Abstract

The predictive processing framework has gained significant popularity across disciplines investigating the mind and brain. In this article we critically examine two of the recently made claims about the kind of headway that the framework can make in the neuroscientific and philosophical investigation of consciousness. Firstly, we argue that predictive processing is unlikely to yield significant breakthroughs in the search for the neural correlates of consciousness as it is still too vague to individuate neural mechanisms at a fine enough scale. Despite its unifying ambitions, the framework harbors a diverse family of competing computational models which rely on different assumptions and are under-constrained by neurological data. Secondly, we argue that the framework is also ill suited to provide a unifying theory of consciousness. Here, we focus on the tension between the claim that predictive processing is compatible with all of the leading neuroscientific models of consciousness with the fact that most attempts explaining consciousness within the framework rely heavily on external assumptions.

Highlights

  • The predictive processing (PP) framework has caused a lot of excitement among philosophers and cognitive scientists in the last decade

  • We critically assessed the proposal that the popular PP approach to perception, cognition, and action can be successfully applied to consciousness and guide the search for the neural correlates of consciousness

  • It is questionable whether or not the PP framework can, offer a componential analysis of the nervous system which could guide empirical investigations aimed at uncovering the mechanisms underlying conscious experiences

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Summary

Introduction

The predictive processing (PP) framework has caused a lot of excitement among philosophers and cognitive scientists in the last decade. The internal model and world can be matched in one of two ways: either the input is used to update the model that yielded the predictions in the first place (perceptual inference) or the sensory input is changed via action in order to match the model (active inference).1 Proponents of such approaches have already demonstrated its strong potential to accommodate various mental phenomena surrounding perception, cognitive penetration, perceptual binding, and attention Hohwy and Seth issued a programmatic statement trying to make good on the claim that predictive processing can inform us about different facets of conscious experience and guide the search for systematic neural correlates of consciousness (NCCs) They suggest that PP offers the most promising approach for embedding the on-going search for the NCCs within a unifying framework, one which can even motivate and operationalize “closer links between phenomenological properties of conscious experience and mechanistic properties of underlying neural substrates”

Determining neural correlates of consciousness
PP and the search for systematic NCCs
Bayes in the brain?
The issue of fine-grained realism about PP
The issue of coarse-grained realism about PP
PP and the hard problem
PP and cognitivism about consciousness
Conclusion
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