What is mood? A computational perspective

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. acti...

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Bibliographic Details
Published in:Psychological medicine 2018-10, Vol.48 (14), p.2277-2284
Main Authors: Clark, James E, Watson, Stuart, Friston, Karl J
Format: Article
Language:English
Subjects:
Affect - physiology
Autonomic nervous system
Bayesian analysis
Brain
Brain - physiology
Brain research
Computational neuroscience
Emotional disorders
Emotions
Free energy
Humans
Models, Theoretical
Mood
Mood Disorders - physiopathology
Neurobiology
Neuromodulation
Neurosciences
Pathology
Proprioception
Review
Scholarships & fellowships
Sensorimotor system
Uncertainty
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Summary: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.
ISSN:0033-2917
1469-8978
DOI:10.1017/S0033291718000430