2015
DOI: 10.1152/jn.00025.2015
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MATLAB-based automated patch-clamp system for awake behaving mice

Abstract: Automation has been an important part of biomedical research for decades, and the use of automated and robotic systems is now standard for such tasks as DNA sequencing, microfluidics, and high-throughput screening. Recently, Kodandaramaiah and colleagues (Nat Methods 9: 585-587, 2012) demonstrated, using anesthetized animals, the feasibility of automating blind patch-clamp recordings in vivo. Blind patch is a good target for automation because it is a complex yet highly stereotyped process that revolves around… Show more

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Cited by 35 publications
(36 citation statements)
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“…The depth of detection events was distributed between 500 and 1,000 μm (Supplementary Fig. 2B), consistent with what is known for blind patching161724. As in the case shown in Fig.…”
Section: Resultssupporting
confidence: 87%
“…The depth of detection events was distributed between 500 and 1,000 μm (Supplementary Fig. 2B), consistent with what is known for blind patching161724. As in the case shown in Fig.…”
Section: Resultssupporting
confidence: 87%
“…In conclusion, we demonstrated that the combination of robotic automation, real-time image acquisition and analysis leads to a significant increase in the efficiency of a difficult laboratory technique, such as microinjection into single cells in tissue. Robotic systems have enabled the automation of difficult laboratory techniques that require precise micromanipulation such as in vivo patch clamping of single [50][51][52] as well as multiple neurons in vivo 53 . Additionally, previous work relied on camera images to guide automated patch clamping systems to specific locations in tissue 11,54 .…”
Section: Discussionmentioning
confidence: 99%
“…Several approaches have been reported recently to address some of the limitations of manual operations in the conventional intracellular recording system. Recently, automated systems have been developed to reduce the "art" in the process of intracellular recording in vivo [10][11][12] . Kodandaramaiah and colleagues 10 developed a closedloop control system that used a temporal sequence of electrode impedance changes as a feedback signal to automate movement of electrode and whole-cell patching of neurons in the cortex and hippocampus of anesthetized, head-fixed mice. They recently improved the algorithm to automate localization of a pipette to deep cortical nuclei through autonomous detection and lateral navigation around blood vessels and obtained high-yield (10%) thalamic whole-cell recordings 13 .…”
Section: Introductionmentioning
confidence: 99%
“…They recently improved the algorithm to automate localization of a pipette to deep cortical nuclei through autonomous detection and lateral navigation around blood vessels and obtained high-yield (10%) thalamic whole-cell recordings 13 . Desai et al 12 and Ota et al 11 developed similar algorithms to automate cortical whole-cell patching in awake, head-fixed, behaving mice and sharp micropipette recording in anesthetized, headfixed mice, respectively.…”
Section: Introductionmentioning
confidence: 99%