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神经技术的最新进展具有广泛的神经科学研究潜力。

Recent advances in neurotechnologies with broad potential for neuroscience research.

机构信息

Center for Bio-Integrated Electronics, Northwestern University, Evanston, IL, USA.

Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA.

出版信息

Nat Neurosci. 2020 Dec;23(12):1522-1536. doi: 10.1038/s41593-020-00739-8. Epub 2020 Nov 16.

Abstract

Interest in deciphering the fundamental mechanisms and processes of the human mind represents a central driving force in modern neuroscience research. Activities in support of this goal rely on advanced methodologies and engineering systems that are capable of interrogating and stimulating neural pathways, from single cells in small networks to interconnections that span the entire brain. Recent research establishes the foundations for a broad range of creative neurotechnologies that enable unique modes of operation in this context. This review focuses on those systems with proven utility in animal model studies and with levels of technical maturity that suggest a potential for broad deployment to the neuroscience community in the relatively near future. We include a brief summary of existing and emerging neuroscience techniques, as background for a primary focus on device technologies that address associated opportunities in electrical, optical and microfluidic neural interfaces, some with multimodal capabilities. Examples of the use of these technologies in recent neuroscience studies illustrate their practical value. The vibrancy of the engineering science associated with these platforms, the interdisciplinary nature of this field of research and its relevance to grand challenges in the treatment of neurological disorders motivate continued growth of this area of study.

摘要

对人类思维的基本机制和过程进行解码的兴趣是现代神经科学研究的核心驱动力。为了实现这一目标而开展的各项活动依赖于先进的方法和工程系统,这些系统能够对从单个小网络中的细胞到跨越整个大脑的连接进行探测和刺激。最近的研究为广泛的创造性神经技术奠定了基础,这些技术在这方面能够实现独特的操作模式。本综述重点介绍了那些在动物模型研究中已经证明具有实际应用价值、并且在技术成熟度方面具有广泛应用于神经科学界的潜力的系统。我们简要总结了现有的和新兴的神经科学技术,作为重点介绍解决电、光和微流控神经接口相关机会的设备技术的背景,其中一些技术具有多模态能力。这些技术在最近的神经科学研究中的应用实例说明了它们的实际价值。与这些平台相关的工程科学的活力、该研究领域的跨学科性质以及它在治疗神经障碍方面的重大挑战的相关性,激发了该研究领域的持续增长。

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