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Cognition with neurons: A large-scale, biologically realistic model of the Wason task

I present a cognitive model, dubbed BioSLIE, that integrates and extends recent advances in: 1) distributed, structuresensitive representation; 2) neurocomputational modeling; and 3) our understanding of the neuroanatomy of inference. As a result, BioSLIE is biologically detailed, learns different behaviors in different contexts, and exhibits systematic, structuresensitive generalization. Here, BioSLIE is applied to the Wason card selection task. Its performance meets Cosmides’ (1989) challenge to mechanistically define domain-general procedures that can use induction to produce the observed domain specific performance on the Wason task. As well, it demonstrates the relevance of neural computation to understanding cognition, despite claims to the contrary by Fodor and Pylyshyn (1988) and Jackendoff (2002).