Most statistical learning studies focus on the learning oftransitional probabilities between adjacent elements in asequence, however, other statistical regularities may un-derpin different aspects of processing language and regu-larities in other domains. Here, we investigate how con-junctive statistical regularities (of the form A and B to-gether predict C) can be learned, and how this learningis impacted by similarity in representations analogousto that in unambiguous words, homonyms with mul-tiple unrelated meanings, and polysemes with multiplerelated meanings. We observed that provided the stimu-lus structure is relatively simple, participants are readilyable to learn conjunctive probabilities and display sen-sitivity to relatedness among representations. These re-sults open new theoretical possibilities for exploring thedomain-generality of how the learning and processingsystems merge conjunctive information in simple labo-ratory tasks and in natural language.

Most words are polysemous, denoting related but distinct senses (e.g., chicken referring to an ANIMAL or to FOOD).Jager, Green, and Clelland (2016, LCN) reported facilitatory effects of polysemy on lexical processing that interacted withword frequency and type of task. We undertook a broader investigation of interactions between polysemy and severalsublexical, lexical, and semantic properties of words, to determine whether such interactions could explain inconsistenteffects of polysemy reported in the literature. Estimating degree of polysemy using dictionary sense counts, we studied theinteraction between polysemy and these other properties when predicting performance in lexical decision and semantic cat-egorization mega-studies. We observed interactions between polysemy and both lexical and semantic, but not sublexical,variables. Our results, while not replicating the exact effects reported by Jager and colleagues, highlight the importance ofdeveloping models of semantic ambiguity that take into consideration interactions with other psycholinguistic propertiesof words.