10 found
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  1.  11
    Hierarchical Structure in Sequence Processing: How to Measure It and Determine Its Neural Implementation.Julia Uddén, Mauricio Jesus Dias Martins, Willem Zuidema & W. Tecumseh Fitch - 2020 - Topics in Cognitive Science 12 (3):910-924.
    Spoken language consists of a linear sequence of units, from which the existence of particular underlying hierarchical processing mechanisms is inferred. Uddén et al. use graph theory to provide a framework for describing the possible structural relationships that may underlie a linear output sequence. Being more explicit in defining different structures can help identifying and testing for such structures in AGL experiments, as well as help showing how behavioral and neuroimaging data reveals signatures of hierarchical processing in humans.
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  2.  8
    Hierarchical Structure in Sequence Processing: How to Measure It and Determine Its Neural Implementation.Julia Uddén, Mauricio de Jesus Dias Martins, Willem Zuidema & W. Tecumseh Fitch - 2020 - Topics in Cognitive Science 12 (3):910-924.
    Spoken language consists of a linear sequence of units, from which the existence of particular underlying hierarchical processing mechanisms is inferred. Uddén et al. use graph theory to provide a framework for describing the possible structural relationships that may underlie a linear output sequence. Being more explicit in defining different structures can help identifying and testing for such structures in AGL experiments, as well as help showing how behavioral and neuroimaging data reveals signatures of hierarchical processing in humans.
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  3.  56
    Children’s Grammars Grow More Abstract with Age-Evidence from an Automatic Procedure for Identifying the Productive Units of Language.Gideon Borensztajn, Willem Zuidema & Rens Bod - 2009 - Topics in Cognitive Science 1 (1):175-188.
    We develop an approach to automatically identify the most probable multiword constructions used in children’s utterances, given syntactically annotated utterances from the Brown corpus of CHILDES. The found constructions cover many interesting linguistic phenomena from the language acquisition literature and show a progression from very concrete toward abstract constructions. We show quantitatively that for all children of the Brown corpus grammatical abstraction, defined as the relative number of variable slots in the productive units of their grammar, increases globally with age.
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  4.  9
    Five Ways in Which Computational Modeling Can Help Advance Cognitive Science: Lessons From Artificial Grammar Learning.Willem Zuidema, Robert M. French, Raquel G. Alhama, Kevin Ellis, Timothy J. O'Donnell, Tim Sainburg & Timothy Q. Gentner - 2020 - Topics in Cognitive Science 12 (3):925-941.
    Zuidema et al. illustrate how empirical AGL studies can benefit from computational models and techniques. Computational models can help clarifying theories, and thus in delineating research questions, but also in facilitating experimental design, stimulus generation, and data analysis. The authors show, with a series of examples, how computational modeling can be integrated with empirical AGL approaches, and how model selection techniques can indicate the most likely model to explain experimental outcomes.
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  5.  27
    On the structural ambiguity in natural language that the neural architecture cannot deal with.Rens Bod, Hartmut Fitz & Willem Zuidema - 2006 - Behavioral and Brain Sciences 29 (1):71-72.
    We argue that van der Velde's & de Kamps's model does not solve the binding problem but merely shifts the burden of constructing appropriate neural representations of sentence structure to unexplained preprocessing of the linguistic input. As a consequence, their model is not able to explain how various neural representations can be assigned to sentences that are structurally ambiguous.
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  6. Thomas' theorem meets Bayes' rule: a model of the iterated learning of language.Vanessa Ferdinand & Willem Zuidema - 2009 - In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society. pp. 1786--1791.
     
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  7.  10
    Editors' Review and Introduction: Learning Grammatical Structures: Developmental, Cross‐Species, and Computational Approaches.Carel ten Cate, Judit Gervain, Clara C. Levelt, Christopher I. Petkov & Willem Zuidema - 2020 - Topics in Cognitive Science 12 (3):804-814.
    Artificial grammar learning (AGL) is used to study how human adults, infants, animals or machines learn various sorts of rules defined over sounds or visual items. Ten Cate et al. introduce the topic and provide a critical synthesis of this important interdisciplinary area of research. They identify the questions that remain open and the challenges that lie ahead, and argue that the limits of human, animal and machine learning abilities have yet to be found.
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  8.  9
    Selecting the model that best fits the data.Willemijn van Woerkom & Willem Zuidema - 2017 - Behavioral and Brain Sciences 40.
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  9.  51
    How did we get from there to here in the evolution of language?Willem Zuidema & Bart de Boer - 2003 - Behavioral and Brain Sciences 26 (6):694-695.
    Jackendoff's scenario of the evolution of language is a major contribution towards a more rigorous theory of the origins of language, because it is theoretically constrained by a testable theory of modern language. However, the theoretical constraints from evolutionary theory are not really recognized in his work. We hope that Jackendoff's lead will be followed by intensive cooperation between linguistic theorists and evolutionary modellers.
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  10.  48
    The importance of social learning in the evolution of cooperation and communication.Willem Zuidema - 2002 - Behavioral and Brain Sciences 25 (2):283-284.
    The new emphasis that Rachlin gives to social learning is welcome, because its role in the emergence of altruism and communication is often underestimated. However, Rachlin's account is underspecified and therefore not satisfactory. I argue that recent computational models of the evolution of language show an alternative approach and present an appealing perspective on the evolution and acquisition of a complex, altruistic behavior like syntactic language.
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