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Nat. Biomed. Eng., 08 November 2024 | https://doi.org/10.1038/s41551-024-01280-w A stealthy neural recorder for the study of behaviour in primates

Saehyuck Oh ^1,2,19, Janghwan Jekal ^1,2,19, Jinyoung Won ^3,19, Kyung Seob Lim ⁴, Chang-Yeop Jeon ³, Junghyung Park ³, Hyeon-Gu Yeo ^3,5, Yu Gyeong Kim ^3,5, Young Hee Lee ^6,7, Leslie Jaesun Ha ^6,7, Han Hee Jung ^1,2, Junwoo Yea^1,2, Hyeokjun Lee ^1,2, Jeongdae Ha ^1,2, Jinmo Kim ^2,8, Doyoung Lee ^2,8, Soojeong Song ^1,2, Jieun Son^1,2, Tae Sang Yu ^1,2, Jungmin Lee ⁹, Sanghoon Lee ¹, Jaehong Lee ¹, Bong Hoon Kim ¹, Ji-Woong Choi ^2,8, Jong-Cheol Rah^10,11, Young Min Song ¹², Jae-Woong Jeong ¹³, Hyung Jin Choi ^6,7, Sheng Xu ¹⁴, Youngjeon Lee ^3,5,* & Kyung-In Jang ^{1,2,8,10,11,15,16,17,18,*}

¹Department of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea.
²Brain Engineering Convergence Research Center, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea.
³National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Cheongju, Republic of Korea.
⁴Futuristic Animal Resource and Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Cheongju, Republic of Korea.
⁵KRIBB School of Bioscience, Korea National University of Science and Technology (UST), Daejeon, Republic of Korea.
⁶Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea.
⁷Wide River Institute of Immunology, Seoul National University College of Medicine, Seoul, Republic of Korea.
⁸Department of Electrical Engineering and Computer Science, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea.
⁹Hertie Institute for Clinical Brain Research, International Max Planck Research School and University of Tuebingen, Tuebingen, Germany.
¹⁰Department of Brain Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea.
¹¹Korea Brain Research Institute (KBRI), Daegu, Republic of Korea.
¹²School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea.
¹³School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
¹⁴Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA.
¹⁵Artificial Intelligence Major in Department of Interdisciplinary Studies, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea.
¹⁶Institute of Next-generation Semiconductor Convergence Technology, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea.
¹⁷Sensorium Institute, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea.
¹⁸ENSIDE Corporation, Daegu, Republic of Korea.
¹⁹These authors contributed equally: Saehyuck Oh, Janghwan Jekal, Jinyoung Won.

^*Corresponding authors: correspondence to Youngjeon Lee or Kyung-In Jang

Abstract

By monitoring brain neural signals, neural recorders allow for the study of neurological mechanisms underlying specific behavioural and cognitive states. However, the large brain volumes of non-human primates and their extensive range of uncontrolled movements and inherent wildness make it difficult to carry out covert and long-term recording and analysis of deep-brain neural signals. Here we report the development and performance of a stealthy neural recorder for the study of naturalistic behaviours in non-human primates. The neural recorder includes a fully implantable wireless and battery-free module for the recording of local field potentials and accelerometry data in real time, a flexible 32-electrode neural probe with a resorbable insertion shuttle, and a repeater coil-based wireless-power-transfer system operating at the body scale. We used the device to record neurobehavioural data for over 1 month in a freely moving monkey and leveraged the recorded data to train an artificial intelligence model for the classification of the animals’ eating behaviours.

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형식Research article
게재일2024년 11월 (BRIC 등록일 2024-11-15)
연구진국내(교신)+국외 연구진
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