Evidence map›Paper›PMID 30969898›Full record

ArticleJournal of neurophysiology2019

Autonomous patch-clamp robot for functional characterization of neurons in vivo: development and application to mouse visual cortex.

Gregory L Holst, William Stoy, Bo Yang, Ilya Kolb, Suhasa B Kodandaramaiah, Lu Li, Ulf Knoblich, Hongkui Zeng, Bilal Haider, Edward S Boyden and 1 more

Abstract read
In one paragraph

Article in Journal of neurophysiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

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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.

Gregory L HolstGeorge W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology , Atlanta, Georgia.ORCID 0000-0003-2361-7938
William StoyWallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology , Atlanta, Georgia.ORCID 0000-0001-9425-0809
Bo YangGeorge W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology , Atlanta, Georgia.
Ilya KolbWallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology , Atlanta, Georgia.
Suhasa B KodandaramaiahDepartment of Mechanical Engineering, University of Minnesota , Minneapolis, Minnesota.
Lu LiAllen Institute for Brain Science , Seattle, Washington.
Ulf KnoblichAllen Institute for Brain Science , Seattle, Washington.
Hongkui ZengAllen Institute for Brain Science , Seattle, Washington.
Bilal HaiderWallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology , Atlanta, Georgia.
Edward S BoydenMedia Arts and Sciences, Massachusetts Institute of Technology , Cambridge, Massachusetts.
Craig R ForestGeorge W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology , Atlanta, Georgia.

Funding

Generation of novel cell type specific mouse genetic toolsU19MH114830 · NIMH · ALLEN INSTITUTE · PI ZENG, HONGKUI · 2017 to 2021
$64.7M
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
NEI NIH HHS R01 EY023173NIMH NIH HHS U19 MH114830NINDS NIH HHS R01 NS102727
6 · The paper itself

Abstract

Patch clamping is the gold standard measurement technique for cell-type characterization in vivo, but it has low throughput, is difficult to scale, and requires highly skilled operation. We developed an autonomous robot that can acquire multiple consecutive patch-clamp recordings in vivo. In practice, 40 pipettes loaded into a carousel are sequentially filled and inserted into the brain, localized to a cell, used for patch clamping, and disposed. Automated visual stimulation and electrophysiology software enables functional cell-type classification of whole cell-patched cells, as we show for 37 cells in the anesthetized mouse in visual cortex (V1) layer 5. We achieved 9% yield, with 5.3 min per attempt over hundreds of trials. The highly variable and low-yield nature of in vivo patch-clamp recordings will benefit from such a standardized, automated, quantitative approach, allowing development of optimal algorithms and enabling scaling required for large-scale studies and integration with complementary techniques.

Indexed as

RoboticsAnimalsElectrophysiological PhenomenaMaleMiceMice, Inbred C57BLNeuronsPatch-Clamp TechniquesPhotic StimulationVisual Cortexautomatedin vivolayer 5patch clamproboticvisual cortex

Identifiers

PMID30969898
PMCPMC6620702

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.