A Dynamic Bayesian Observer Model Reveals Origins of Bias in Visual Path Integration

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Humans are typically biased while navigating by integrating their self-motion. Using virtual reality and probabilistic modeling, Lakshminarasimhan et al. demonstrate that systematic errors in visual path integration originate from the combined influence of a slow-velocity prior and growing position uncertainty.

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