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Psychopathic personality tendencies and electrophysiological correlates social vs reward-based decision-making

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Driessen, J.M.A. (Josi);Diaconescu, A.O.;Buitelaar, J.K.;Kessels, R.P.C. (Roy);Glennon, J.C.;Brazil, I.A. (Inti)

Description

Individuals who are characterized by elevated levels of psychopathic traits tend to consistently violate social norms and seek personal gains. Previous studies in offender and non-offender samples have indicated that such behaviors could be caused by impairments in associative learning. In order for associative learning to be successful, we need to constantly monitor the relationship between events and their outcomes and adapt our behavior in response to changes in these event-outcome contingencies. Recent advances in computational modelling approaches offer insight into the unobservable computational processes that are thought to be required for associative learning. In the present study, we used such a model to investigate the associations between psychopathic traits in a non-offender sample and the cognitive computations underlying adaptive behavior during associative learning. We also investigated the potential engagement of adaptive control processes by measuring oscillatory theta activity in the prefrontal cortex. Participants performed a reinforcement learning task in which the trade-off between using social and non-social information affected task performance and the associated monetary reward for the participant. The findings indicated that increasing levels of psychopathic traits co-occurred with larger impairments in learning from social information, and suggested that antisocial traits were linked to a reduced ability to track changes in the trustworthiness of social advice over time. These impairments did not relate to a preference for one of the information sources, and the decreased task performance did not affect the risk that was taken in order to obtain a high reward. Furthermore, it was found that decreased theta power was linked to higher levels of psychopathic traits, which aligns with indications that theta is involved in tracking the volatility of social information. This is the first study that provides support for a relationship between associative learning, theta power, and psychopathic traits and contributes to our understanding of the underlying associative learning mechanisms that cause low responsivity towards current treatment interventions in those with psychopathy.

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Metrics

Dataset Index

0.4

FAIR Score

81%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Radboud University

License

Restricted Access

Radboud University - Human Data 1.1

Assigned Domain

Subfield

Cardiology and Cardiovascular Medicine

Field

Medicine

Domain

Health Sciences

Confidence Score

58%

Source

Open Alex

Keywords

psychopathy, associative learning, social learning, computational modelling, theta power

Normalization Factors

FT

63.46

CTw

1.00

MTw

1.00