Evidence map›Paper›PMID 35169018›Full record

ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2022

Prior Expectations in Visual Speed Perception Predict Encoding Characteristics of Neurons in Area MT.

Ling-Qi Zhang, Alan A Stocker

Erratum issuedAbstract read
In one paragraph

Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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  9. The tilt illusion arises from an efficient reallocation of neural coding resources at the contextual boundary.Proceedings of the National Academy of Sciences of the United States of America · 2025
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  10. Article
  11. Article
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  13. A unified framework for perceived magnitude and discriminability of sensory stimuli.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  14. Article
  15. Neural encoding of multiple motion speeds in visual cortical area MT.bioRxiv : the preprint server for biology · 2023
    Article
  16. Causal inference during closed-loop navigation: parsing of self- and object-motion.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
    Article
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  18. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Ling-Qi Zhang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bayesian inference provides an elegant theoretical framework for understanding the characteristic biases and discrimination thresholds in visual speed perception. However, the framework is difficult to validate because of its flexibility and the fact that suitable constraints on the structure of the sensory uncertainty have been missing. Here, we demonstrate that a Bayesian observer model constrained by efficient coding not only well explains human visual speed perception but also provides an accurate quantitative account of the tuning characteristics of neurons known for representing visual speed. Specifically, we found that the population coding accuracy for visual speed in area MT ("neural prior") is precisely predicted by the power-law, slow-speed prior extracted from fitting the Bayesian observer model to psychophysical data ("behavioral prior") to the point that the two priors are indistinguishable in a cross-validation model comparison. Our results demonstrate a quantitative validation of the Bayesian observer model constrained by efficient coding at both the behavioral and neural levels.

Indexed as

Motion PerceptionBayes TheoremHumansMotivationNeuronsVisual PerceptionBayesian modelefficient codingneural representationspeed priorWeber's law

Identifiers

PMID35169018
PMCPMC8985856

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.