Oh Saehyuck, Jekal Janghwan, Won Jinyoung, Lim Kyung Seob, Jeon Chang-Yeop, Park Junghyung, Yeo Hyeon-Gu, Kim Yu Gyeong, Lee Young Hee, Ha Leslie Jaesun, Jung Han Hee, Yea Junwoo, Lee Hyeokjun, Ha Jeongdae, Kim Jinmo, Lee Doyoung, Song Soojeong, Son Jieun, Yu Tae Sang, Lee Jungmin, Lee Sanghoon, Lee Jaehong, Kim Bong Hoon, Choi Ji-Woong, Rah Jong-Cheol, Song Young Min, Jeong Jae-Woong, Choi Hyung Jin, Xu Sheng, Lee Youngjeon, Jang Kyung-In
Department of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea.
Brain Engineering Convergence Research Center, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea.
Nat Biomed Eng. 2024 Nov 8. doi: 10.1038/s41551-024-01280-w.
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.
通过监测大脑神经信号,神经记录器有助于研究特定行为和认知状态背后的神经机制。然而,非人类灵长类动物大脑体积大,其不受控制的运动范围广且具有天生的野性,这使得对深部脑区神经信号进行隐蔽且长期的记录和分析变得困难。在此,我们报告了一种用于研究非人类灵长类动物自然行为的隐形神经记录器的开发及其性能。该神经记录器包括一个用于实时记录局部场电位和加速度计数据的完全可植入的无线且无电池模块、一个带有可吸收插入穿梭器的柔性32电极神经探针,以及一个在身体尺度上运行的基于中继线圈的无线电力传输系统。我们使用该设备在一只自由活动的猴子身上记录了超过1个月的神经行为数据,并利用所记录的数据训练了一个用于分类动物进食行为的人工智能模型。