ArticleeLife2025
Precision-based causal inference modulates audiovisual temporal recalibration.
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.
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4 citing papers in PubMed.
- Distilling noise characteristics and prior expectations in multisensory causal inference.PLoS computational biology · 2026Article
- Visual confidence accurately tracks increasing internal noise with eccentricity in peripheral vision.bioRxiv : the preprint server for biology · 2026Article
- Environmental motion presented ahead of self-motion modulates heading direction estimation.PLoS computational biology · 2025Article
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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.
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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.