The personality trait of behavioral inhibition modulates perceptions of moral character and performance during the trust game: behavioral results and computational modeling

Abstract

Decisions based on trust are critical for human social interaction. We judge the trustworthiness of partners in social interactions based on a number of partner characteristics as well as experiences with those partners. These decisions are also influenced by personality. The current study examined how the personality trait of behavioral inhibition, which involves the tendency to avoid or withdraw from novelty in both social and non-social situations, is related to explicit ratings of trustworthiness as well as decisions made in the trust game. In the game, healthy young adults interacted with three fictional partners who were portrayed as trustworthy, untrustworthy or neutral through biographical information. Participants could choose to keep $1 or send $3 of virtual money to a partner. The partner could then choose to send $1.5 back to the participant or to keep the entire amount. On any trial in which the participant chose to send, the partner always reciprocated with 50% probability, irrespective of how that partner was portrayed in the biography. Behavioral inhibition was assessed through a self-report questionnaire. Finally, a reinforcement learning computational model was fit to the behavior of each participant. Self-reported ratings of trust confirmed that all participants, irrespective of behavioral inhibition, perceived differences in the moral character of the three partners (trustworthiness of good > neutral > bad partner). Decisions made in the game showed that inhibited participants tended to trust the neutral partner less than uninhibited participants. In contrast, this was not reflected in the ratings of the neutral partner (either pre- or post-game), indicating a dissociation between ratings of trustworthiness and decisions made by inhibited participants. Computational modeling showed that this was due to lower initial trust of the neutral partner rather than a higher learning rate associated with loss, suggesting an implicit bias against the neutral partner. Overall, the results suggest inhibited individuals may be predisposed to interpret neutral or ambiguous information more negatively which could, at least in part, account for the tendency to avoid unfamiliar people characteristic of behaviorally inhibited temperament, as well as its relationship to anxiety disorders.

Inhibited Personality Temperaments Translated Through Enhanced Avoidance and Associative Learning Increase Vulnerability for PTSD

“…One factor that may help account for the gender differences in PTSD rates may be an interaction with personality temperaments such as BI. Women outscore men on the AMBI in some studies (Gladstone and Parker, 2005; Radell et al., 2016), but not all (Myers et al., 2012a; Allen et al., 2017). The failure to find a clear sex difference could be due to variability in expression of a personality factor (or other vulnerability).…”

The Personality Trait of Intolerance to Uncertainty Affects Behavior in a Novel Computer-Based Conditioned Place Preference Task

“…In addition to these findings with basic classical conditioning and avoidance learning, the effects of personality factors have been examined with computer-based tasks involving economic decision making. For example, Radell et al (2016) used a cognitive economic decision making task based on socials interactions (i.e., the trust game) with behaviorally inhibited individuals. This task, based on the version used by Delgado et al (2005) , had participants read the biographies of partners in the game that portrayed them as morally trustworthy (“good partner”), untrustworthy (“bad partner”), or neutral (“neutral partner”).…”

“…In the computer avoidance task ( Sheynin et al, 2014 ), participants were given no instructions and had to learn, through trial-and-error, what behavior resulted in avoiding point loss. In the trust game ( Radell et al, 2016 ), all partners shared 50% of the time regardless of the nature of their biographies but individuals with anxiety vulnerability only differed in how they treated the neutral partner. The probabilistic category learning task ( Myers et al, 2016 ) involved uncertainty in that it was not possible to be correct 100% of the time based on the probabilistic nature of the categories.…”

Memory, Interrupted: A Retrieval Model of Intrusive Memories, Recovery Trajectories, and Neurobiological Effects in Post-Traumatic Stress Disorder

“…For example, Myers et al (2013) developed an RL model with separate mechanisms for rewards and losses, and showed that performance of PTSD participants in a probabilistic decision-making task, could be modeled as a consequence of abnormally large reward values ascribed to neutral trials. A related model (Radell et al, 2016) showed similar results in groups of participants with the personality trait of COMPUTATIONAL MODEL OF INTRUSIVE MEMORIES behavioral inhibition, typically marked by higher anxiety and avoidance behavior. Individuals with high behavioral inhibition showed higher reward values assigned to neutral faces in a trust task than individuals with lower inhibition.…”

“…As noted above, the biological mechanisms of PTSD are typically understood through the lens of the fear conditioning and extinction literature. In computational models, conditioning and extinction are captured through Reinforcement Learning (Sutton & Barto, 1998), a formal theory of how agents learn to select different actions based on environmental feedback (Myers et al, 2013;Radell et al, 2015Radell et al, , 2016Radell et al, 2017;Sheynin et al, 2015). For example, Myers et al (2013) developed an RL model with separate mechanisms for rewards and losses, and showed that performance of PTSD participants in a probabilistic decision-making task, could be modeled as a consequence of abnormally large reward values ascribed to neutral trials.…”