On logical inference over brains, behaviour, and artificial neural networks
In the cognitive, computational, and neuro-sciences, practitioners often reason about what
computational models represent or learn, as well as what algorithm is instantiated. The
putative goal of such reasoning is to generalize claims about the model in question, to
claims about the mind and brain, and the neurocognitive capacities of those systems. Such
inference is often based on a model's performance on a task, and whether that performance
approximates human behavior or brain activity. Here we demonstrate how such …
computational models represent or learn, as well as what algorithm is instantiated. The
putative goal of such reasoning is to generalize claims about the model in question, to
claims about the mind and brain, and the neurocognitive capacities of those systems. Such
inference is often based on a model's performance on a task, and whether that performance
approximates human behavior or brain activity. Here we demonstrate how such …
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