Evidence map›Paper›PMID 37930888›Full record

ArticleCell reports2023

Layers of inhibitory networks shape receptive field properties of AII amacrine cells.

Amurta Nath, William N Grimes, Jeffrey S Diamond

Open access · goldAbstract read
In one paragraph

Article in Cell reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.1field-weighted citation impact, top 13% 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

6 citing papers in PubMed, 14 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Amurta NathSynaptic Physiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.
William N GrimesSynaptic Physiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.
Jeffrey S DiamondSynaptic Physiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA. Electronic address: diamondj@ninds.nih.gov.
National Institutes of Health · US

Funding

Circuit function and visual signal processing in the retinaZIANS003145 · NINDS · NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE · PI DIAMOND, JEFFREY S · 2014 to 2025
$16.7M
Intramural NIH HHS ZIA NS003145
6 · The paper itself

Abstract

In the retina, rod and cone pathways mediate visual signals over a billion-fold range in luminance. AII ("A-two") amacrine cells (ACs) receive signals from both pathways via different bipolar cells, enabling AIIs to operate at night and during the day. Previous work has examined luminance-dependent changes in AII gap junction connectivity, but less is known about how surrounding circuitry shapes AII receptive fields across light levels. Here, we report that moderate contrast stimuli elicit surround inhibition in AIIs under all but the dimmest visual conditions, due to actions of horizontal cells and at least two ACs that inhibit presynaptic bipolar cells. Under photopic (daylight) conditions, surround inhibition transforms AII response kinetics, which are inherited by downstream ganglion cells. Ablating neuronal nitric oxide synthase type-1 (nNOS-1) ACs removes AII surround inhibition under mesopic (dusk/dawn), but not photopic, conditions. Our findings demonstrate how multiple layers of neural circuitry interact to encode signals across a wide physiological range.

Indexed as

Amacrine CellsRetinaGap JunctionsRetinal Cone Photoreceptor CellsamacrineCP: Neurosciencegap junctioninhibitionmesopicnNOSphotopicreceptive fieldretinascotopic

Identifiers

PMID37930888
PMCPMC10769003
OpenAlexW4388381072

What OpenQuestion holds

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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.