The Predictive Dynamics of Happiness and Well-Being

Mark Miller*, Julian Kiverstein, Erik Rietveld

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

20 Citations (Scopus)
80 Downloads (Pure)


We offer an account of mental health and well-being using the predictive processing framework (PPF). According to this framework, the difference between mental health and psychopathology can be located in the goodness of the predictive model as a regulator of action. What is crucial for avoiding the rigid patterns of thinking, feeling and acting associated with psychopathology is the regulation of action based on the valence of affective states. In PPF, valence is modelled as error dynamics—the change in prediction errors over time. Our aim in this paper is to show how error dynamics can account for both momentary happiness and longer term well-being. What will emerge is a new neurocomputational framework for making sense of human flourishing.

Original languageEnglish
Pages (from-to)15-30
Number of pages16
JournalEmotion Review
Issue number1
Publication statusPublished - 1 Jan 2022


  • error dynamics
  • predictive processing
  • valence
  • well-being


Dive into the research topics of 'The Predictive Dynamics of Happiness and Well-Being'. Together they form a unique fingerprint.

Cite this