Evidence map›Paper›PMID 34780469›Full record

ArticlePLoS computational biology2021

Causal inference regulates audiovisual spatial recalibration via its influence on audiovisual perception.

Fangfang Hong, Stephanie Badde, Michael S Landy

Abstract read
In one paragraph

Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
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  3. Article
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  10. Multisensory causal inference is feature-specific, not object-based.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
    Article
  11. Article
  12. Article
  13. Crossmodal interactions in human learning and memory.Frontiers in human neuroscience · 2023
    Review
  14. Article
  15. Article
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.

Fangfang HongDepartment of Psychology, New York University, New York City, New York, United States of America.ORCID 0000-0003-1890-1977
Stephanie BaddeDepartment of Psychology, Tufts University, Medford, Massachusetts, United States of America.ORCID 0000-0002-4005-5503
Michael S LandyDepartment of Psychology, New York University, New York City, New York, United States of America.ORCID 0000-0002-2079-4552

Funding

SHAPE REPRESENTATION AND MULTIPLE DEPTH CUESR01EY008266 · NEI · NEW YORK UNIVERSITY · PI MICHAEL S LANDY · 1989 to 2026
$7.7M
NEI NIH HHS R01 EY008266
6 · The paper itself

Abstract

To obtain a coherent perception of the world, our senses need to be in alignment. When we encounter misaligned cues from two sensory modalities, the brain must infer which cue is faulty and recalibrate the corresponding sense. We examined whether and how the brain uses cue reliability to identify the miscalibrated sense by measuring the audiovisual ventriloquism aftereffect for stimuli of varying visual reliability. To adjust for modality-specific biases, visual stimulus locations were chosen based on perceived alignment with auditory stimulus locations for each participant. During an audiovisual recalibration phase, participants were presented with bimodal stimuli with a fixed perceptual spatial discrepancy; they localized one modality, cued after stimulus presentation. Unimodal auditory and visual localization was measured before and after the audiovisual recalibration phase. We compared participants' behavior to the predictions of three models of recalibration: (a) Reliability-based: each modality is recalibrated based on its relative reliability-less reliable cues are recalibrated more; (b) Fixed-ratio: the degree of recalibration for each modality is fixed; (c) Causal-inference: recalibration is directly determined by the discrepancy between a cue and its estimate, which in turn depends on the reliability of both cues, and inference about how likely the two cues derive from a common source. Vision was hardly recalibrated by audition. Auditory recalibration by vision changed idiosyncratically as visual reliability decreased: the extent of auditory recalibration either decreased monotonically, peaked at medium visual reliability, or increased monotonically. The latter two patterns cannot be explained by either the reliability-based or fixed-ratio models. Only the causal-inference model of recalibration captures the idiosyncratic influences of cue reliability on recalibration. We conclude that cue reliability, causal inference, and modality-specific biases guide cross-modal recalibration indirectly by determining the perception of audiovisual stimuli.

Indexed as

Acoustic StimulationAdultAttentional BiasAuditory PerceptionBrainCausalityComputational BiologyCuesFemaleHumansMaleModels, NeurologicalModels, PsychologicalPhotic StimulationReproducibility of ResultsSound Localization

Identifiers

PMID34780469
PMCPMC8629398

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.