Bayesian causal inference reveals declined proprioception, increased integration bias underlie older adults' stronger visual bias in hand position perception.

Self-localization is fundamental to bodily self-consciousness across the lifespan. Humans estimate body-part position by integrating afferent signals such as vision and proprioception. Rubber and mirror hand illusions highlight the dominant role of vision in hand position perception. Although older adults rely more heavily on visual information, the computational mechanisms underlying age-related increases in visual bias remain unclear. Here, we examined age-related changes in visuo-proprioceptive integration using a Bayesian causal inference (BCI) model. Two experiments introduced spatial discrepancies between visual and proprioceptive hand positions to manipulate the likelihood of integration. Participants reached toward a target after the visual hand disappeared, allowing the BCI model to estimate sensory reliabilities and the prior probability of a common cause ([Formula: see text]). Decision-making strategies were also compared within the BCI framework. Older adults exhibited reduced proprioceptive reliability and a higher [Formula: see text], indicating a stronger tendency to infer a shared source for visual and proprioceptive signals. No age-related differences were observed in decision-making strategy. These findings suggest that age-related visual bias reflects changes not only in sensory reliability but also in causal inference during multisensory integration.