 Reduction in social learning and increased policy uncertainty about harmful intent is associated with pre-existing paranoid beliefs: Evidence from modelling a modified serial dictator gameJoseph M Barnby, Vaughan Bell, Mitul A Mehta and Michael Moutoussis PLOS Computational Biology, 2020, vol. 16, issue 10, 1-23 Abstract: Current computational models suggest that paranoia may be explained by stronger higher-order beliefs about others and increased sensitivity to environments. However, it is unclear whether this applies to social contexts, and whether it is specific to harmful intent attributions, the live expression of paranoia. We sought to fill this gap by fitting a computational model to data (n = 1754) from a modified serial dictator game, to explore whether pre-existing paranoia could be accounted by specific alterations to cognitive parameters characterising harmful intent attributions. We constructed a ‘Bayesian brain’ model of others’ intent, which we fitted to harmful intent and self-interest attributions made over 18 trials, across three different partners. We found that pre-existing paranoia was associated with greater uncertainty about other’s actions. It moderated the relationship between learning rates and harmful intent attributions, making harmful intent attributions less reliant on prior interactions. Overall, the magnitude of harmful intent attributions was directly related to their uncertainty, and importantly, the opposite was true for self-interest attributions. Our results explain how pre-existing paranoia may be the result of an increased need to attend to immediate experiences in determining intentional threat, at the expense of what is already known, and more broadly, they suggest that environments that induce greater probabilities of harmful intent attributions may also induce states of uncertainty, potentially as an adaptive mechanism to better detect threatening others. Importantly, we suggest that if paranoia were able to be explained exclusively by core domain-general alterations we would not observe differential parameter estimates underlying harmful-intent and self-interest attributions.Author summary: A great deal of work has tried to explain paranoia through general cognitive principles, although relatively little has tried to understand whether paranoia may be explained by specific changes to social learning processes. This question is crucial, as paranoia is inherently a social phenomenon, and requires mechanistic explanations to match with its dynamic phenomenology. In this paper we wanted to test whether pre-existing and live paranoid beliefs about others specifically altered how an individual attributed harmful intent–the live expression of paranoia–to partners over a series of live interactions. To do this we applied a novel computational model and network analysis to behavioural data from a large sample of participants in the general population that had played a modified Dictator game online, and required them to attribute whether the behaviour of their partner was due to their intent to harm, or their self-interest, on two mutually exclusive scales. Pre-existing paranoid beliefs about others reduced the value of new partner behaviours on evolving attributions of harmful intent. We suggest that both pre-existing paranoid beliefs and momentary paranoia may incur an adaptive cognitive state to better track potentially threatening others, and demonstrate phenomenological specificity associated with mechanisms of live paranoia. Date: 2020 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1008372 DOI: 10.1371/journal.pcbi.1008372 Access Statistics for this article More articles in PLOS Computational Biology from Public Library of Science |
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