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As the various contributions to this special volume will no doubt attest, the predictive coding model of the mind and brain is remarkably ambitious in scope of explanation. For one, its central proponents allege that it offers a single, unified mechanism for phenomena that are traditionally treated as distinct and, accordingly, explained in disparate ways. As Jakob Hohwy writes, Perception, action, and attention are but three different ways of doing the very same thing. All three ways must be balanced carefully with each other in order to get the world right. The unity of conscious perception, the nature of the self, and our knowledge of our private mental world is at heart grounded in our attempts to optimize predictions about our ongoing sensory input. (Hohwy 2013: 2).The mechanism that allegedly unifies these phenomena-prediction error minimization-is also supposed to promise unity across the cognitive sciences. As Andy Clark writes, this framework makes rich and illuminating contact with work in cognitive neuroscience while boasting a firm foundation in computational modeling and Bayesian theory. It thus offers what is arguably the first truly systematic bridge linking three of our most promising tools for understanding mind and reason: cognitive neuroscience, computational modelling, and probabilistic Bayesian approaches to dealing with evidence and uncertainty (Clark, 2013 190-1).Ambition such as this begets excitement, but it should also encourage careful scrutiny. Our general interest is at the interface of two standardly distinguished mental kinds or processescognition and sense perception. Both of the above theorists, as well as others, embrace to some degree a radical consequence of the predictive coding framework, namely, that the cognition/perception distinction will have to be revised in some important ways, if not abandoned outright. An important way to test this feature of the framework, as well as use it to shed new insight 1 This work was thoroughly collaborative and the paper thoroughly co-authored--the order of authors was chosen randomly.

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