The Pruning of Decision Trees: Healthy vs. Depressed Individuals
Real-life decisions are often complex because they involve making sequential choices that constrain future options. In order to render multi-step decisions manageable, people ‘prune’ from consideration branches of decision trees that contain negative outcomes. We have previously theorised (Huys et al., 2012; 2015a; 2015b; Lally et al., 2017) that sub-optimal pruning contributes to depression by promoting an oversampling of branches that result in unsavoury outcomes, which results in a negatively-biased valuation of the world.
To assess this theory, we administered to depressed and non-depressed individuals a sequential reinforcement-based decision-making task to determine pruning behaviours.
While results showed that participants did indeed prune branches of decision trees that began with large losses regardless of the potential utility of those branches, there was no group difference in pruning behaviours; nor was there a significant relationship between pruning and magnitude of depression/anxiety. Whilst these data provide no evidence for sup-optimal pruning in depressed patients, future research could determine whether maladaptive pruning behaviours are observable in specific sub-groups of depressed patients (i.e. in treatment resistant individuals), or whether misuse of other heuristics may contribute to depression.
Published Work:
Faulkner P, Huys Q, Renz D, Eshel N, Pilling S, Dayan P & Roiser JP (2021) A Comparison of ‘Pruning’ During Multi-Step Planning in Depressed and Healthy Individuals Psychological Medicine
Lally N, Huys QJ, M Eshel N, Faulkner P, Dayan P & Roiser JP (2017) The Neural Basis of Aversive Pavlovian Guidance During Planning Journal of Neuroscience
Huys QJM, Lally N, Faulkner P, Seifritz E, Gershman SJ, Dayan P & Roiser JP (2015) The Interplay of Approximate Planning Strategies Proceedings of the National Academy of Sciences of the United States of America (PNAS)