Awareness as inference in a higher-order state space. Issue 1 (11th March 2020)

• Record Type: Journal Article
• Authors: Fleming, Stephen M
• Is Part Of: Neuroscience of consciousness. Issue 1(2020)
• Publication Date: 2020-03-11
• Subjects: theories and models -- computational modeling -- consciousness -- metacognition; Consciousness -- Periodicals; Consciousness -- Physiological aspects -- Periodicals; 612.823
• DOI: 10.1093/nc/niz020
• Languages: English
• ISSNs: 2057-2107

Abstract

Abstract: Humans have the ability to report the contents of their subjective experience—we can say to each other, 'I am aware of X '. The decision processes that support these reports about mental contents remain poorly understood. In this article, I propose a computational framework that characterizes awareness reports as metacognitive decisions (inference) about a generative model of perceptual content. This account is motivated from the perspective of how flexible hierarchical state spaces are built during learning and decision-making. Internal states supporting awareness reports, unlike those covarying with perceptual contents, are simple and abstract, varying along a 1D continuum from absent to present. A critical feature of this architecture is that it is both higher-order and asymmetric: a vast number of perceptual states is nested under 'present', but a much smaller number of possible states nested under 'absent'. Via simulations, I show that this asymmetry provides a natural account of observations of 'global ignition' in brain imaging studies of awareness reports.