Evidence map›Paper›PMID 28858615›Full record

ArticleNeuron2017

Robotic Automation of In Vivo Two-Photon Targeted Whole-Cell Patch-Clamp Electrophysiology.

Luca A Annecchino, Alexander R Morris, Caroline S Copeland, Oshiorenoya E Agabi, Paul Chadderton, Simon R Schultz

Open access · hybridAbstract read
In one paragraph

Article in Neuron, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
2.5field-weighted citation impact, top 11% of its field
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

32 citing papers in PubMed, 69 citations in OpenAlex.

  1. Article
  2. Review
  3. Editorial: The diversity of the plasticitome.Frontiers in synaptic neuroscience · 2026
    Article
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  5. Article
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  7. Review
  8. Article
  9. Review
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  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Harnessing non-destructive 3D pathology.Nature biomedical engineering · 2021
    Review
  17. Review
  18. Article
  19. Grand Challenge at the Frontiers of Synaptic Neuroscience.Frontiers in synaptic neuroscience · 2021
    Article
  20. TbScience advances · 2021
    Article
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

6 authors at 1 institution in 1 country.

Luca A AnnecchinoDepartment of Bioengineering and Centre for Neurotechnology, Imperial College London, London SW7 2AZ, UK.
Alexander R MorrisDepartment of Bioengineering and Centre for Neurotechnology, Imperial College London, London SW7 2AZ, UK.
Caroline S CopelandDepartment of Bioengineering and Centre for Neurotechnology, Imperial College London, London SW7 2AZ, UK.
Oshiorenoya E AgabiDepartment of Bioengineering and Centre for Neurotechnology, Imperial College London, London SW7 2AZ, UK.
Paul ChaddertonDepartment of Bioengineering and Centre for Neurotechnology, Imperial College London, London SW7 2AZ, UK.
Simon R SchultzDepartment of Bioengineering and Centre for Neurotechnology, Imperial College London, London SW7 2AZ, UK. Electronic address: s.schultz@imperial.ac.uk.
Imperial College London · GB

Funding

Medical Research Council G1000512Wellcome Trust
6 · The paper itself

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.

Indexed as

AnimalsAutomationCerebellumMiceNeocortexNeuronsPatch-Clamp TechniquesPhotonsRoboticsautomated neurophysiologymultiphoton microscopypatch clamprobotic automation

Identifiers

PMID28858615
PMCPMC5584670
OpenAlexW2751742913

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.