Doubting what you already know: Uncertainty regarding state transitions is associated with obsessive compulsive symptoms

Isaac Fradkin, Casimir Ludwig, Eran Eldar and Jonathan D Huppert

PLOS Computational Biology, 2020, vol. 16, issue 2, 1-26

Abstract: Obsessive compulsive (OC) symptoms involve excessive information gathering (e.g., checking, reassurance-seeking), and uncertainty about possible, often catastrophic, future events. Here we propose that these phenomena are the result of excessive uncertainty regarding state transitions (transition uncertainty): a computational impairment in Bayesian inference leading to a reduced ability to use the past to predict the present and future, and to oversensitivity to feedback (i.e. prediction errors). Using a computational model of Bayesian learning under uncertainty in a reversal learning task, we investigate the relationship between OC symptoms and transition uncertainty. Individuals high and low in OC symptoms performed a task in which they had to detect shifts (i.e. transitions) in cue-outcome contingencies. Modeling subjects’ choices was used to estimate each individual participant’s transition uncertainty and associated responses to feedback. We examined both an optimal observer model and an approximate Bayesian model in which participants were assumed to attend (and learn about) only one of several cues on each trial. Results suggested the participants were more likely to distribute attention across cues, in accordance with the optimal observer model. As hypothesized, participants with higher OC symptoms exhibited increased transition uncertainty, as well as a pattern of behavior potentially indicative of a difficulty in relying on learned contingencies, with no evidence for perseverative behavior. Increased transition uncertainty compromised these individuals' ability to predict ensuing feedback, rendering them more surprised by expected outcomes. However, no evidence for excessive belief updating was found. These results highlight a potential computational basis for OC symptoms and obsessive compulsive disorder (OCD). The fact the OC symptoms predicted a decreased reliance on the past rather than perseveration challenges preconceptions of OCD as a disorder of inflexibility. Our results have implications for the understanding of the neurocognitive processes leading to excessive uncertainty and distrust of past experiences in OCD.Author summary: Obsessive compulsive (OC) symptoms involve excessive information gathering (e.g., checking, reassurance seeking), and excessive uncertainty about possible future events. Normally, people can use prior experience to predict present and future events. Here we suggest that OC symptoms can be traced back to an impairment in this prediction mechanism. In Bayesian models of learning and decision making the relative weight given to prior experience depends on the estimation of uncertainty. Particularly, when one believes that past states cannot predict the future with certainty, the optimal behavior is to assign a higher weight to current feedback at the expense of prior experience. We examined this mechanism, using a task that required participants to learn cue-outcome contingencies from feedback, while considering the possibility that occasional changes in the contingencies render past experience irrelevant. A computational analysis of participants' behavior showed that participants with higher OC symptoms indeed assigned lower weight to prior experience, leading to over-exploratory behavior. These results have implications for the understanding of the neurocognitive processes leading to excessive uncertainty and distrust of past experiences in obsessive compulsive disorder.

Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007634 (text/html)
https://journals.plos.org/ploscompbiol/article/fil ... 07634&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1007634

DOI: 10.1371/journal.pcbi.1007634

Access Statistics for this article

More articles in PLOS Computational Biology from Public Library of Science
Bibliographic data for series maintained by ploscompbiol ().