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Towards a computational (neuro)phenomenology of mental action: modelling meta-awareness and attentional control with deep-parametric active inference

Lars Sandved-Smith, Casper Hesp, Antoine Lutz, Jérémie Mattout, Karl Friston, Maxwell James Ramstead

PsyArXiv June 10, 2020 preprint DOI: 10.31234/osf.io/5jh3c (opens in new tab)

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AI-extracted from the abstract
Characteristics Theoretical or philosophical paper
Topics Philosophy of mind
Citations 11
Key points Argues that extending active inference with a hierarchical level for explicit meta-awareness and covert attentional action yields a computational proof of principle for how access, monitoring, and control of cognitive states can emerge, illustrated through mind-wandering and its regulation in focused attention.

Abstract

Metacognition refers to the capacity to access, monitor, and control aspects of one’s mental operations and is central to the human condition and experience. Disorders of metacognition are a hallmark of many psychiatric conditions and the training of metacognitive skills is central in education and in many psychotherapies. This paper provides first steps towards the development of a formal neurophenomenology of metacognition. To do so, we leverage the tools of the active inference framework, extending a previous computational model of implicit metacognition by adding a hierarchical level to model explicit (conscious) meta-awareness and the voluntary control of attention through covert action. Using the example of mind-wandering and its regulation in focused attention, we provide a computational proof of principle for an inferential architecture apt to enable the emergence of central components of metacognition: namely, the ability to access, monitor, and control cognitive states.

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