onset. Our brain-based cancer detection system comprises a novel VOC sensing methodology that incorporates entire biological chemosensory arrays, biological signal transduction, and neuronal computations in a form of a forward-engineered technology for cancer VOC detection.
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Affiliation(s)
- Alexander Farnum
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Michael Parnas
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Ehsanul Hoque Apu
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA; Division of Hematology and Oncology, Department of Internal Medicine, Michigan Medicine, University of Michigan, Ann Arbor, MI, 48108, USA
| | - Elyssa Cox
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Noël Lefevre
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Christopher H Contag
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA; Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, USA
| | - Debajit Saha
- Department of Biomedical Engineering and the Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, USA.
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32
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Chen Z, Liang Q, Wei Z, Chen X, Shi Q, Yu Z, Sun T. An Overview of In Vitro Biological Neural Networks for Robot Intelligence. CYBORG AND BIONIC SYSTEMS 2023; 4:0001. [PMID: 37040493 PMCID: PMC10076061 DOI: 10.34133/cbsystems.0001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 10/17/2022] [Indexed: 01/12/2023] Open
Abstract
In vitro biological neural networks (BNNs) interconnected with robots, so-called BNN-based neurorobotic systems, can interact with the external world, so that they can present some preliminary intelligent behaviors, including learning, memory, robot control, etc. This work aims to provide a comprehensive overview of the intelligent behaviors presented by the BNN-based neurorobotic systems, with a particular focus on those related to robot intelligence. In this work, we first introduce the necessary biological background to understand the 2 characteristics of the BNNs: nonlinear computing capacity and network plasticity. Then, we describe the typical architecture of the BNN-based neurorobotic systems and outline the mainstream techniques to realize such an architecture from 2 aspects: from robots to BNNs and from BNNs to robots. Next, we separate the intelligent behaviors into 2 parts according to whether they rely solely on the computing capacity (computing capacity-dependent) or depend also on the network plasticity (network plasticity-dependent), which are then expounded respectively, with a focus on those related to the realization of robot intelligence. Finally, the development trends and challenges of the BNN-based neurorobotic systems are discussed.
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Affiliation(s)
- Zhe Chen
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
- Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology), Ministry of Education, Beijing 10081, China
- Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing 100081, China
| | - Qian Liang
- Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology), Ministry of Education, Beijing 10081, China
- Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing 100081, China
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China
| | - Zihou Wei
- Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology), Ministry of Education, Beijing 10081, China
- Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing 100081, China
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China
| | - Xie Chen
- Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology), Ministry of Education, Beijing 10081, China
- Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing 100081, China
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China
| | - Qing Shi
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
- Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology), Ministry of Education, Beijing 10081, China
- Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing 100081, China
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China
| | - Zhiqiang Yu
- Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology), Ministry of Education, Beijing 10081, China
- Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing 100081, China
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China
| | - Tao Sun
- Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology), Ministry of Education, Beijing 10081, China
- Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing 100081, China
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China
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33
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Yi D, Yao Y, Wang Y, Chen L. Manufacturing Processes of Implantable Microelectrode Array for In Vivo Neural Electrophysiological Recordings and Stimulation: A State-Of-the-Art Review. JOURNAL OF MICRO- AND NANO-MANUFACTURING 2022; 10:041001. [PMID: 37860671 PMCID: PMC10583290 DOI: 10.1115/1.4063179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 08/08/2023] [Indexed: 10/21/2023]
Abstract
Electrophysiological recording and stimulation of neuron activities are important for us to understand the function and dysfunction of the nervous system. To record/stimulate neuron activities as voltage fluctuation extracellularly, microelectrode array (MEA) implants are a promising tool to provide high temporal and spatial resolution for neuroscience studies and medical treatments. The design configuration and recording capabilities of the MEAs have evolved dramatically since their invention and manufacturing process development has been a key driving force for such advancement. Over the past decade, since the White House Brain Research Through Advancing Innovative Neurotechnologies (BRAIN) Initiative launched in 2013, advanced manufacturing processes have enabled advanced MEAs with increased channel count and density, access to more brain areas, more reliable chronic performance, as well as minimal invasiveness and tissue reaction. In this state-of-the-art review paper, three major types of electrophysiological recording MEAs widely used nowadays, namely, microwire-based, silicon-based, and flexible MEAs are introduced and discussed. Conventional design and manufacturing processes and materials used for each type are elaborated, followed by a review of further development and recent advances in manufacturing technologies and the enabling new designs and capabilities. The review concludes with a discussion on potential future directions of manufacturing process development to enable the long-term goal of large-scale high-density brain-wide chronic recordings in freely moving animals.
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Affiliation(s)
- Dongyang Yi
- Department of Mechanical and Industrial Engineering, University of Massachusetts Lowell, 1 University Avenue, Lowell, MA 01854
| | - Yao Yao
- Department of Industrial and Systems Engineering, University of Missouri, 416 South 6th Street, Columbia, MO 65211
| | - Yi Wang
- Department of Industrial and Systems Engineering, University of Missouri, E3437C Thomas & Nell Lafferre Hall, 416 South 6th Street, Columbia, MO 65211
| | - Lei Chen
- Department of Mechanical and Industrial Engineering, University of Massachusetts Lowell, 1 University Avenue, Lowell, MA 01854
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34
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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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35
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Chiappalone M, Cota VR, Carè M, Di Florio M, Beaubois R, Buccelli S, Barban F, Brofiga M, Averna A, Bonacini F, Guggenmos DJ, Bornat Y, Massobrio P, Bonifazi P, Levi T. Neuromorphic-Based Neuroprostheses for Brain Rewiring: State-of-the-Art and Perspectives in Neuroengineering. Brain Sci 2022; 12:1578. [PMID: 36421904 PMCID: PMC9688667 DOI: 10.3390/brainsci12111578] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 11/09/2022] [Accepted: 11/17/2022] [Indexed: 08/27/2023] Open
Abstract
Neuroprostheses are neuroengineering devices that have an interface with the nervous system and supplement or substitute functionality in people with disabilities. In the collective imagination, neuroprostheses are mostly used to restore sensory or motor capabilities, but in recent years, new devices directly acting at the brain level have been proposed. In order to design the next-generation of neuroprosthetic devices for brain repair, we foresee the increasing exploitation of closed-loop systems enabled with neuromorphic elements due to their intrinsic energy efficiency, their capability to perform real-time data processing, and of mimicking neurobiological computation for an improved synergy between the technological and biological counterparts. In this manuscript, after providing definitions of key concepts, we reviewed the first exploitation of a real-time hardware neuromorphic prosthesis to restore the bidirectional communication between two neuronal populations in vitro. Starting from that 'case-study', we provide perspectives on the technological improvements for real-time interfacing and processing of neural signals and their potential usage for novel in vitro and in vivo experimental designs. The development of innovative neuroprosthetics for translational purposes is also presented and discussed. In our understanding, the pursuit of neuromorphic-based closed-loop neuroprostheses may spur the development of novel powerful technologies, such as 'brain-prostheses', capable of rewiring and/or substituting the injured nervous system.
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Affiliation(s)
- Michela Chiappalone
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Vinicius R. Cota
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Marta Carè
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Mattia Di Florio
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
| | - Romain Beaubois
- IMS Laboratory, CNRS UMR 5218, University of Bordeaux, 33405 Talence, France
| | - Stefano Buccelli
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Federico Barban
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Martina Brofiga
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
| | - Alberto Averna
- Department of Neurology, Bern University Hospital, University of Bern, 3012 Bern, Switzerland
| | - Francesco Bonacini
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
| | - David J. Guggenmos
- Department of Rehabilitation Medicine, University of Kansas Medical Center, Kansas City, KS 66103, USA
- Landon Center on Aging, University of Kansas Medical Center, Kansas City, KS 66103, USA
| | - Yannick Bornat
- IMS Laboratory, CNRS UMR 5218, University of Bordeaux, 33405 Talence, France
| | - Paolo Massobrio
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
- National Institute for Nuclear Physics (INFN), 16146 Genova, Italy
| | - Paolo Bonifazi
- IKERBASQUE, The Basque Fundation, 48009 Bilbao, Spain
- Biocruces Health Research Institute, 48903 Barakaldo, Spain
| | - Timothée Levi
- IMS Laboratory, CNRS UMR 5218, University of Bordeaux, 33405 Talence, France
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Khona M, Fiete IR. Attractor and integrator networks in the brain. Nat Rev Neurosci 2022; 23:744-766. [DOI: 10.1038/s41583-022-00642-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/22/2022] [Indexed: 11/06/2022]
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37
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Banno T, Tsuruhara S, Seikoba Y, Tonai R, Yamashita K, Idogawa S, Kita Y, Suzuki K, Yagi Y, Kondo Y, Numano R, Koida K, Kawano T. Nanoneedle-Electrode Devices for In Vivo Recording of Extracellular Action Potentials. ACS NANO 2022; 16:10692-10700. [PMID: 35786946 DOI: 10.1021/acsnano.2c02399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Microscale needle-like electrode technologies offer in vivo extracellular recording with a high spatiotemporal resolution. Further miniaturization of needles to nanoscale minimizes tissue injuries; however, a reduced electrode area increases electrical impedance that degrades the quality of neuronal signal recording. We overcome this limitation by fabricating a 300 nm tip diameter and 200 μm long needle electrode where the amplitude gain with a high-impedance electrode (>15 MΩ, 1 kHz) was improved from 0.54 (-5.4 dB) to 0.89 (-1.0 dB) by stacking it on an amplifier module of source follower. The nanoelectrode provided the recording of both local field potential (<300 Hz) and action potential (>500 Hz) in the mouse cortex, in contrast to the electrode without the amplifier. These results suggest that microelectrodes can be further minimized by the proposed amplifier configuration for low-invasive recording and electrophysiological studies in submicron areas in tissues, such as dendrites and axons.
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Affiliation(s)
- Tomoaki Banno
- Department of Electrical and Electronic Information Engineering, Toyohashi University of Technology, Toyohashi, Aichi 441-8580, Japan
| | - Shuhei Tsuruhara
- Department of Electrical and Electronic Information Engineering, Toyohashi University of Technology, Toyohashi, Aichi 441-8580, Japan
| | - Yu Seikoba
- Department of Electrical and Electronic Information Engineering, Toyohashi University of Technology, Toyohashi, Aichi 441-8580, Japan
| | - Ryohei Tonai
- Department of Electrical and Electronic Information Engineering, Toyohashi University of Technology, Toyohashi, Aichi 441-8580, Japan
| | - Koji Yamashita
- Electronics-Inspired Interdisciplinary Research Institute, Toyohashi University of Technology, Toyohashi, Aichi 441-8580, Japan
| | - Shinnosuke Idogawa
- Department of Electronic engineering, National Institute of Technology, Kushiro College, Kushiro, Hokkaido 084-0916, Japan
| | - Yuto Kita
- Department of Electrical and Electronic Information Engineering, Toyohashi University of Technology, Toyohashi, Aichi 441-8580, Japan
| | - Ko Suzuki
- TechnoPro R&D Company, Minatoku, Tokyo 106-6135, Japan
| | - Yuki Yagi
- Department of Electrical and Electronic Information Engineering, Toyohashi University of Technology, Toyohashi, Aichi 441-8580, Japan
| | - Yuki Kondo
- Department of Electrical and Electronic Information Engineering, Toyohashi University of Technology, Toyohashi, Aichi 441-8580, Japan
| | - Rika Numano
- Electronics-Inspired Interdisciplinary Research Institute, Toyohashi University of Technology, Toyohashi, Aichi 441-8580, Japan
- Applied Chemistry and Life Science, Toyohashi University of Technology, Toyohashi, Aichi 441-8580, Japan
| | - Kowa Koida
- Electronics-Inspired Interdisciplinary Research Institute, Toyohashi University of Technology, Toyohashi, Aichi 441-8580, Japan
- Department of Computer and Science and Engineering, Toyohashi University of Technology, Toyohashi, Aichi 441-8580, Japan
| | - Takeshi Kawano
- Department of Electrical and Electronic Information Engineering, Toyohashi University of Technology, Toyohashi, Aichi 441-8580, Japan
- Electronics-Inspired Interdisciplinary Research Institute, Toyohashi University of Technology, Toyohashi, Aichi 441-8580, Japan
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38
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Schröter M, Wang C, Terrigno M, Hornauer P, Huang Z, Jagasia R, Hierlemann A. Functional imaging of brain organoids using high-density microelectrode arrays. MRS BULLETIN 2022; 47:530-544. [PMID: 36120104 PMCID: PMC9474390 DOI: 10.1557/s43577-022-00282-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 02/02/2022] [Indexed: 05/31/2023]
Abstract
ABSTRACT Studies have provided evidence that human cerebral organoids (hCOs) recapitulate fundamental milestones of early brain development, but many important questions regarding their functionality and electrophysiological properties persist. High-density microelectrode arrays (HD-MEAs) represent an attractive analysis platform to perform functional studies of neuronal networks at the cellular and network scale. Here, we use HD-MEAs to derive large-scale electrophysiological recordings from sliced hCOs. We record the activity of hCO slices over several weeks and probe observed neuronal dynamics pharmacologically. Moreover, we present results on how the obtained recordings can be spike-sorted and subsequently studied across scales. For example, we show how to track single neurons across several days on the HD-MEA and how to infer axonal action potential velocities. We also infer putative functional connectivity from hCO recordings. The introduced methodology will contribute to a better understanding of developing neuronal networks in brain organoids and provide new means for their functional characterization. IMPACT STATEMENT Human cerebral organoids (hCOs) represent an attractive in vitro model system to study key physiological mechanisms underlying early neuronal network formation in tissue with healthy or disease-related genetic backgrounds. Despite remarkable advances in the generation of brain organoids, knowledge on the functionality of their neuronal circuits is still scarce. Here, we used complementary metal-oxide-semiconductor (CMOS)-based high-density microelectrode arrays (HD-MEAs) to perform large-scale recordings from sliced hCOs over several weeks and quantified their activity across scales. Using single-cell and network metrics, we were able to probe aspects of hCO neurophysiology that are more difficult to obtain with other techniques, such as patch clamping (lower yield) and calcium imaging (lower temporal resolution). These metrics included, for example, extracellular action potential (AP) waveform features and axonal AP velocity at the cellular level, as well as functional connectivity at the network level. Analysis was enabled by the large sensing area and the high spatiotemporal resolution provided by HD-MEAs, which allowed recordings from hundreds of neurons and spike sorting of their activity. Our results demonstrate that HD-MEAs provide a multi-purpose platform for the functional characterization of hCOs, which will be key in improving our understanding of this model system and assessing its relevance for translational research. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1557/s43577-022-00282-w.
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Affiliation(s)
- Manuel Schröter
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Congwei Wang
- NRD, F. Hoffmann-La Roche Ltd., Roche Innovation Center Basel, Basel, Switzerland
| | - Marco Terrigno
- NRD, F. Hoffmann-La Roche Ltd., Roche Innovation Center Basel, Basel, Switzerland
| | - Philipp Hornauer
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Ziqiang Huang
- EMBL Imaging Centre, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Ravi Jagasia
- NRD, F. Hoffmann-La Roche Ltd., Roche Innovation Center Basel, Basel, Switzerland
| | - Andreas Hierlemann
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
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Lee SH, Thunemann M, Lee K, Cleary DR, Tonsfeldt KJ, Oh H, Azzazy F, Tchoe Y, Bourhis AM, Hossain L, Ro YG, Tanaka A, Kılıç K, Devor A, Dayeh SA. Scalable Thousand Channel Penetrating Microneedle Arrays on Flex for Multimodal and Large Area Coverage BrainMachine Interfaces. ADVANCED FUNCTIONAL MATERIALS 2022; 32:2112045. [PMID: 36381629 PMCID: PMC9648634 DOI: 10.1002/adfm.202112045] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Indexed: 05/29/2023]
Abstract
The Utah array powers cutting-edge projects for restoration of neurological function, such as BrainGate, but the underlying electrode technology has itself advanced little in the last three decades. Here, advanced dual-side lithographic microfabrication processes is exploited to demonstrate a 1024-channel penetrating silicon microneedle array (SiMNA) that is scalable in its recording capabilities and cortical coverage and is suitable for clinical translation. The SiMNA is the first penetrating microneedle array with a flexible backing that affords compliancy to brain movements. In addition, the SiMNA is optically transparent permitting simultaneous optical and electrophysiological interrogation of neuronal activity. The SiMNA is used to demonstrate reliable recordings of spontaneous and evoked field potentials and of single unit activity in chronically implanted mice for up to 196 days in response to optogenetic and to whisker air-puff stimuli. Significantly, the 1024-channel SiMNA establishes detailed spatiotemporal mapping of broadband brain activity in rats. This novel scalable and biocompatible SiMNA with its multimodal capability and sensitivity to broadband brain activity will accelerate the progress in fundamental neurophysiological investigations and establishes a new milestone for penetrating and large area coverage microelectrode arrays for brain-machine interfaces.
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Affiliation(s)
- Sang Heon Lee
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, CA 92093, USA
| | - Martin Thunemann
- Biomedical Engineering Department, Boston University, Boston, MA 02215, USA
| | - Keundong Lee
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, CA 92093, USA
| | - Daniel R Cleary
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, CA 92093, USA
- Department of Neurological Surgery, University of California San Diego, La Jolla, CA 92093, USA
| | - Karen J Tonsfeldt
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, CA 92093, USA
- Department of Obstetrics, Gynecology, and Reproductive Sciences, Center for Reproductive Science and Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Hongseok Oh
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, CA 92093, USA
| | - Farid Azzazy
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, CA 92093, USA
| | - Youngbin Tchoe
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, CA 92093, USA
| | - Andrew M Bourhis
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, CA 92093, USA
| | - Lorraine Hossain
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, CA 92093, USA
- Graduate Program of Materials Science and Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Yun Goo Ro
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, CA 92093, USA
| | - Atsunori Tanaka
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, CA 92093, USA
- Graduate Program of Materials Science and Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Kıvılcım Kılıç
- Biomedical Engineering Department, Boston University, Boston, MA 02215, USA
| | - Anna Devor
- Biomedical Engineering Department, Boston University, Boston, MA 02215, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Shadi A Dayeh
- Integrated Electronics and Biointerfaces Laboratory, Department of Electrical and Computer Engineering, University of California San Diego, CA 92093, USA
- Graduate Program of Materials Science and Engineering, University of California San Diego, La Jolla, CA 92093, USA
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40
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Tringides CM, Mooney DJ. Materials for Implantable Surface Electrode Arrays: Current Status and Future Directions. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2022; 34:e2107207. [PMID: 34716730 DOI: 10.1002/adma.202107207] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 10/26/2021] [Indexed: 06/13/2023]
Abstract
Surface electrode arrays are mainly fabricated from rigid or elastic materials, and precisely manipulated ductile metal films, which offer limited stretchability. However, the living tissues to which they are applied are nonlinear viscoelastic materials, which can undergo significant mechanical deformation in dynamic biological environments. Further, the same arrays and compositions are often repurposed for vastly different tissues rather than optimizing the materials and mechanical properties of the implant for the target application. By first characterizing the desired biological environment, and then designing a technology for a particular organ, surface electrode arrays may be more conformable, and offer better interfaces to tissues while causing less damage. Here, the various materials used in each component of a surface electrode array are first reviewed, and then electrically active implants in three specific biological systems, the nervous system, the muscular system, and skin, are described. Finally, the fabrication of next-generation surface arrays that overcome current limitations is discussed.
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Affiliation(s)
- Christina M Tringides
- Harvard Program in Biophysics, Harvard University, Cambridge, MA, 02138, USA
- Harvard-MIT Division in Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, MA, 02138, USA
| | - David J Mooney
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, MA, 02138, USA
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA
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Bierman-Duquette RD, Safarians G, Huang J, Rajput B, Chen JY, Wang ZZ, Seidlits SK. Engineering Tissues of the Central Nervous System: Interfacing Conductive Biomaterials with Neural Stem/Progenitor Cells. Adv Healthc Mater 2022; 11:e2101577. [PMID: 34808031 PMCID: PMC8986557 DOI: 10.1002/adhm.202101577] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 10/31/2021] [Indexed: 12/19/2022]
Abstract
Conductive biomaterials provide an important control for engineering neural tissues, where electrical stimulation can potentially direct neural stem/progenitor cell (NS/PC) maturation into functional neuronal networks. It is anticipated that stem cell-based therapies to repair damaged central nervous system (CNS) tissues and ex vivo, "tissue chip" models of the CNS and its pathologies will each benefit from the development of biocompatible, biodegradable, and conductive biomaterials. Here, technological advances in conductive biomaterials are reviewed over the past two decades that may facilitate the development of engineered tissues with integrated physiological and electrical functionalities. First, one briefly introduces NS/PCs of the CNS. Then, the significance of incorporating microenvironmental cues, to which NS/PCs are naturally programmed to respond, into biomaterial scaffolds is discussed with a focus on electrical cues. Next, practical design considerations for conductive biomaterials are discussed followed by a review of studies evaluating how conductive biomaterials can be engineered to control NS/PC behavior by mimicking specific functionalities in the CNS microenvironment. Finally, steps researchers can take to move NS/PC-interfacing, conductive materials closer to clinical translation are discussed.
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Affiliation(s)
| | - Gevick Safarians
- Department of Bioengineering, University of California Los Angeles, USA
| | - Joyce Huang
- Department of Bioengineering, University of California Los Angeles, USA
| | - Bushra Rajput
- Department of Bioengineering, University of California Los Angeles, USA
| | - Jessica Y. Chen
- Department of Bioengineering, University of California Los Angeles, USA
- David Geffen School of Medicine, University of California Los Angeles, USA
| | - Ze Zhong Wang
- Department of Bioengineering, University of California Los Angeles, USA
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Yamashita K, Sawahata H, Yamagiwa S, Yokoyama S, Numano R, Koida K, Kawano T. A floating 5 μm-diameter needle electrode on the tissue for damage-reduced chronic neuronal recording in mice. LAB ON A CHIP 2022; 22:747-756. [PMID: 35044407 DOI: 10.1039/d1lc01031j] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
Microelectrode technology is essential in electrophysiology and has made contributions to neuroscience as well as to medical applications. However, it is necessary to minimize tissue damage associated with needle-like electrode on the brain tissue and the implantation surgery, which makes stable chronic recording impossible. Here, we report on an approach for using a 5 μm-diameter needle electrode, which enables the following of tissue motions, via a surgical method. The electrode is placed on the brain tissue of a mouse with a dissolvable material, reducing the physical stress to the tissue; this is followed by the implantation of the electrode device in the brain without fixing it to the cranium, achieving a floating electrode architecture on the tissue. The electrode shows stable recording with no significant degradation of the signal-to-noise ratios for 6 months, and minimized tissue damage is confirmed compared to that when using a cranium-fixed electrode with the same needle geometry.
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Affiliation(s)
- Koji Yamashita
- Department of Electrical and Electronic Information Engineering, Toyohashi University of Technology, Aichi, Japan.
| | | | - Shota Yamagiwa
- Department of Electrical and Electronic Information Engineering, Toyohashi University of Technology, Aichi, Japan.
| | | | - Rika Numano
- Electronics-Interdisciplinary Research Institute (EIIRIS), Toyohashi University of Technology, Aichi, Japan
- Department of Applied Chemistry and Life Science, Toyohashi University of Technology, Aichi, Japan
| | - Kowa Koida
- Electronics-Interdisciplinary Research Institute (EIIRIS), Toyohashi University of Technology, Aichi, Japan
- Department of Computer Science and Engineering, Toyohashi University of Technology, Aichi, Japan
| | - Takeshi Kawano
- Department of Electrical and Electronic Information Engineering, Toyohashi University of Technology, Aichi, Japan.
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43
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Racz RR, Kollo M, Racz G, Bulz C, Ackels T, Warner T, Wray W, Kiskin N, Chen C, Ye Z, de Hoz L, Rancz E, Schaefer AT. jULIEs: nanostructured polytrodes for low traumatic extracellular recordings and stimulation in the mammalian brain. J Neural Eng 2022; 19. [PMID: 35108701 DOI: 10.1088/1741-2552/ac514f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 02/02/2022] [Indexed: 11/11/2022]
Abstract
Objective Extracellular microelectrode techniques are the most widely used approach to interrogate neuronal populations. Regardless of the manufacturing method, damage to the vasculature and circuit function during probe insertion remains a concern. Reducing the footprint of the penetrating probes is a potential solution to this issue. However, coupling to the extracellular signals requires careful surface engineering. Approach Here, we show that continuously drawn SiO2-insulated ultra-microelectrode fibres offer an attractive substrate to address these challenges. Individual fibres can be fabricated to >10m continuous stretches and a selection of diameters below 30 µm with a low resistance (<100 Ω/m), continuous metal core of <10 µm and atomically flat smooth shank surfaces. To optimize the properties of the miniaturised electrode-tissue interface, we electrodeposit rough Au structures followed by ~20nm IrOx film by electrodeposition resulting in reduction of the interfacial impedance to <500kΩ at 1 kHz. Main results We demonstrate that these ultra-low impedance electrodes (jULIEs) can record and stimulate single and multi-unit activity with minimal tissue disturbance and exceptional signal-to-noise ratio in both superficial (~40µm) and deep (~6mm) structures of the mouse brain. We further show that sensor modifications are stable and probe manufacturing is reproducible. Significance Minimally perturbing bidirectional neural interfacing can reveal circuit function in the mammalian brain in vivo.
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Affiliation(s)
- Romeo Robert Racz
- Neurophysiology, The Francis Crick Institute, 1 MIdland Road, London, London, NW1 1AT, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Mihaly Kollo
- The Francis Crick Institute, 1 Midland Road, London, NW1 1AT, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Gabriella Racz
- The Francis Crick Institute, 1 Midland Road, London, NW1 1AT, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Ciprian Bulz
- University of Southampton, University Road, Southampton, Hampshire, SO17 1BJ, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Tobias Ackels
- The Francis Crick Institute, 1 Midland Road, London, NW1 1AT, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Tom Warner
- The Francis Crick Institute, 1 Midland Road, London, NW1 1AT, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - William Wray
- The Francis Crick Institute, 1 Midland Road, London, NW1 1AT, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Nikolai Kiskin
- Department of Bioengineering, Imperial College London, Exhibition Road, London, London, SW7 2AZ, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Chi Chen
- Department of Neurogenetics, Charité Universitätsmedizin Berlin, Hermann-Rein-Straße 3, Berlin, Berlin, 10117, GERMANY
| | - Zhiwen Ye
- University of Washington, 1959 NE Pacific St., Seattle, Washington, 98195-7420, UNITED STATES
| | - Livia de Hoz
- Neuroscience Research Center, Charité Universitätsmedizin Berlin, Virchowweg 6, Berlin, Berlin, 10117, GERMANY
| | - Ede Rancz
- The Francis Crick Institute, 1 Midland Road, London, NW1 1AT, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Andreas T Schaefer
- The Francis Crick Institute, 1 Midland Road, London, NW1 1AT, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
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44
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Gao L, Wang J, Zhao Y, Li H, Liu M, Ding J, Tian H, Guan S, Fang Y. Free-Standing Nanofilm Electrode Arrays for Long-Term Stable Neural Interfacings. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2022; 34:e2107343. [PMID: 34796566 DOI: 10.1002/adma.202107343] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 11/16/2021] [Indexed: 06/13/2023]
Abstract
Flexible neural electrodes integrated on micrometer-thick polymer substrates offer important opportunities for improving the stability of neuronal activity recordings during cognitive processes. However, the bending stiffness of micrometer-thick polymer substrates is typically two orders of magnitude higher than that of nanofilm electrodes, making it a limiting factor in electrode-tissue interfacings. Here, this limitation is overcome by developing self-assembled nanofilm electrode arrays (NEAs) that consist of high-density, free-standing gold nanofilm electrodes. Chronically implanted NEAs can form intimate and innervated interfaces with neural tissue, enabling stable neuronal activity recordings across multiple brain regions over several months. As an application example, the activities of the same neuronal populations are tracked across odor discrimination reversal learning and it is illustrated how dorsal striatal neurons represent and update stimulus-outcome associations across multiple timescales. The results underscore the potential of free-standing nanoscale materials for interfacing biological systems over long terms.
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Affiliation(s)
- Lei Gao
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, 100190, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jinfen Wang
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, 100190, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yan Zhao
- State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, College of Mechanical and Vehicle Engineering, Hunan University, Changsha, 410082, China
| | - Hongbian Li
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, 100190, China
| | - Mengcheng Liu
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, 100190, China
| | - Jianfei Ding
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, 100190, China
| | - Huihui Tian
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, 100190, China
| | - Shouliang Guan
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, 100190, China
| | - Ying Fang
- CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, 100190, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
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45
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Yuan H, Li Y, Yang J, Li H, Yang Q, Guo C, Zhu S, Shu X. State of the Art of Non-Invasive Electrode Materials for Brain-Computer Interface. MICROMACHINES 2021; 12:1521. [PMID: 34945371 PMCID: PMC8705666 DOI: 10.3390/mi12121521] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 12/01/2021] [Accepted: 12/02/2021] [Indexed: 02/02/2023]
Abstract
The brain-computer interface (BCI) has emerged in recent years and has attracted great attention. As an indispensable part of the BCI signal acquisition system, brain electrodes have a great influence on the quality of the signal, which determines the final effect. Due to the special usage scenario of brain electrodes, some specific properties are required for them. In this study, we review the development of three major types of EEG electrodes from the perspective of material selection and structural design, including dry electrodes, wet electrodes, and semi-dry electrodes. Additionally, we provide a reference for the current chaotic performance evaluation of EEG electrodes in some aspects such as electrochemical performance, stability, and so on. Moreover, the challenges and future expectations for EEG electrodes are analyzed.
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Affiliation(s)
- Haowen Yuan
- State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China; (H.Y.); (J.Y.); (H.L.); (Q.Y.); (C.G.); (S.Z.)
| | - Yao Li
- State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China; (H.Y.); (J.Y.); (H.L.); (Q.Y.); (C.G.); (S.Z.)
| | - Junjun Yang
- State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China; (H.Y.); (J.Y.); (H.L.); (Q.Y.); (C.G.); (S.Z.)
| | - Hongjie Li
- State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China; (H.Y.); (J.Y.); (H.L.); (Q.Y.); (C.G.); (S.Z.)
| | - Qinya Yang
- State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China; (H.Y.); (J.Y.); (H.L.); (Q.Y.); (C.G.); (S.Z.)
| | - Cuiping Guo
- State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China; (H.Y.); (J.Y.); (H.L.); (Q.Y.); (C.G.); (S.Z.)
| | - Shenmin Zhu
- State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China; (H.Y.); (J.Y.); (H.L.); (Q.Y.); (C.G.); (S.Z.)
| | - Xiaokang Shu
- School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
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Garg R, Roman DS, Wang Y, Cohen-Karni D, Cohen-Karni T. Graphene nanostructures for input-output bioelectronics. BIOPHYSICS REVIEWS 2021; 2:041304. [PMID: 35005709 PMCID: PMC8717360 DOI: 10.1063/5.0073870] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 12/03/2021] [Indexed: 01/01/2023]
Abstract
The ability to manipulate the electrophysiology of electrically active cells and tissues has enabled a deeper understanding of healthy and diseased tissue states. This has primarily been achieved via input/output (I/O) bioelectronics that interface engineered materials with biological entities. Stable long-term application of conventional I/O bioelectronics advances as materials and processing techniques develop. Recent advancements have facilitated the development of graphene-based I/O bioelectronics with a wide variety of functional characteristics. Engineering the structural, physical, and chemical properties of graphene nanostructures and integration with modern microelectronics have enabled breakthrough high-density electrophysiological investigations. Here, we review recent advancements in 2D and 3D graphene-based I/O bioelectronics and highlight electrophysiological studies facilitated by these emerging platforms. Challenges and present potential breakthroughs that can be addressed via graphene bioelectronics are discussed. We emphasize the need for a multidisciplinary approach across materials science, micro-fabrication, and bioengineering to develop the next generation of I/O bioelectronics.
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Affiliation(s)
- Raghav Garg
- Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - Daniel San Roman
- Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - Yingqiao Wang
- Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - Devora Cohen-Karni
- Preclinical education biochemistry, Lake Erie College of Osteopathic Medicine at Seton Hill, Greensburg, Pennsylvania 15601, USA
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47
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Vomero M, Schiavone G. Biomedical Microtechnologies Beyond Scholarly Impact. MICROMACHINES 2021; 12:mi12121471. [PMID: 34945320 PMCID: PMC8709221 DOI: 10.3390/mi12121471] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 11/22/2021] [Accepted: 11/24/2021] [Indexed: 11/16/2022]
Abstract
The recent tremendous advances in medical technology at the level of academic research have set high expectations for the clinical outcomes they promise to deliver. To the demise of patient hopes, however, the more disruptive and invasive a new technology is, the bigger the gap is separating the conceptualization of a medical device and its adoption into healthcare systems. When technology breakthroughs are reported in the biomedical scientific literature, news focus typically lies on medical implications rather than engineering progress, as the former are of higher appeal to a general readership. While successful therapy and diagnostics are indeed the ultimate goals, it is of equal importance to expose the engineering thinking needed to achieve such results and, critically, identify the challenges that still lie ahead. Here, we would like to provoke thoughts on the following questions, with particular focus on microfabricated medical devices: should research advancing the maturity and reliability of medical technology benefit from higher accessibility and visibility? How can the scientific community encourage and reward academic work on the overshadowed engineering aspects that will facilitate the evolution of laboratory samples into clinical devices?
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Affiliation(s)
- Maria Vomero
- BioEE Laboratory, Electrical Engineering Department, Columbia University, New York, NY 10027, USA;
| | - Giuseppe Schiavone
- Research Management & Innovation Directorate, King’s College London, Tower Wing, Guy’s Hospital, London SE1 9RT, UK
- Correspondence:
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48
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Meikle SJ, Wong YT. Neurophysiological considerations for visual implants. Brain Struct Funct 2021; 227:1523-1543. [PMID: 34773502 DOI: 10.1007/s00429-021-02417-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 10/17/2021] [Indexed: 11/26/2022]
Abstract
Neural implants have the potential to restore visual capabilities in blind individuals by electrically stimulating the neurons of the visual system. This stimulation can produce visual percepts known as phosphenes. The ideal location of electrical stimulation for achieving vision restoration is widely debated and dependent on the physiological properties of the targeted tissue. Here, the neurophysiology of several potential target structures within the visual system will be explored regarding their benefits and downfalls in producing phosphenes. These regions will include the lateral geniculate nucleus, primary visual cortex, visual area 2, visual area 3, visual area 4 and the middle temporal area. Based on the existing engineering limitations of neural prostheses, we anticipate that electrical stimulation of any singular brain region will be incapable of achieving high-resolution naturalistic perception including color, texture, shape and motion. As improvements in visual acuity facilitate improvements in quality of life, emulating naturalistic vision should be one of the ultimate goals of visual prostheses. To achieve this goal, we propose that multiple brain areas will need to be targeted in unison enabling different aspects of vision to be recreated.
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Affiliation(s)
- Sabrina J Meikle
- Department of Electrical and Computer Systems Engineering, Monash University, 14 Alliance Lane, Clayton, Vic, 3800, Australia
- Department of Physiology and Biomedicine Discovery Institute, Monash University, 14 Alliance Lane, Clayton, Vic, 3800, Australia
- Monash Vision Group, Monash University, 14 Alliance Lane, Clayton, Vic, 3800, Australia
| | - Yan T Wong
- Department of Electrical and Computer Systems Engineering, Monash University, 14 Alliance Lane, Clayton, Vic, 3800, Australia.
- Department of Physiology and Biomedicine Discovery Institute, Monash University, 14 Alliance Lane, Clayton, Vic, 3800, Australia.
- Monash Vision Group, Monash University, 14 Alliance Lane, Clayton, Vic, 3800, Australia.
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Rapeaux AB, Constandinou TG. Implantable brain machine interfaces: first-in-human studies, technology challenges and trends. Curr Opin Biotechnol 2021; 72:102-111. [PMID: 34749248 DOI: 10.1016/j.copbio.2021.10.001] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 09/29/2021] [Accepted: 10/02/2021] [Indexed: 11/29/2022]
Abstract
Implantable brain machine interfaces (BMIs) are now on a trajectory to go mainstream, wherein what was once considered last resort will progressively become elective at earlier stages in disease treatment. First-in-human successes have demonstrated the ability to decode highly dexterous motor skills such as handwriting, and speech from human cortical activity. These have been used for cursor and prosthesis control, direct-to-text communication and speech synthesis. Along with these breakthrough studies, technology advancements have enabled the observation of more channels of neural activity through new concepts for centralised/distributed implant architectures. This is complemented by research in flexible substrates, packaging, surgical workflows and data processing. New regulatory guidance and funding has galvanised the field. This culmination of resource, efforts and capability is now attracting significant investment for BMI commercialisation. This paper reviews recent developments and describes the paradigm shift in BMI development that is leading to new innovations, insights and BMI translation.
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Affiliation(s)
- Adrien B Rapeaux
- Department of Electrical and Electronic Engineering, Imperial College London, UK; Centre for Bio-Inspired Technology, Imperial College London, UK; Care Research and Technology (CR&T) based at Imperial College London and the University of Surrey, UK Dementia Research Institute (UK DRI), UK
| | - Timothy G Constandinou
- Department of Electrical and Electronic Engineering, Imperial College London, UK; Centre for Bio-Inspired Technology, Imperial College London, UK; Care Research and Technology (CR&T) based at Imperial College London and the University of Surrey, UK Dementia Research Institute (UK DRI), UK.
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Park Y, Chung TS, Lee G, Rogers JA. Materials Chemistry of Neural Interface Technologies and Recent Advances in Three-Dimensional Systems. Chem Rev 2021; 122:5277-5316. [PMID: 34739219 DOI: 10.1021/acs.chemrev.1c00639] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Advances in materials chemistry and engineering serve as the basis for multifunctional neural interfaces that span length scales from individual neurons to neural networks, neural tissues, and complete neural systems. Such technologies exploit electrical, electrochemical, optical, and/or pharmacological modalities in sensing and neuromodulation for fundamental studies in neuroscience research, with additional potential to serve as routes for monitoring and treating neurodegenerative diseases and for rehabilitating patients. This review summarizes the essential role of chemistry in this field of research, with an emphasis on recently published results and developing trends. The focus is on enabling materials in diverse device constructs, including their latest utilization in 3D bioelectronic frameworks formed by 3D printing, self-folding, and mechanically guided assembly. A concluding section highlights key challenges and future directions.
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Affiliation(s)
- Yoonseok Park
- Querrey Simpson Institute for Bioelectronics, Northwestern University, Evanston, Illinois 60208, United States
| | - Ted S Chung
- Querrey Simpson Institute for Bioelectronics, Northwestern University, Evanston, Illinois 60208, United States.,Department of Biomedical Engineering, Northwestern University, Evanston, Illinois 60208, United States
| | - Geumbee Lee
- Querrey Simpson Institute for Bioelectronics, Northwestern University, Evanston, Illinois 60208, United States
| | - John A Rogers
- Querrey Simpson Institute for Bioelectronics, Northwestern University, Evanston, Illinois 60208, United States.,Department of Biomedical Engineering, Northwestern University, Evanston, Illinois 60208, United States.,Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois 60208, United States.,Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, Illinois 60208, United States.,Department of Chemistry, Northwestern University, Evanston, Illinois 60208, United States.,Department of Mechanical Engineering, Northwestern University, Evanston, Illinois 60208, United States.,Department of Neurological Surgery, Northwestern University, Evanston, Illinois 60208, United States
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