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What is mood? A computational perspective

Clark, JE; Watson, S; Friston, KJ; (2018) What is mood? A computational perspective. Psychological Medicine 10.1017/S0033291718000430. (In press). Green open access

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Abstract

The neurobiological understanding of mood, and by extension mood disorders, remains elusive despite decades of research implicating several neuromodulator systems. This review considers a new approach based on existing theories of functional brain organisation. The free energy principle (a.k.a. active inference), and its instantiation in the Bayesian brain, offers a complete and simple formulation of mood. It has been proposed that emotions reflect the precision of – or certainty about – the predicted sensorimotor/interoceptive consequences of action. By extending this reasoning, in a hierarchical setting, we suggest mood states act as (hyper) priors over uncertainty (i.e. emotions). Here, we consider the same computational pathology in the proprioceptive and interoceptive (behavioural and autonomic) domain in order to furnish an explanation for mood disorders. This formulation reconciles several strands of research at multiple levels of enquiry.

Type: Article
Title: What is mood? A computational perspective
Open access status: An open access version is available from UCL Discovery
DOI: 10.1017/S0033291718000430
Publisher version: http://dx.doi.org/10.1017/S0033291718000430
Language: English
Additional information: © Cambridge University Press 2018 This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
URI: http://discovery.ucl.ac.uk/id/eprint/10048537
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