title: Computational evidence that frequency trajectory theory does not oppose but emerges from age-of-acquisition theory.
abstract: According to the age-of-acquisition hypothesis, words acquired early in life are processed faster and more accurately than words acquired later. Connectionist models have begun to explore the influence of the age/order of acquisition of items (and also their frequency of encounter). This study attempts to reconcile two different methodological and theoretical approaches (proposed by Lambon Ralph & Ehsan, 2006 and Zevin & Seidenberg, 2002) to age-limited learning effects. The current simulations extend the findings reported by Zevin and Seidenberg (2002) that have shown that frequency trajectories (FTs) have limited and specific effects on word-reading tasks. Using the methodological framework proposed by Lambon Ralph and Ehsan (2006), which makes it possible to compare word-reading and picture-naming tasks in connectionist networks, we were able to show that FT has a considerable influence on age-limited learning effects in a picture naming task. The findings show that when the input-output mappings are arbitrary (simulating picture naming tasks), the links formed by the network become entrenched as a result of early experience and that subsequent variations in frequency of exposure of the items have only a minor impact. In contrast, when the mappings between input-output are quasi-systematic or systematic (simulating word-reading tasks), the training of new items was generalized and resulted in the suppression of age-limited learning effects. At a theoretical level, we suggest that FT, which simultaneously takes account of time and the level of exposure across time, represents a more precise and modulated measure compared with the order of introduction of the items and may lead to innovative hypotheses in the field of age-limited learning effects.
authors.affiliation: Laboratoire de Psychologie et Neurocognition, UMR CNRS 5105, Université Pierre Mendès-France, Grenoble, France. Martial.Mermillod@upmf-grenoble.fr
authors.forename: Martial
authors.initials: M
authors.lastname: Mermillod
authors.forename: Patrick
authors.initials: P
authors.lastname: Bonin
authors.forename: Alain
authors.initials: A
authors.lastname: Méot
authors.forename: Ludovic
authors.initials: L
authors.lastname: Ferrand
authors.forename: Michel
authors.initials: M
authors.lastname: Paindavoine
mesh_terms: D000367:Age Factors; D001185:Artificial Intelligence; D006801:Humans; D007804:Language Development; D008960:Models, Psychological; D016571:Neural Networks, Computer; D011578:Psycholinguistics; D011932:Reading; D013997:Time Factors