Flexible, ultrathin bioelectronic materials and devices for chronically stable neural interfaces

计算机科学 接口(物质) 纳米技术 生物电子学 神经科学 材料科学 生物传感器 生物 气泡 最大气泡压力法 并行计算
作者
Lianjie Zhou,Zhongyuan Wu,Mubai Sun,Jaejin Park,Mengdi Han,Ming Wang,Junsheng Yu,Zengfeng Di,Yongfeng Mei,Wubin Bai,Xinge Yu,Ki Jun Yu,Enming Song
标识
DOI:10.1002/brx2.47
摘要

Abstract Advanced technologies that can establish intimate, long‐lived functional interfaces with neural systems have attracted increasing interest due to their wide‐ranging applications in neuroscience, bioelectronic medicine, and the associated treatment of neurodegenerative diseases. A critical challenge of significance remains in the development of electronic platforms that offer conformal contact with soft brain tissue for the sensing or stimulation of brain activities and chronically stable operation in vivo, at scales that range from cellular‐level resolution to macroscopic areas. This review summarizes recent advances in this field, with an emphasis on the use of demonstrated concepts, constituent materials, engineered designs, and system integration to address the current challenges. The article begins with an overview of recent bioelectronic platforms with unique form factors, ranging from filamentary probes to conformal sheets and three‐dimensional frameworks for alleviating the mechanical mismatch between interface materials and neural tissues. Next, active interfaces which utilize inorganic/organic semiconductor‐enabled devices are reviewed, highlighting various working principles of recording mechanisms including capacitively and conductively coupled sensing enabled by high transistor matrices at high spatiotemporal resolution. The subsequent section presents approaches to biological integration which use active materials for multiplexed addressing, local amplification and multimodal operation with high‐channel‐count and large‐scale electronic systems in a safe fashion that provides multi‐decade stable performance in both animal models and human subjects. The advances summarized in this review will guide the future direction of this technology and provide a basis for next‐generation chronic neural interfaces with long‐lived high‐performance operation.

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