A Radial Modulus‐Gradient Fiber for Chronic Recording and Decoding in Deep Brain
Abstract
ABSTRACT Fiber electronics provide the most promising platform for the detection, modulation, and reconstruction of biosignals in the brain. However, preserving stable communication between fiber electronics and cellular‐scale targets in the deep brain is critical but challenging because of their mechanical mismatch. Here, our study fills this gap by developing a radial modulus‐gradient fiber (RMGF), which can bridge high‐modulus conductive components (MPa) and low‐modulus brain tissue (kPa) to well eliminate the mechanical mismatch at the entire neural‒device interface. The RMGF exhibits strain‐insensitive electrical properties (<0.2% resistance fluctuation over 700,000 stretching‒release cycles). As an example, the RMGF enables unprecedented five‐month continuous tracking of single neurons in the dorsal lateral geniculate nucleus of freely moving cats, and allows reconstruction of visual stimuli with the use of only three neurons, with a high correlation coefficient of 0.95, approaching the theoretical limit of the unscented Kalman filter (0.97). The results indicate that dorsal lateral geniculate nucleus neurons maintain stable tuning properties (spatial frequency sensitivity, ON/OFF characteristics, and X‐cell classification) and reveal a minimal effective ensemble for efficient encoding of information within deep thalamic circuits. This RMGF represents a platform for chronic recording at the single‐cell level and investigating fundamental mechanisms in the deep tissues.
Article Details
Authors (35)
Liyuan Wang
Chengqiang Tang
Zhengqi Han
School of Life Sciences, State Key Laboratory of Brain Function and Disorders Fudan University Shanghai China
Haixin Zhong
Research Institute of Intelligent Complex Systems, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science Institutes of Brain Science, Institute of Science and Technology for Brain‑Inspired Intelligence Artificial Intelligence Laboratory Fudan University Shanghai China
Kailin Zhang
Department of Chemistry, University of Basel, BPR 1096, Mattenstrasse 24a, Basel 4058, Switzerland
Ziyi Xie
Beijing National Laboratory for Molecular Science, Key Laboratory of Organic Solids, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, 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 China
Peng Zhai
The Institute of AI and Robotics Fudan University Shanghai China
Hongjian Li
Jiaheng Liang
School of Life Sciences, State Key Laboratory of Brain Function and Disorders Fudan University Shanghai China
Jiajia Wang
Jiawei Chen
State Key Laboratory of Advanced Materials for Intelligent Sensing and Key Laboratory of Organic Integrated Circuits, Ministry of Education & Tianjin Key Laboratory of Molecular Optoelectronic Sciences, Institute of Molecular Plus, Department of Chemistry
Yiqing Yang
Ziwei Liu
Mingyi Huang
Research Institute of Intelligent Complex Systems, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science Institutes of Brain Science, Institute of Science and Technology for Brain‑Inspired Intelligence Artificial Intelligence Laboratory Fudan University Shanghai China
Sihui Yu
Qingquan Han
Xiangran Cheng
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 China
Jinyan Li
Jiahao Shen
Xiaofei Wang
College of Chemistry and Molecular Sciences, Wuhan University, Wuhan 430072, China
Cheng Cao
Biqin Dong
Lihua Zhang
Center for Functional Nanomaterials
Qi Tong
National Key Laboratory of Veterinary Public Health and Safety, Key Laboratory for Prevention and Control of Avian Influenza and Other Major Poultry Diseases of the Ministry of Agriculture and Rural Affairs, College of Veterinary Medicine, China Agricultural University
Chen Zhao
Ya Huang
Bingjie Wang
Songlin Zhang
Peining Chen
Jue Deng
Yuguo Yu
Research Institute of Intelligent Complex Systems, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science Institutes of Brain Science, Institute of Science and Technology for Brain‑Inspired Intelligence Artificial Intelligence Laboratory Fudan University Shanghai China
Hongbo Yu
Department of Psychological and Brain Sciences, University of California Santa Barbara
Huisheng Peng
Xuemei Sun