Computational Evidence That Frequency Trajectory Theory Does Not Oppose But Emerges From Age‐of‐Acquisition Theory
David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Cognitive Science 36 (8):1499-1531 (2012)
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
|Keywords||Quasi‐systematic/systematic mappings Arbitrary mappings Age of acquisition Frequency trajectory|
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References found in this work BETA
R. French (1999). Catastrophic Forgetting in Connectionist Networks. Trends in Cognitive Sciences 3 (4):128-135.
Willem J. M. Levelt, Ardi Roelofs & Antje S. Meyer (1999). A Theory of Lexical Access in Speech Production. Behavioral and Brain Sciences 22 (1):1-38.
Martial Mermillod, Nicolas Vermeulen, Daniel Lundqvist & Paula M. Niedenthal (2009). Neural Computation as a Tool to Differentiate Perceptual From Emotional Processes: The Case of Anger Superiority Effect. Cognition 110 (3):346-357.
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