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Dryad

Data from: Testosterone eliminates strategic prosocial behavior in healthy males

Cite this dataset

Kutlikova, Hana; Zhang, Lei; van Honk, Jack; Lamm, Claus (2022). Data from: Testosterone eliminates strategic prosocial behavior in healthy males [Dataset]. Dryad. https://doi.org/10.5061/dryad.866t1g1t1

Abstract

Humans are strategically more prosocial when their actions are being watched by others than when they act alone. Using a psychopharmacogenetic approach, we investigated the computational and endocrinological mechanisms of such audience-driven prosociality. 187 male participants received either a single dose of testosterone or a placebo and performed a prosocial and self-benefitting reinforcement learning task. Crucially, the task was performed either in private or when being watched. Rival theories suggest that the hormone might either diminish or strengthen audience-depended generosity. We show that exogenous testosterone fully eliminated strategic, i.e., feigned, generosity and thus decreased submission to audience expectations. We performed reinforcement-learning drift-diffusion computational modeling to elucidate which latent aspects of decision-making testosterone acted on. The modeling revealed that testosterone compared to placebo did not deteriorate reinforcement learning per se, rather, when being watched, the hormone altered the degree to which the learned information on choice value translated to action selection. This indicates that when being watched, the hormone was influencing participants towards choices that are less optimal for prosociality, which resulted in nonconforming behavior. Indeed, exploratory personal values analysis suggests that the effect of testosterone in our reinforcement learning task is underpinned by a shift from socially conforming to nonconforming decisions. Together, these results indicate that instead of deceptively increasing socially desirable behavior, testosterone - by acting on situational personal values - counteracts submission to audience expectations, despite plausible reputational costs.

Methods

Data from a prosocial reinforcement learning task, programmed in PsychoPy.

Funding

Vienna Science and Technology Fund