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What is mood? A computational perspective

Lookup NU author(s): James Clark, Dr Stuart Watson



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Copyright © Cambridge University Press 2018 This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (, which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. 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.

Publication metadata

Author(s): Clark JE, Watson S, Friston KJ

Publication type: Article

Publication status: Published

Journal: Psychological Medicine

Year: 2018

Volume: 48

Issue: 14

Pages: 2277-2284

Print publication date: 01/10/2018

Online publication date: 26/02/2018

Acceptance date: 01/02/2018

Date deposited: 12/03/2018

ISSN (print): 0033-2917

ISSN (electronic): 1469-8978

Publisher: Cambridge University Press


DOI: 10.1017/S0033291718000430


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