Using an artificial script, we have previously demonstrated that readers use co-occurrence statistics to learn about the presence and position of af ix-like chunks in strings of pseudo-letters (Lelonkiewicz, Ktori & Crepaldi, 2020). These findings were taken as evidence that visual statistical learning might be implicated in morphological processing during visual word recognition.

Reading involves an interaction of linguistic and perceptual processes, in which top-down, lexical knowledge aids letter perception. Does such facilitation interact with letter co-occurrence regularities? Skilled readers were briefly exposed to strings of five consonants; critically, letters in position 2 and 4 were embedded in either high (L in e.g., GLVTZ) or low (e.g., NLRTZ) transitional probability (TP) triplets. When presented with two strings differing by the critical letter (GLVTZ vs.

There is little contact between theories of individual word identification and sentence processing models. In this talk, I present a study, led by Katarina Marjanovic and carried out in collaboration with Yamil Vidal, where we tried to bridge this gap by assessing cross-word priming during natural reading. By combining eye tracking and EEG, we found that cross-word semantic priming (“…the cat and the dog…” vs. “…the table and the dog…”) is solid and strong, both in eye tracking metrics and in Fixated-Related Potentials (FRPs). This is not the case for morphological priming (“…the cat and the dog…” vs. “…the cats and the dog…”), which doesn’t seem to emerge in sentence context.