English

Carbon-based Nanomaterials for Neural Electrode Technology

• Liu Yang ^1, ,
• Duan Xiaojie ^{1,2, ,}

• 1.

  Department of Biomedical Engineering, College of Engineering, Peking University, Beijing 100871, China

• 2.

  Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China

Corresponding author: Xiaojie Duan, Email: xjduan@pku.edu.cn; Tel.: +86-10-62745972

• Received Date: 25 July 2020
  Accepted Date: 23 August 2020
  Revised Date: 21 August 2020
  Available Online: 15 December 2020
• Fund Project:

  The project was supported by the National Natural Science Foundation of China (21972005, 91648207, 81771821), the National Key Basic Research Program of China (2016YFA0200103), and the Beijing Graphene Innovation Program (Z191100000819001)

Abstract: As a powerful tool for monitoring and modulating neural activities, implantable neural electrodes constitute the basis for a wide range of applications, including fundamental studies of brain circuits and functions, treatment of various neurological diseases, and realization of brain-machine interfaces. However, conventional neural electrodes have the issue of mechanical mismatch with soft neural tissues, which can result in tissue inflammation and gliosis, thus causing degradation of function over chronic implantation. Furthermore, implantable neural electrodes, especially depth electrodes, can only carry out limited data sampling within predefined anatomical regions, making it challenging to perform large-area brain mapping. With excellent electrical, mechanical, and chemical properties, carbon-based nanomaterials, including graphene and carbon nanotubes (CNTs), have been used as materials of implantable neural electrodes in recent years. Electrodes made from graphene and CNT fibers exhibit low electrochemical impedance, benefiting from the porous microstructure of the fibers. This enables a much smaller size of neural electrode. Together with the low Young's modulus of the fibers, this small size results in very soft electrodes. Soft neural electrodes made from graphene and CNT fibers show a much-reduced inflammatory response and enable stable chronic in vivo action potential recording for 4-5 months. Combining different modalities of neural interfacing, including electrophysiological measurement, optical imaging/stimulation, and magnetic resonance imaging (MRI), could leverage the spatial and temporal resolution advantages of different techniques, thus providing new insights into how neural circuits process information. Transparent neural electrode arrays made from graphene or CNTs enable simultaneous calcium imaging through the transparent electrodes, from which concurrent electrical recording is taken, thus providing complementary cellular information in addition to high-temporal-resolution electrical recording. Transparent neural electrodes from carbon-based nanomaterials can record well-defined neuronal response signals with negligible light-induced artifacts from cortical surfaces under optogenetic stimulation. Graphene and CNT-based materials were used to fabricate MRI-compatible neural electrodes with negligible artifacts under high field MRI. Simultaneous deep brain stimulation (DBS) and functional magnetic resonance imaging (fMRI) with graphene fiber electrodes in the subthalamic nucleus (STN) in Parkinsonian rats revealed robust blood oxygenation level dependent responses along the basal ganglia-thalamocortical network in a frequency-dependent manner, with responses from some regions not previously detectable. This review introduces the recent development and application of neural electrode technologies based on graphene and CNTs. We also discuss biological safety issues and challenges faced by neural electrodes made from carbon nanomaterials. The use of carbon-based nanomaterials for the fabrication of various soft and multi-modality compatible neural electrodes will provide a powerful platform for both fundamental and translational neuroscience research.

Key words:
• Neural interfacing
•  /  Graphene
•  /  Carbon nanotube
•  /  Flexible electronics
•  /  Multimodal neural interface
•  /  Microelectrode probe
•  /  Brain activity mapping
•  /  Neuromodulation

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