从电生理到生化调制接口:脑机通信的进化。

IF 9.1 2区 材料科学 Q1 CHEMISTRY, PHYSICAL
Wenhao Li, Haochen Zou, Bowen Yang, Lanxin Xiao, Songrui Liu, Zan Chen, Lei Xie, Wentao Zhu, Xiao Zhao, Lianhui Wang, Ting Li, Ting Wang
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引用次数: 0

摘要

脑机接口(bmi)通过解码神经信号并提供反馈刺激,在生物神经系统和外部设备之间建立双向通信。通过三个相互关联的维度,实现与生物系统的无缝集成推动了BMI技术的范式进化。这篇综述总结了从电生理到生化调节bmi的转变,强调了反映生物神经特征的关键进化趋势。首先,信号模式已经从单一的电生理检测扩展到集成的生化传感,通过捕获快速电传输和较慢生化过程的双重电化学通信途径,实现全面的神经回路分析。其次,电极形态已经从刚性硅结构转变为灵活的自适应材料,可以在机械上匹配神经组织特性,减少机械不匹配并提高长期生物相容性。第三,系统架构已经从被动监测发展到主动闭环平台,结合了神经形态智能和实时治疗反馈,实现了基于多模态信号分析的动态神经调节。尽管取得了重大进展,但在实现高电极寿命,开发可扩展的多模态接口以及理解基本的神经通信机制方面仍然存在挑战。未来的方向指向生化调节的脑接口,包括活的、自适应的和进化反应的组件,与精确的神经治疗的生物神经网络无缝集成。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
From Electrophysiological to Biochemically-Modulated Interfaces: Evolution of Brain-Machine Communication.

Brain-machine interfaces (BMIs) establish bidirectional communication between biological neural systems and external devices by decoding neural signals and delivering feedback stimulation. Achieving seamless integration with biological systems has driven the paradigmatic evolution of BMI technology through three interconnected dimensions. This review summarizes the shift from electrophysiological to biochemically-modulated BMIs, emphasizing key evolutionary trends that mirror biological neural characteristics. First, signal modalities have expanded from single electrophysiological detection to integrated biochemical sensing, enabling comprehensive neural circuit analysis through dual electrical-chemical communication pathways that capture both rapid electrical transmission and slower biochemical processes. Second, electrode morphology has transformed from rigid silicon structures to flexible, adaptive materials that mechanically match neural tissue properties, reducing mechanical mismatch and improving long-term biocompatibility. Third, system architectures have evolved from passive monitoring to active closed-loop platforms that incorporate neuromorphic intelligence and real-time therapeutic feedback, enabling dynamic neuromodulation based on multimodal signal analysis. Despite significant progress, challenges remain in achieving high electrode longevity, developing scalable multimodal interfaces, as well as understanding fundamental neural communication mechanisms. Future directions point toward biochemically-modulated brain interfaces incorporating living, adaptive, and evolutionarily responsive components that seamlessly integrate with biological neural networks for precision neurological therapeutics.

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来源期刊
Small Methods
Small Methods Materials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍: Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques. With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community. The online ISSN for Small Methods is 2366-9608.
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