Generalization from newly learned words reveals structural properties of the human reading system

We presented a brief overview of the warping mechanism, the main simulation and behavioural results related to learning and generalizing from new made up words, and the implications of these results for dual route models of the lexical system and statistical learning theory at the International Workshop on Reading and Developmental Dyslexia (Bilbao, 5-7 May 2016), the First vs. Second Language Learning: from Neurobiology to Cognition Workshop (Jerusalem, 26-29 September, 2016) and at the 57th Annual Meeting of the Psychonomic Society (Boston, 17-20 November 2016).This is the author accepted manuscript. The final version is available from American Psychological Association via the DOI in this record.Connectionist accounts of quasiregular domains, such as spelling-sound correspondences in English, represent exception words (e.g., pint) amidst regular words (e.g., mint) via a graded “warping” mechanism. Warping allows the model to extend the dominant pronunciation to nonwords (regularization) with minimal interference (spillover) from the exceptions. We tested for a behavioral marker of warping by investigating the degree to which participants generalized from newly learned made-up words, which ranged from sharing the dominant pronunciation (regulars), a subordinate pronunciation (ambiguous), or a previously non-existent (exception) pronunciation. The new words were learned over two days, and generalization was assessed 48 hours later using nonword neighbors of the new words in a tempo naming task. The frequency of regularization (a measure of generalization) was directly related to degree of warping required to learn the pronunciation of the new word. Simulations using the Plaut et al. (1996) model further support a warping interpretation. Findings highlight the need to develop theories of representation that are integrally tied to how those representations are learned and generalized.This work was supported by a Marie Curie Fellowship (PIIF-GA-2013-627784) to Blair C. Armstrong and by a grant from the Spanish Ministry of Science and Innovation (PSI2011-24048) to Nicolas Dumay. Additional support was provided by the Ohio State University. We thank Christine Kay for helping with data collection and scoring, as well as David Plaut, Manuel Carreiras, Ram Frost, Yevdokiya Yermolayeva, and three anonymous reviewers for commenting on earlier drafts