Neuron
Volume 95, Issue 5, 30 August 2017, Pages 1037-1047.e11
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Closed-Loop Real-Time Imaging Enables Fully Automated Cell-Targeted Patch-Clamp Neural Recording In Vivo

https://doi.org/10.1016/j.neuron.2017.08.011Get rights and content
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Highlights

  • Imagepatching enables fully automated cell-targeted patch-clamp recording in vivo

  • Closed-loop real-time imaging accounts for target cell movements during patching

  • Successful whole-cell recordings are obtained from targeted neurons in vivo

Summary

Targeted patch-clamp recording is a powerful method for characterizing visually identified cells in intact neural circuits, but it requires skill to perform. We previously developed an algorithm that automates “blind” patching in vivo, but full automation of visually guided, targeted in vivo patching has not been demonstrated, with currently available approaches requiring human intervention to compensate for cell movement as a patch pipette approaches a targeted neuron. Here we present a closed-loop real-time imaging strategy that automatically compensates for cell movement by tracking cell position and adjusting pipette motion while approaching a target. We demonstrate our system’s ability to adaptively patch, under continuous two-photon imaging and real-time analysis, fluorophore-expressing neurons of multiple types in the living mouse cortex, without human intervention, with yields comparable to skilled human experimenters. Our “imagepatching” robot is easy to implement and will help enable scalable characterization of identified cell types in intact neural circuits.

Keywords

patch clamp
in vivo electrophysiology
fluorescent proteins
fluorescent object detection
automation
cell types
mouse
cortex
imaging
two-photon microscopy

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