The present paper addresses the study of non-arbitrariness in language within a deep learning framework. We present a set of experiments aimed at assessing the pervasiveness of different forms of non-arbitrary phonological patterns across a set of typologically distant languages. Different sequence-processing neural networks are trained in a set…

Natural language is highly complex and can be challenging for some learners, yet the contribution of complexity to individual differences in language learning remains poorly understood. This poor understanding appears due to both a lack of consensus among researchers regarding what complexity is, and to on-line language research often employing…

The present study aimed to refine current hypotheses regarding thematic reversal anomalies, which have been found to elicit either N400 or--more frequently--"semantic-P600" (sP600) effects. Our goal was to investigate whether distinct ERP profiles reflect aspectual-thematic differences between Agent-Subject Verbs (ASVs; e.g., "to eat") and…