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The Predictive Dynamics of Happiness and Well-Being

Miller, Mark and Rietveld, Erik and Kiverstein, Julian (2021) The Predictive Dynamics of Happiness and Well-Being. [Preprint]

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Abstract

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.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Miller, Markmarkmiller@chain.hokudai.ac.jp
Rietveld, Erikd.w.rietveld@amsterdamumc.nl
Kiverstein, Julianj.d.kiverstein@amsterdamumc.nl
Keywords: predictive processing, error dynamics, valence, happiness, reward, well-being
Subjects: Specific Sciences > Cognitive Science
General Issues > Philosophers of Science
Specific Sciences > Psychology
Depositing User: Prof. Mark Miller
Date Deposited: 07 Jul 2021 14:04
Last Modified: 07 Jul 2021 14:04
Item ID: 19282
Subjects: Specific Sciences > Cognitive Science
General Issues > Philosophers of Science
Specific Sciences > Psychology
Date: 6 July 2021
URI: http://philsci-archive.pitt.edu/id/eprint/19282

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