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3 - Computational Models of Reading and Mathematical Difficulties

from Part I - Theoretical Frameworks and Computational Models

Published online by Cambridge University Press:  28 July 2022

By
Marco Zorzi  and
Alberto Testolin
Edited by
Michael A. Skeide
Michael A. Skeide
Affiliation:
Max Planck Institute for Human Cognitive and Brain Sciences
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Summary

Computational modelling is a powerful tool in cognitive science to evaluate or compare existing theories and to make novel experimental predictions. In contrast to the vague formulation of traditional verbal theories (e.g., box-and-arrow models), computational models need to be formally explicit in any implementational detail and can produce accurate simulations of human performance. Computational modelling has many different flavours that reflect distinct theoretical approaches to understanding human cognition (see McClelland 2009, for a review).

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Chapter
Information
The Cambridge Handbook of Dyslexia and Dyscalculia , pp. 45 - 60
Publisher: Cambridge University Press
Print publication year: 2022

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References

Suggestions for Further Reading

Harm, M. W., and Seidenberg, M. S.. 1999. ‘Phonology, Reading Acquisition, and Dyslexia: Insights from Connectionist Models’. Psychological Review, 106 (3): 491–528.CrossRefGoogle ScholarPubMed
Perry, C., Zorzi, M., and Ziegler, J. C.. 2019. ‘Understanding Dyslexia Through Personalized Large-Scale Computational Models’. Psychological Science, 30: 386–95.CrossRefGoogle ScholarPubMed
Testolin, A., Zou, W. Y., and McClelland, J. L.. 2020. ‘Numerosity Discrimination in Deep Neural Networks: Initial Competence, Developmental Refinement and Experience Statistics’. Developmental Science, 23 (5): e12940.Google Scholar
Ziegler, J. C., Perry, C., and Zorzi, M.. 2020. ‘Learning to Read and Dyslexia: From Theory to Intervention Through Personalized Computational Models’. Current Directions in Psychological Science, 29 (3): 293–300.CrossRefGoogle ScholarPubMed
Zorzi, M., and Testolin, A.. 2018. ‘An Emergentist Perspective on the Origin of Number Sense’. Philosophical Transactions of the Royal Society B: Biological Sciences, 373 (1740): 20170043.CrossRefGoogle Scholar

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