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
Learn more about PhilPapers
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|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
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.
Citations of this work BETA
No citations found.
Similar books and articles
Jiajie Zhang Todd R. Johnson Hongbin Wang (1998). The Relation Between Order Effects and Frequency Learning in Tactical Decision Making. Thinking and Reasoning 4 (2):123 – 145.
Stellan Ohlsson (1997). Old Ideas, New Mistakes: All Learning is Relational. Behavioral and Brain Sciences 20 (1):79-80.
Keith S. Apfelbaum & Bob McMurray (2011). Using Variability to Guide Dimensional Weighting: Associative Mechanisms in Early Word Learning. Cognitive Science 35 (6):1105-1138.
Sophie Dufour, Angèle Brunellière & Ulrich H. Frauenfelder (2013). Tracking the Time Course of Word‐Frequency Effects in Auditory Word Recognition With Event‐Related Potentials. Cognitive Science 37 (3):489-507.
Derek Bickerton (2001). Okay for Content Words, but What About Functional Items? Behavioral and Brain Sciences 24 (6):1104-1105.
Joanne Arciuli & Ian C. Simpson (2012). Statistical Learning Is Related to Reading Ability in Children and Adults. Cognitive Science 36 (2):286-304.
Alexander Clark & Shalom Lappin (2013). Complexity in Language Acquisition. Topics in Cognitive Science 5 (1):89-110.
Steven J. Humphrey (1999). Probability Learning, Event-Splitting Effects and the Economic Theory of Choice. Theory and Decision 46 (1):51-78.
Erik D. Thiessen & Philip I. Pavlik (2013). iMinerva: A Mathematical Model of Distributional Statistical Learning. Cognitive Science 37 (2):310-343.
Letitia R. Naigles (2001). Why Theories of Word Learning Don't Always Work as Theories of Verb Learning. Behavioral and Brain Sciences 24 (6):1113-1114.
Janet H. Hsiao & Sze Man Lam (2013). The Modulation of Visual and Task Characteristics of a Writing System on Hemispheric Lateralization in Visual Word Recognition—A Computational Exploration. Cognitive Science 37 (5):861-890.
Heather Bortfeld (2004). Which Came First: Infants Learning Language or Motherese? Behavioral and Brain Sciences 27 (4):505-506.
Ricardo Sabates, Leon Feinstein & Eleni Skaliotis (2007). Who Achiveves Level 2 Qualifications During Adulthood? Evidence From the NCDS. British Journal of Educational Studies 55 (4):390 - 408.
William J. Rapaport & Michael W. Kibby (2002). Contextual Vocabulary Acquisition: A Computational Theory and Educational Curriculum. In Nagib Callaos, Ana Breda & Ma Yolanda Fernandez J. (eds.), Proceedings of the 6th World Multiconference on Systemics, Cybernetics and Informatics. International Institute of Informatics and Systemics.
Added to index2012-09-18
Total downloads2 ( #354,724 of 1,102,917 )
Recent downloads (6 months)1 ( #297,281 of 1,102,917 )
How can I increase my downloads?