Statistical learning abilities and their relation to language

Numerous studies on statistical learning (SL) have demonstrated humans' sensitivity to complex statistical properties in their sensory environment. These observations have had a profound impact on the study of language, highlighting statistical aspects of the linguistic input that can be learned from experience, leading to the widespread claim that SL plays a key role in language acquisition and processing. But how can this theorized link be experimentally demonstrated? One increasingly popular avenue comes from studies of individual differences, which tie individual variability in SL to variance in linguistic behavior. This review presents the theoretical advances stemming from this line of research, as well as some of the challenges it currently faces. It contends that while previous studies had an important role in establishing the existence of some coarse-grained link between SL and language, recent developments in SL research suggest that the exact nature of this relationship is more complex than originally conceived and is still far from being fully understood. I specifically discuss three outstanding challenges: (a) understanding individual differences in light of the componential nature of SL, (b) mapping the full array of SL processes given the complexity of real-world statistics, and (c) estimating the strength of current empirical evidence while taking into account both positive and null findings. Confronting these issues, I argue, is a necessary step towards a full theory of the role of SL across language.