Evidence map›Paper›PMID 33759001›Full record

ArticleJournal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology2021

Automated methods for efficient and accurate electroretinography.

Luke T Havens, Alexandra C N Kingston, Daniel I Speiser

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Article in Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Luke T HavensDepartment of Biology, The University of North Carolina at Chapel Hill, 120 South Road, Chapel Hill, NC, 27599, USA. lukethavens@gmail.com.ORCID 0000-0002-4754-2101
Alexandra C N KingstonDepartment of Biological Science, The University of Tulsa, 800 South Tucker Drive, Tulsa, OK, 74104, USA.ORCID 0000-0002-1982-8831
Daniel I SpeiserDepartment of Biological Sciences, University of South Carolina, 715 Sumter Street, Columbia, SC, 29208, USA.ORCID 0000-0001-6662-3583

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electroretinography (ERG) is a foundational method for assessing visual system physiology, but accurate ERG can be time- and labor-intensive, often involving manual adjustment of the wavelength and intensity of light stimuli and real-time comparison of physiological responses to inform those adjustments. Furthermore, current approaches to ERG often require expertise beyond that necessary for the electrophysiological preparation itself. To improve both the efficiency and accessibility of ERG, we designed an automated system for stimulus presentation and data acquisition. Here, we test this novel system's ability to accurately assess spectral sensitivity in the well-characterized visual system of the crayfish Procambarus clarkii using three approaches: the first, based on response magnitude, maximizes efficiency; the second is a well-established method we use to further validate our efficient approach's accuracy. Third, we explore the potential benefits of extensible automation using a method assessing the interplay between temporal acuity and spectral sensitivity. Using our system, we are able to acquire accurate results in ERG experiments quickly (testing the entire visible spectrum in 8 min, 30 s using our response magnitude approach). Moreover, data collected via all three methods yielded results consistent with each other and previous work on P. clarkii.

Indexed as

ElectroretinographySignal Processing, Computer-AssistedVision, OcularVisual PerceptionAnimalsAstacoideaAutomation, LaboratoryEvoked PotentialsPhotic StimulationReproducibility of ResultsRetinaTime FactorsAutomationCrayfishERGSpectral sensitivityVisual ecology

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Registered trials

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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.