This paper spells out the attention schema theory of consciousness in terms of the predictive processing framework. As it stands, the attention schema theory lacks a plausible computational formalization that could be used for developing possible mechanistic models of how it is realized in the brain. The predictive processing framework, on the other hand, fails to provide a plausible explanation of the subjective quality or the phenomenal aspect of conscious experience. The aim of this work is to apply the formal (...) tools of predictive processing to outline a possible model of cognition that details a plausible way in which organisms may acquire or construct the kinds of schemas postulated by the attention schema theory. This is done in terms of Bayesian control models, which tend to favour representing information in a frugal or 'sparse' manner that strips away detail in precisely the way that the attention schema requires. Once integrated, these two accounts can offer a plausible explanation of the supposedly irreducible and mysterious 'feel' of conscious experience, in terms of the frugal manner in which perceptual mechanisms are represented by the attention schema. (shrink)

Chalmers (2018) raises three challenges for Michael Graziano's attention schema theory. Our aim in this paper is to bolster Graziano's attention schema theory with some tools and insights from the predictive processing framework, in order to respond to the challenges raised by Chalmers and more generally strengthen the theory. We will first introduce the attention schema theory and the three challenges raised by Chalmers, before outlining our application of predictive processing to the theory and how it can resolve these challenges, (...) thus offering a solution to the meta-problem. (shrink)