The aim of this large-scale, preregistered, cross-linguistic study was to mediate between theories of the acquisition of inflectional morphology, which lie along a continuum from rule-based to analogy-based. Across three morphologically rich languages (Polish, Finnish and Estonian), 120 children (mean age 48.32 months, SD = 7.0 months) completed an experimental, elicited-production study of noun case marking. Confirmatory analyses found effects of surface-form (whole-word, token) frequency for Polish and Estonian, and phonological neighbourhood density (PND) for all three languages (using either our preregistered class-based or an exploratory form-based measure). An exploratory all-languages analysis yielded both main effects, and a predicted interaction, such that the effect of PND was greater for forms with lower surface-form frequency, which are less available for direct retrieval from memory. Cross-linguistic differences were investigated with exploratory analyses of case variance, affix syncretism and stem changes. We conclude that these findings are difficult to reconcile with accounts that posit rules or linguistic abstractions and are most naturally explained by analogy-based connectionist or exemplar accounts.The International Centre for Language and Communicative Development (LuCiD) will bring about a transformation in our understanding of how children learn to communicate, and deliver the crucial information needed to design effective interventions in child healthcare, communicative development and early years education. Learning to use language to communicate is hugely important for society. Failure to develop language and communication skills at the right age is a major predictor of educational and social inequality in later life. To tackle this problem, we need to know the answers to a number of questions: How do children learn language from what they see and hear? What do measures of children's brain activity tell us about what they know? and How do differences between children and differences in their environments affect how children learn to talk? Answering these questions is a major challenge for researchers. LuCiD will bring together researchers from a wide range of different backgrounds to address this challenge. The LuCiD Centre will be based in the North West of England and will coordinate five streams of research in the UK and abroad. It will use multiple methods to address central issues, create new technology products, and communicate evidence-based information directly to other researchers and to parents, practitioners and policy-makers. LuCiD's RESEARCH AGENDA will address four key questions in language and communicative development: 1) ENVIRONMENT: How do children combine the different kinds of information that they see and hear to learn language? 2) KNOWLEDGE: How do children learn the word meanings and grammatical categories of their language? 3) COMMUNICATION: How do children learn to use their language to communicate effectively? 4) VARIATION: How do children learn languages with different structures and in different cultural environments? The fifth stream, the LANGUAGE 0-5 PROJECT, will connect the other four streams. It will follow 80 English learning children from 6 months to 5 years, studying how and why some children's language development is different from others. A key feature of this project is that the children will take part in studies within the other four streams. This will enable us to build a complete picture of language development from the very beginning through to school readiness. Applying different methods to study children's language development will constrain the types of explanations that can be proposed, helping us create much more accurate theories of language development. We will observe and record children in natural interaction as well as studying their language in more controlled experiments, using behavioural measures and correlations with brain activity (EEG). Transcripts of children's language and interaction will be analysed and used to model how these two are related using powerful computer algorithms.

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