aiqbench analysis
This paper applies the ROSE neural language model to analyze syntactic transfer in bilingual production, using oscillatory mechanisms to explain cross-linguistic influence at a neurocomputational level. By linking formal modeling properties with specific biomarkers of non-native processing, it provides implementational constraints for theories of bilingualism that go beyond traditional timing signatures like event-related potentials.
Neurocomputational Mechanisms of Syntactic Transfer in Bilingual Sentence Production
arXiv:2601.18056v2 Announce Type: replace Abstract: We discuss the benefits of incorporating oscillatory neural mechanisms into the study of bilingual production errors and their traditionally documented timing signatures (e.g., event-related potentials), which can offer new implementational-level constraints for theories of bilingualism. We argue that a recent neural model of language, ROSE, can offer a neurocomputational account of syntactic transfer in bilingual production, capturing some of its formal properties and the scope of morphosyntactic sequencing failure modes. We take as a case study cross-linguistic influence (CLI) and attendant theories of functional inhibition/competition, and present these as being driven by specific oscillatory failure modes during L2 sentence planning. We argue that modeling CLI in this way not only offers the kinds of linking hypotheses ROSE was built to encourage, but also licenses the exploration of more spatiotemporally complex biomarkers of non-native processing than more commonly discussed neural signatures.
Abstract:We discuss the benefits of incorporating oscillatory neural mechanisms into the study of bilingual production errors and their traditionally documented timing signatures (e.g., event-related potentials), which can offer new implementational-level constraints for theories of bilingualism. We argue that a recent neural model of language, ROSE, can offer a neurocomputational account of syntactic transfer in bilingual production, capturing some of its formal properties and the scope of morphosyntactic sequencing failure modes. We take as a case study cross-linguistic influence (CLI) and attendant theories of functional inhibition/competition, and present these as being driven by specific oscillatory failure modes during L2 sentence planning. We argue that modeling CLI in this way not only offers the kinds of linking hypotheses ROSE was built to encourage, but also licenses the exploration of more spatiotemporally complex biomarkers of non-native processing than more commonly discussed neural signatures.
Computation and Language (cs.CL)
arXiv:2601.18056 [cs.CL]
(or arXiv:2601.18056v2 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2601.18056 Focus to learn more arXiv-issued DOI via DataCite
Uluslu, A. Y., & Murphy, E. (2026). Neurocomputational mechanisms of syntactic transfer. Journal of Neurolinguistics, 80, Article 101363
https://doi.org/10.1016/j.jneuroling.2026.101363. Focus to learn more DOI(s) linking to related resources
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