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用于体内细胞内电生理学的机器人导航至皮质下神经组织

Robotic navigation to subcortical neural tissue for intracellular electrophysiology in vivo.

作者信息

Stoy W A, Kolb I, Holst G L, Liew Y, Pala A, Yang B, Boyden E S, Stanley G B, Forest C R

机构信息

Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia.

George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia.

出版信息

J Neurophysiol. 2017 Aug 1;118(2):1141-1150. doi: 10.1152/jn.00117.2017. Epub 2017 Jun 7.

Abstract

In vivo studies of neurophysiology using the whole cell patch-clamp technique enable exquisite access to both intracellular dynamics and cytosol of cells in the living brain but are underrepresented in deep subcortical nuclei because of fouling of the sensitive electrode tip. We have developed an autonomous method to navigate electrodes around obstacles such as blood vessels after identifying them as a source of contamination during regional pipette localization (RPL) in vivo. In mice, robotic navigation prevented fouling of the electrode tip, increasing RPL success probability 3 mm below the pial surface to 82% ( = 72/88) over traditional, linear localization (25%, = 24/95), and resulted in high-quality thalamic whole cell recordings with average access resistance (32.0 MΩ) and resting membrane potential (-62.9 mV) similar to cortical recordings in isoflurane-anesthetized mice. Whole cell yield improved from 1% ( = 1/95) to 10% ( = 9/88) when robotic navigation was used during RPL. This method opens the door to whole cell studies in deep subcortical nuclei, including multimodal cell typing and studies of long-range circuits. This work represents an automated method for accessing subcortical neural tissue for intracellular electrophysiology in vivo. We have implemented a novel algorithm to detect obstructions during regional pipette localization and move around them while minimizing lateral displacement within brain tissue. This approach leverages computer control of pressure, manipulator position, and impedance measurements to create a closed-loop platform for pipette navigation in vivo. This technique enables whole cell patching studies to be performed throughout the living brain.

摘要

使用全细胞膜片钳技术进行的神经生理学体内研究能够精确地获取活脑内细胞的细胞内动态和细胞质,但由于敏感电极尖端的污染,在深部皮层下核中的研究较少。我们开发了一种自主方法,在体内区域移液管定位(RPL)过程中将血管识别为污染源后,使电极能够绕过血管等障碍物。在小鼠中,机器人导航可防止电极尖端污染,将软脑膜表面以下3毫米处的RPL成功率从传统线性定位的25%(95次中有24次成功)提高到82%(88次中有72次成功),并获得了高质量的丘脑全细胞记录,其平均接入电阻(32.0 MΩ)和静息膜电位(-62.9 mV)与异氟烷麻醉小鼠的皮层记录相似。在RPL过程中使用机器人导航时,全细胞成功率从1%(95次中有1次成功)提高到了10%(88次中有9次成功)。这种方法为深部皮层下核的全细胞研究打开了大门,包括多模态细胞分型和长程回路研究。这项工作代表了一种在体内获取皮层下神经组织进行细胞内电生理学研究的自动化方法。我们实施了一种新颖的算法,用于在区域移液管定位过程中检测障碍物并绕过它们,同时将脑组织内的横向位移降至最低。这种方法利用压力、操纵器位置和阻抗测量的计算机控制,创建了一个用于体内移液管导航的闭环平台。这项技术使全细胞膜片钳研究能够在整个活脑中进行。

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