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Consciousness and Predictive Processing

Wanja Wiese

Experienced Wholeness January 12, 2018 DOI: 10.7551/mitpress/9780262036993.003.0008 (opens in new tab)

Summary

AI-generated from the abstract

Predictive processing (PP) is not itself a theory of consciousness, but it may inform consciousness research if taken as a general theory of brain function—the idea that the brain's primary job is to minimize prediction error. This chapter explores how PP explains attention and its relationship to consciousness, including how volitional attention can alter conscious contents. It also proposes that PP offers a unifying framework for several theories of consciousness, such as global workspace theory, attention schema theory, and integrated information theory.

Study at a glance

Characteristics Theoretical or philosophical paper Peer reviewed
Key finding Proposes that predictive processing can provide a unifying perspective on several theories of consciousness and their relation to attention.

Abstract

Predictive processing (PP) is not a theory of consciousness. Hence, it is not obvious that PP should have any relevance to research on consciousness. A first promising possibility opens up if we consider the ambitious assumption that PP is a general theory of brain function. If the brain’s function is to minimize prediction error (just as the heart’s function is to pump blood), as Jakob Hohwy (2015) suggests, then it might well be that the computational processes underlying consciousness can usefully be described within the PP framework. This chapter focuses on (i) how PP accounts for attention, and what this suggests with regards to the relation between attention and consciousness (e.g., how volitional attention may change the contents of consciousness); (ii) furthermore, it is suggested that PP can provide a unifying perspective on some proposed functions and theories of consciousness (such as global workspace theory, attention schema theory, and integrated information theoy).

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