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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. Microsyst Nanoeng 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] [What about the content of this article? (0)] [Affiliation(s)] [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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