UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Psychopathy-related traits and the use of reward and social information: a computational approach.

Brazil, IA; Hunt, LT; Bulten, BH; Kessels, RP; de Bruijn, ER; Mars, RB; (2013) Psychopathy-related traits and the use of reward and social information: a computational approach. Front Psychol , 4 , Article 952. 10.3389/fpsyg.2013.00952. Green open access

[thumbnail of fpsyg-04-00952.pdf]
Preview
PDF
fpsyg-04-00952.pdf

Download (1MB)

Abstract

Psychopathy is often linked to disturbed reinforcement-guided adaptation of behavior in both clinical and non-clinical populations. Recent work suggests that these disturbances might be due to a deficit in actively using information to guide changes in behavior. However, how much information is actually used to guide behavior is difficult to observe directly. Therefore, we used a computational model to estimate the use of information during learning. Thirty-six female subjects were recruited based on their total scores on the Psychopathic Personality Inventory (PPI), a self-report psychopathy list, and performed a task involving simultaneous learning of reward-based and social information. A Bayesian reinforcement-learning model was used to parameterize the use of each source of information during learning. Subsequently, we used the subscales of the PPI to assess psychopathy-related traits, and the traits that were strongly related to the model's parameters were isolated through a formal variable selection procedure. Finally, we assessed how these covaried with model parameters. We succeeded in isolating key personality traits believed to be relevant for psychopathy that can be related to model-based descriptions of subject behavior. Use of reward-history information was negatively related to levels of trait anxiety and fearlessness, whereas use of social advice decreased as the perceived ability to manipulate others and lack of anxiety increased. These results corroborate previous findings suggesting that sub-optimal use of different types of information might be implicated in psychopathy. They also further highlight the importance of considering the potential of computational modeling to understand the role of latent variables, such as the weight people give to various sources of information during goal-directed behavior, when conducting research on psychopathy-related traits and in the field of forensic psychiatry.

Type: Article
Title: Psychopathy-related traits and the use of reward and social information: a computational approach.
Location: Switzerland
Open access status: An open access version is available from UCL Discovery
DOI: 10.3389/fpsyg.2013.00952
Publisher version: http://dx.doi.org/10.3389/fpsyg.2013.00952
Language: English
Additional information: © 2013 Brazil, Hunt, Bulten, Kessels, de Bruijn and Mars. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. PMCID: PMC3868018
Keywords: associative learning, computational modeling, individual differences, personality traits, psychopathic traits, psychopathy, reinforcement learning, social learning
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
URI: https://discovery.ucl.ac.uk/id/eprint/1417738
Downloads since deposit
93Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item