Oversampled and undersolved: Depressive rumination from an active inference perspective. (November 2022)

• Record Type: Journal Article
• Authors: Berg, Max; Feldmann, Matthias; Kirchner, Lukas; Kube, Tobias
• Is Part Of: Neuroscience and biobehavioral reviews. Volume 142(2022)
• Publication Date: 2022-11
• Subjects: Rumination -- Depression -- Active inference -- Bayesian sampling -- Mental simulation -- Problem-solving; Psychophysiology -- Periodicals; Human behavior -- Periodicals; Animal behavior -- Periodicals; Neurology -- Periodicals; Behavior -- Periodicals; Ethology -- Periodicals; Neurology -- Periodicals; Psychophysiologie -- Périodiques; Comportement humain -- Périodiques; Animaux -- Mœurs et comportement -- Périodiques; Neurologie -- Périodiques; Animal behavior; Human behavior; Neurology; Psychophysiology; Periodicals; Electronic journals; 573.8
• DOI: 10.1016/j.neubiorev.2022.104873
• Languages: English
• ISSNs: 0149-7634

Abstract

Abstract: Rumination is a widely recognized cognitive deviation in depression. Despite the recognition, researchers have struggled to explain why patients cannot disengage from the process, although it depresses their mood and fails to lead to effective problem-solving. We rethink rumination as repetitive but unsuccessful problem-solving attempts. Appealing to an active inference account, we suggest that adaptive problem-solving is based on the generation, evaluation, and performance of candidate policies that increase an organism's knowledge of its environment. We argue that the problem-solving process is distorted during rumination. Specifically, rumination is understood as engaging in excessive yet unsuccessful oversampling of policy candidates that do not resolve uncertainty. Because candidates are sampled from policies that were selected in states resembling one's current state, "bad" starting points (e.g., depressed mood, physical inactivity) make the problem-solving process vulnerable for generating a ruminative „halting problem". This problem leads to high opportunity costs, learned helplessness and diminished overt behavior. Besides reviewing evidence for the conceptual paths of this model, we discuss its neurophysiological correlates and point towards clinical implications. Highlights: An active inference account of depressive rumination is presented in this review. Rumination is interpreted as repetitive Bayesian oversampling / rapid discarding of candidate policies. This explains why rumination is continued despite inducing depressed mood and failing at problem-solving. The re-interpretation of rumination has implications for the pharmacological and psychological treatment of depression.