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Cognition|July 20, 2025
Recalling sequences from memory can explain the distribution of recursive structures in natural languagesFenna H Poletiek, Peter Hagoort, Bruno R BocanegraCognition|June 1, 2015
What baboons can (not) tell us about natural language grammarsFenna H Poletiek, Hartmut Fitz, Bruno R BocanegraNature Human Behaviour|April 5, 2019
Intelligent problem-solvers externalize cognitive operationsBruno R Bocanegra, Fenna H Poletiek, Bouchra Ftitache, et al.Journal of Experimental Psychology. Learning, Memory, and Cognition|October 25, 2021
The semantics-syntax interface: Learning grammatical categories and hierarchical syntactic structure through semanticsFenna H Poletiek, Padraic Monaghan, Maartje van de Velde, et al.Behavioral Sciences & the Law|April 30, 2002
How psychiatrists and judges assess the dangerousness of persons with mental illness: an 'expertise bias"Fenna H PoletiekActa Psychologica|November 9, 2002
Implicit learning of a recursive rule in an artificial grammarFenna H PoletiekCognitive Science|September 29, 2018
Under What Conditions Can Recursion Be Learned? Effects of Starting Small in Artificial Grammar Learning of Center-Embedded StructureFenna H Poletiek, Christopher M Conway, Michelle R Ellefson, et al.Cognition|December 15, 2010
The impact of adjacent-dependencies and staged-input on the learnability of center-embedded hierarchical structuresJun Lai, Fenna H PoletiekQuarterly Journal of Experimental Psychology (2006)|December 10, 2008
What is learned about fragments in artificial grammar learning? A transitional probabilities approachFenna H Poletiek, Gezinus WoltersPhilosophical Transactions of the Royal Society of London. Series B, Biological Sciences|June 13, 2012
How semantic biases in simple adjacencies affect learning a complex structure with non-adjacencies in AGL: a statistical accountFenna H Poletiek, Jun LaiPageof 30