Evidence map›Paper›PMID 27385800›Full record

ArticleJournal of neurophysiology2016

Integration of autopatching with automated pipette and cell detection in vitro.

Qiuyu Wu 吴秋雨, Ilya Kolb, Brendan M Callahan, Zhaolun Su, William Stoy, Suhasa B Kodandaramaiah, Rachael Neve, Hongkui Zeng, Edward S Boyden, Craig R Forest and 1 more

Abstract readValidation Study
In one paragraph

Article in Journal of neurophysiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

27 citing papers in PubMed.

  1. Article
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  8. Multiscale, multi-perspective imaging assisted robotic microinjection of 3D biological structures.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2021
    Article
  9. Article
  10. Visual Familiarity Induced 5-Hz Oscillations and Improved Orientation and Direction Selectivities in V1.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021
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  14. Fabrication andJournal of electroanalytical chemistry (Lausanne, Switzerland) · 2020
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Qiuyu Wu 吴秋雨Department of Biological Sciences, Purdue University, West Lafayette, Indiana.
Ilya KolbWallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia.
Brendan M CallahanPicower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts.
Zhaolun SuDepartment of Biological Sciences, Purdue University, West Lafayette, Indiana.
William StoyWallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia.
Suhasa B KodandaramaiahMIT Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts; McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts; Department of Mechanical Engineering, University of Minnesota-Twin Cities, Minneapolis, Minnesota; and.
Rachael NeveMcGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts.
Hongkui ZengAllen Institute for Brain Science, Seattle, Washington.
Edward S BoydenMIT Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts; McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts.
Craig R ForestWallace 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.
Alexander A ChubykinDepartment of Biological Sciences, Purdue University, West Lafayette, Indiana; chubykin@purdue.edu.

Funding

High-throughput robotic analysis of integrated neuronal phenotypesR01EY023173 · NEI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BOYDEN, EDWARD S., FOREST, CRAIG · 2012 to 2016
$4.3M
Scalable Cell- and Circuit-Targeted ElectrophysiologyR01NS102727 · NINDS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BOYDEN, EDWARD S., FOREST, CRAIG · 2017 to 2020
$2.2M
In-vivo circuit activity measurement at single cell, sub-threshold resolutionU01MH106027 · NIMH · GEORGIA INSTITUTE OF TECHNOLOGY · PI FOREST, CRAIG, STANLEY, GARRETT B. · 2014 to 2016
$1.5M
NEI NIH HHS R01 EY023173NIMH NIH HHS U01 MH106027NINDS NIH HHS R01 NS102727
6 · The paper itself

Abstract

Patch clamp is the main technique for measuring electrical properties of individual cells. Since its discovery in 1976 by Neher and Sakmann, patch clamp has been instrumental in broadening our understanding of the fundamental properties of ion channels and synapses in neurons. The conventional patch-clamp method requires manual, precise positioning of a glass micropipette against the cell membrane of a visually identified target neuron. Subsequently, a tight "gigaseal" connection between the pipette and the cell membrane is established, and suction is applied to establish the whole cell patch configuration to perform electrophysiological recordings. This procedure is repeated manually for each individual cell, making it labor intensive and time consuming. In this article we describe the development of a new automatic patch-clamp system for brain slices, which integrates all steps of the patch-clamp process: image acquisition through a microscope, computer vision-based identification of a patch pipette and fluorescently labeled neurons, micromanipulator control, and automated patching. We validated our system in brain slices from wild-type and transgenic mice expressing channelrhodopsin 2 under the Thy1 promoter (line 18) or injected with a herpes simplex virus-expressing archaerhodopsin, ArchT. Our computer vision-based algorithm makes the fluorescent cell detection and targeting user independent. Compared with manual patching, our system is superior in both success rate and average trial duration. It provides more reliable trial-to-trial control of the patching process and improves reproducibility of experiments.

Indexed as

AlgorithmsAutomation, LaboratoryImage Processing, Computer-AssistedMicroscopy, FluorescenceAnimalsCalibrationComputer GraphicsFemaleFluorescent DyesImmunohistochemistryMaleMice, Inbred C57BLMice, TransgenicNeuronsPatch-Clamp TechniquesTime FactorsFluorescent Dyescomputer visionfluorescent cell detectionin vitro slice electrophysiologypatch-clamp

Identifiers

PMID27385800
PMCPMC5144721

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.