Robotic automation of in vivo two photon targeted whole-cell patch clamp electrophysiology

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Title: Robotic automation of in vivo two photon targeted whole-cell patch clamp electrophysiology
Authors: Annecchino, LA
Morris, AR
Copeland, CS
Agabi, OE
Chadderton, P
Schultz, SR
Item Type: Journal Article
Abstract: 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.
Issue Date: 30-Aug-2017
Date of Acceptance: 12-Aug-2017
ISSN: 0896-6273
Publisher: Elsevier
Start Page: 1048
End Page: 1055.e3
Journal / Book Title: Neuron
Volume: 95
Issue: 5
Copyright Statement: © 2017 The Authors. This is an open access article under the CC BY license (
Sponsor/Funder: Biotechnology and Biological Sciences Research Council (BBSRC)
Scientifica Ltd
Commission of the European Communities
Funder's Grant Number: BB/K001817/1
Keywords: automated neurophysiology
multiphoton microscopy
patch clamp
robotic automation
1109 Neurosciences
1702 Cognitive Science
Neurology & Neurosurgery
Publication Status: Published
Appears in Collections:Faculty of Engineering
Dyson School of Design Engineering

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