Evidence map›Paper›PMID 39996594›Full record

ArticleeLife2025

Precision-based causal inference modulates audiovisual temporal recalibration.

Luhe Li, Fangfang Hong, Stephanie Badde, Michael S Landy

Abstract read
In one paragraph

Article in eLife, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Luhe LiDepartment of Psychology, New York University, New York, United States.ORCID https://orcid.org/0000-0002-0182-3952
Fangfang HongDepartment of Psychology, University of Pennsylvania, Philadelphia, United States.ORCID https://orcid.org/0000-0003-1890-1977
Stephanie BaddeDepartment of Psychology, Tufts University, Medford, United States.ORCID https://orcid.org/0000-0002-4005-5503
Michael S LandyDepartment of Psychology, New York University, New York, United States.ORCID https://orcid.org/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 EY008266NIH HHS EY08266
6 · The paper itself

Abstract

Cross-modal temporal recalibration guarantees stable temporal perception across ever-changing environments. Yet, the mechanisms of cross-modal temporal recalibration remain unknown. Here, we conducted an experiment to measure how participants' temporal perception was affected by exposure to audiovisual stimuli with constant temporal delays that we varied across sessions. Consistent with previous findings, recalibration effects plateaued with increasing audiovisual asynchrony (nonlinearity) and varied by which modality led during the exposure phase (asymmetry). We compared six observer models that differed in how they update the audiovisual temporal bias during the exposure phase and in whether they assume a modality-specific or modality-independent precision of arrival latency. The causal-inference observer shifts the audiovisual temporal bias to compensate for perceived asynchrony, which is inferred by considering two causal scenarios: when the audiovisual stimuli have a common cause or separate causes. The asynchrony-contingent observer updates the bias to achieve simultaneity of auditory and visual measurements, modulating the update rate by the likelihood of the audiovisual stimuli originating from a simultaneous event. In the asynchrony-correction model, the observer first assesses whether the sensory measurement is asynchronous; if so, she adjusts the bias proportionally to the magnitude of the measured asynchrony. Each model was paired with either modality-specific or modality-independent precision of arrival latency. A Bayesian model comparison revealed that both the causal-inference process and modality-specific precision in arrival latency are required to capture the nonlinearity and asymmetry observed in audiovisual temporal recalibration. Our findings support the hypothesis that audiovisual temporal recalibration relies on the same causal-inference processes that govern cross-modal perception.

Indexed as

Auditory PerceptionTime PerceptionVisual PerceptionAcoustic StimulationAdultFemaleHumansMalePhotic StimulationYoung Adultaudiovisual temporal recalibrationBayesian modelingcausal inferencehumanneuroscience

Identifiers

PMID39996594
PMCPMC11856930

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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.