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Maybe this old dinosaur isn’t extinct: What does Bayesian modeling add to associationism?

Published online by Cambridge University Press:  25 August 2011

Irina Baetu ,
Itxaso Barberia ,
Robin A. Murphy  and
A. G. Baker
Irina Baetu
Affiliation:
Department of Experimental Psychology, University of Cambridge, Cambridge CB2 3EB, England, United Kingdom. [email protected]
Itxaso Barberia
Affiliation:
Department of Psychology, McGill University, Montréal, QC, H3A 1B1, Canada. [email protected]
Robin A. Murphy
Affiliation:
Department of Experimental Psychology, University of Oxford, Oxford OX1 3UD, United Kingdom. [email protected]@psy.ox.ac.ukhttp://web.me.com/robinmurphy/oxford/Welcome.html
A. G. Baker
Affiliation:
Department of Psychology, McGill University, Montréal, QC, H3A 1B1, Canada. [email protected]
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Abstract

We agree with Jones & Love (J&L) that much of Bayesian modeling has taken a fundamentalist approach to cognition; but we do not believe in the potential of Bayesianism to provide insights into psychological processes. We discuss the advantages of associative explanations over Bayesian approaches to causal induction, and argue that Bayesian models have added little to our understanding of human causal reasoning.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 34 , Issue 4 , August 2011 , pp. 190 - 191
Copyright
Copyright © Cambridge University Press 2011

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References

Baetu, I. & Baker, A. G. (2009) Human judgments of positive and negative causal chains. Journal of Experimental Psychology: Animal Behavior Processes 35:153–68.Google Scholar
Baker, A. G., Murphy, R. A. & Vallee-Tourangeau, F. (1996) Associative and normative models of causal induction: Reacting to versus understanding cause. In: The psychology of learning and motivation, vol. 34, ed. Shanks, D. R., Holyoak, K. J. & Medin, D. L., pp. 1–45. Academic Press.Google Scholar
Cowell, R. A., Bussey, T. J. & Saksida, L. M. (2006) Why does brain damage impair memory? A connectionist model of object recognition memory in perirhinal cortex. Journal of Neuroscience 26:12186–97.CrossRefGoogle ScholarPubMed
Hagmayer, Y., Sloman, S. A., Lagnado, D. A. & Waldmann, M. R. (2007) Causal reasoning through intervention. In: Causal learning: Psychology, philosophy, and computation, ed. Gopnik, A. & Schultz, L., pp. 86–100. Oxford University Press.Google Scholar
Harm, M. W. & Seidenberg, M. S. (1999) Phonology, reading acquisition, and dyslexia: Insights from connectionist models. Psychological Review 106:491–528.CrossRefGoogle ScholarPubMed
Kim, J. J., Krupa, D. J. & Thompson, R. F. (1998) Inhibitory cerebello-olivary projections and blocking effect in classical conditioning. Science 279:570–73.CrossRefGoogle ScholarPubMed
Lagnado, D. A. & Sloman, S. A. (2006) Time as guide to cause. Journal of Experimental Psychology: Learning, Memory, and Cognition 32(3):451–60.Google ScholarPubMed
McClelland, J. L. & Rumelhart, D. E. (1988) Explorations in parallel distributed processing: A handbook of models, programs, and exercises. MIT Press.Google Scholar
Pavlov, I. P. (1927) Conditioned reflexes. Oxford University Press.Google Scholar
Plaut, D. C. (1995) Double dissociation without modularity: Evidence from connectionist neuropsychology. Journal of Clinical and Experimental Neuropsychology 17:291–321.Google Scholar
Rescorla, R. A. & Wagner, A. R. (1972) A theory of Pavlovian conditioning: Variations in the effectiveness of reinforcement and nonreinforcement. In: Classical conditioning II: Current theory and research, ed. Black, A. H. & Prokasy, W. F., pp. 64–99. Appleton-Century-Crofts.Google Scholar
Steyvers, M., Tenenbaum, J. B., Wagenmakers, E.-J. & Blum, B. (2003) Inferring causal networks from observations and interventions. Cognitive Science 27:453–89.CrossRefGoogle Scholar
Waelti, P., Dickinson, A. & Schultz, W. (2001) Dopamine responses comply with basic assumptions. Nature 412:43–48.Google Scholar