Evidence map›Paper›PMID 32929073›Full record

ArticleNature communications2020

Ignoring correlated activity causes a failure of retinal population codes.

Kiersten Ruda, Joel Zylberberg, Greg D Field

Abstract read
In one paragraph

Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
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  11. Calibrating Bayesian Decoders of Neural Spiking Activity.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
    Article
  12. Review
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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.

Kiersten RudaDepartment of Neurobiology, Duke University School of Medicine, Durham, NC, USA.ORCID http://orcid.org/0000-0003-2744-6267
Joel ZylberbergDepartment of Physics and Center for Vision Research, York University, Toronto, Ontario, Canada.
Greg D FieldDepartment of Neurobiology, Duke University School of Medicine, Durham, NC, USA. field@neuro.duke.edu.ORCID http://orcid.org/0000-0001-5942-2679

Funding

Light adaptation and circadian modulation of parallel processing in retinaR01EY024567 · NEI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI FIELD, GREGORY DARIN · 2014 to 2018
$2.0M
The structure and significance of correlated activity among retinal ganglion cellsF31EY028833 · NEI · DUKE UNIVERSITY · PI RUDA, KIERSTEN · 2018 to 2019
$73k
NEI NIH HHS F31 EY028833NEI NIH HHS R01 EY024567
6 · The paper itself

Abstract

From starlight to sunlight, adaptation alters retinal output, changing both the signal and noise among populations of retinal ganglion cells (RGCs). Here we determine how these light level-dependent changes impact decoding of retinal output, testing the importance of accounting for RGC noise correlations to optimally read out retinal activity. We find that at moonlight conditions, correlated noise is greater and assuming independent noise severely diminishes decoding performance. In fact, assuming independence among a local population of RGCs produces worse decoding than using a single RGC, demonstrating a failure of population codes when correlated noise is substantial and ignored. We generalize these results with a simple model to determine what conditions dictate this failure of population processing. This work elucidates the circumstances in which accounting for noise correlations is necessary to take advantage of population-level codes and shows that sensory adaptation can strongly impact decoding requirements on downstream brain areas.

Indexed as

Adaptation, OcularAnimalsBayes TheoremLightLinear ModelsNight VisionPhotic StimulationRats, Long-EvansRetinaRetinal Ganglion Cells

Identifiers

PMID32929073
PMCPMC7490269

What OpenQuestion holds

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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.