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An Introduction to Cognitive Modeling

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An Introduction to Model-Based Cognitive Neuroscience

Abstract

We provide a tutorial on the basic attributes of computational cognitive models—models that are formulated as a set of mathematical equations or as a computer simulation. We first show how models can generate complex behavior and novel insights from very simple underlying assumptions about human cognition. We survey the different classes of models, from description to explanation, and present examples of each class. We then illustrate the reasons why computational models are preferable to purely verbal means of theorizing. For example, we show that computational models help theoreticians overcome the limitations of human cognition, thereby enabling us to create coherent and plausible accounts of how we think or remember and guard against subtle theoretical errors. Models can also measure latent constructs and link them to individual differences, which would escape detection if only the raw data were considered. We conclude by reviewing some open challenges.

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Author information

Authors and Affiliations

  1. School of Psychology, University of Western Australia, 35 Stirling Highway, 6009, Crawley, WA, Australia

    Simon Farrell

  2. University of Bristol, Department of Experimental Psychology, 12a Priory Road, Bristol BS8 1TU, UK

    Stephan Lewandowsky

Authors
  1. Simon Farrell
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  2. Stephan Lewandowsky
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Correspondence to Simon Farrell .

Editor information

Editors and Affiliations

  1. Cognitive Science Center, University of Amsterdam, Amsterdam, The Netherlands

    Birte U. Forstmann

  2. Department of Psychological Methods, University of Amsterdam, Amsterdam, The Netherlands

    Eric-Jan Wagenmakers

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Farrell, S., Lewandowsky, S. (2015). An Introduction to Cognitive Modeling. In: Forstmann, B., Wagenmakers, EJ. (eds) An Introduction to Model-Based Cognitive Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2236-9_1

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