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Robotic Automation of In Vivo Two-Photon Targeted Whole-Cell Patch-Clamp Electrophysiology.
Neuron ( IF 16.2 ) Pub Date : 2017-Aug-30 , DOI: 10.1016/j.neuron.2017.08.018
Luca A Annecchino 1 , Alexander R Morris 1 , Caroline S Copeland 1 , Oshiorenoya E Agabi 1 , Paul Chadderton 1 , Simon R Schultz 1
Affiliation  

Whole-cell patch-clamp electrophysiological recording is a powerful technique for studying cellular function. While in vivo patch-clamp recording has recently benefited from automation, it is normally performed "blind," meaning that throughput for sampling some genetically or morphologically defined cell types is unacceptably low. One solution to this problem is to use two-photon microscopy to target fluorescently labeled neurons. Combining this with robotic automation is difficult, however, as micropipette penetration induces tissue deformation, moving target cells from their initial location. Here we describe a platform for automated two-photon targeted patch-clamp recording, which solves this problem by making use of a closed loop visual servo algorithm. Our system keeps the target cell in focus while iteratively adjusting the pipette approach trajectory to compensate for tissue motion. We demonstrate platform validation with patch-clamp recordings from a variety of cells in the mouse neocortex and cerebellum.

中文翻译:

体内双光子靶向全细胞膜片钳电生理学的机器人自动化。

全细胞膜片钳电生理记录是研究细胞功能的强大技术。虽然体内膜片钳记录最近受益于自动化,但它通常是“盲目地”执行的,这意味着对一些基因或形态学定义的细胞类型进行采样的吞吐量低得令人无法接受。这个问题的一种解决方案是使用双光子显微镜来靶向荧光标记的神经元。然而,将其与机器人自动化相结合是困难的,因为微量移液管穿透会导致组织变形,从而将靶细胞从其初始位置移动。在这里,我们描述了一个用于自动双光子靶向膜片钳记录的平台,它通过使用闭环视觉伺服算法解决了这个问题。我们的系统在迭代调整移液器接近轨迹以补偿组织运动的同时保持目标细胞处于焦点。我们使用来自小鼠新皮质和小脑中各种细胞的膜片钳记录来证明平台验证。
更新日期:2017-08-31
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