Statistical Learning (SL) is typically considered to be a domain-general mechanism by which cognitive systems discover the underlying statistical regularities in the input. Recent findings, however, show clear differences in processing regularities across modalities and stimuli as well as low correlations between performance on visual and auditory tasks. Why does a presumably domain-general mechanism show distinct patterns of modality and stimulus specificity? Here we claim that the key to this puzzle lies in the prior knowledge brought upon by learners to the learning task. Specifically, we argue that learners' already entrenched expectations about speech co-occurrences from their native language impacts what they learn from novel auditory verbal input. In contrast, learners are free of such entrenchment when processing sequences of visual material such as abstract shapes. We present evidence from three experiments supporting this hypothesis by showing that auditory-verbal tasks display distinct item-specific effects resulting in low correlations between test items. In contrast, non-verbal tasks - visual and auditory - show high correlations between items. Importantly, we also show that individual performance in visual and auditory SL tasks that do not implicate prior knowledge regarding co-occurrence of elements, is highly correlated. In a fourth experiment, we present further support for the entrenchment hypothesis by showing that the variance in performance between different stimuli in auditory-verbal statistical learning tasks can be traced back to their resemblance to participants' native language. We discuss the methodological and theoretical implications of these findings, focusing on models of domain generality/specificity of SL.

How does prior linguistic knowledge modulate learning in verbal auditory statistical learning (SL) tasks? Here, we address this question by assessing to what extent the frequency of syllabic cooccurrences in the learners' native language determines SL performance. We computed the frequency of co-occurrences of syllables in spoken Spanish through a transliterated corpus, and used this measure to construct two artificial familiarization streams. One stream was constructed by embedding pseudowords with high co-occurrence frequency in Spanish ("Spanish-like" condition), the other by embedding pseudowords with low co-occurrence frequency ("Spanish-unlike" condition). Native Spanishspeaking participants listened to one of the two streams, and were tested in an old/new identification task to examine their ability to discriminate the embedded pseudowords from foils. Our results show that performance in the verbal auditory SL (ASL) task was significantly influenced by the frequency of syllabic co-occurrences in Spanish: When the embedded pseudowords were more "Spanish-like," participants were better able to identify them as part of the stream. These findings demonstrate that