Apparent statistical inference in crows may reflect simple reinforcement learning

Abstract

Johnston et al. report results which they argue demonstrate that crows engage in statistical inference during decision-making. They trained two crows to associate a set of stimuli with different reward probabilities (from 10% to 90%) before choice tests between pairs of stimuli. Across most pairwise combinations, and in a control task in which the number of rewards was equated between probabilities, both crows preferred the stimulus associated with higher reward probability. The magnitude of this preference was affected by the absolute difference between the two probabilities, although (contrary to a claim made by Johnston et al. 2023) preference did not reflect the ratio of prior probabilities independently of absolute differences. Johnston et al. argue that preference for the stimulus with the higher reward probability is “the signature of true statistical inference” (p. 3238), implemented by an analogue magnitude system that represents the reward probability associated with each stimulus. Here, we show that a simple reinforcement learning model, with no explicit representation of reward probabilities, reproduces the critical features of crows’ performance—and indeed better accounts for the observed empirical findings than the concept of statistical inference based on analogue magnitude representations, because it correctly predicts the absence of a ratio effect that would reflect magnitudes when absolute distance is controlled. Contrary to Johnston et al.’s claims, these patterns of behaviour do not necessitate retrieval of calculated reward probabilities from long-term memory and dynamic application of this information across contexts, or (more specifically) require the involvement of an analogue magnitude system in representing abstract probabilities.