Constraints on Statistical Learning Across Species

Both human and nonhuman organisms are sensitive to statistical regularities in sensory inputs that support functions including communication, visual processing, and sequence learning. One of the issues faced by comparative research in this field is the lack of a comprehensive theory to explain the relevance of statistical learning across distinct ecological niches. In the current review we interpret cross-species research on statistical learning based on the perceptual and cognitive mechanisms that characterize the human and nonhuman models under investigation. Considering statistical learning as an essential part of the cognitive architecture of an animal will help to uncover the potential ecological functions of this powerful learning process. The ecological relevance of statistical learning is mostly undefined in the animal kingdom; the majority of cross-species research in this area focuses on revealing human-like abilities rather than discovering the functions of statistical learning in different species. Perception, memory, and learning guide and constrain statistical learning differently across species, limiting the extent to which organisms can process regularities from sensory inputs. Cross-species differences can be framed around general-purpose abilities, developmental processes, and learning challenges characterizing the animal models under investigation, and can be interpreted by considering how statistical learning is integrated within the cognitive system of the learner.