Crossmodal statistical learning is facilitated by modality predictability

Statistical learning involves extracting statistical regularities from the environment. Despite the ubiquitous crossmodal relations in our environment, previous research has failed in showing crossmodal learning suggesting that statistical learning is modality-specific, occurring within but not between sensory modalities. The present study investigates under which circumstances statistical learning can occur between modalities. In the first experiment, participants viewed a stream of meaningless visual fractals and synthetic auditory stimuli. Importantly, the sequence of stimuli could be grouped into unimodal or crossmodal pairs based on their internal transitional probabilities. Using implicit and explicit measures of learning, we found that participants only learned the unimodal pairs. In the second experiment, pairs were presented in separate unimodal and crossmodal blocks. The crossmodal blocks alternated visual and auditory modalities allowing participants to anticipate the upcoming modality. This manipulation allowed significant statistical learning for the crossmodal pairs, reflected only by implicit measures. This suggests that modality transitions predictability aids correct attention deployment across sensory modalities, crucial for learning crossmodal statistical contingencies. In the third experiment, where audiovisual stimuli with semantic content were used leaving access to an amodal shared representation, participants could explicitly recognize statistical regularities between crossmodal pairs even when the upcoming modality was unpredictable. This finding suggests statistical learning between crossmodal pairs can occur when sensory-level limitations are bypassed, and when learning unfolds at an amodal level of representation. These findings challenge the view that statistical learning is strictly modality-specific, instead indicating that crossmodal statistical learning depends on attentional mechanisms and representational level. Public significance statementPrevious research has established that low-level statistical learning occurs within individual sensory modalities. However, evidence for statistical learning across modalities remains limited. This has led to the hypothesis that statistical learning operates as a modality-specific system, constrained by the perceptual properties and content of each sensory system. In this study, we demonstrate that modality transitions predictability enables crossmodal statistical learning, even in the absence of semantic information. Notably, this constraint does not apply to meaningful stimuli, which can be processed at an amodal level. Our findings broaden the classical neurobiological model of statistical learning by highlighting the roles of attentional mechanisms and representational levels in supporting crossmodal statistical learning.