6533b7dbfe1ef96bd126ff9e
RESEARCH PRODUCT
Learning nonadjacent dependencies : No need for algebraic-like computations.
Nadine GallandMichael D. TylerPierre PerruchetRonald Peeremansubject
Relation (database)ComputationExperimental and Cognitive Psychology[ SCCO.PSYC ] Cognitive science/Psychology050105 experimental psychologyAssociation03 medical and health sciences0302 clinical medicineCognitionDevelopmental NeurosciencePhoneticsEvaluation methodsHumansLearning0501 psychology and cognitive sciencesAlgebraic numberAdaptation (computer science)General PsychologyAssociative propertyProblem SolvingComputingMilieux_MISCELLANEOUSCognitive science05 social sciencesInvalid Data[SCCO.PSYC]Cognitive science/Psychology[SCCO.PSYC] Cognitive science/PsychologyPsychologyPsychological Theory030217 neurology & neurosurgeryNatural languageMathematicsdescription
Is it possible to learn the relation between 2 nonadjacent events? M. Pena, L. L. Bonatti, M. Nespor, and J. Mehler (2002) claimed this to be possible, but only in conditions suggesting the involvement of algebraic-like computations. The present article reports simulation studies and experimental data showing that the observations on which Pena et al. grounded their reasoning were flawed by deep methodological inadequacies. When the invalid data are set aside, the available evidence fits exactly with the predictions of a theory relying on ubiquitous associative mechanisms. Because nonadjacent dependencies are frequent in natural language, this reappraisal has far-reaching implications for the current debate on the need for rule-based computations in human adaptation to complex structures.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2004-12-09 |