| Literature DB >> 35715450 |
Gabriele Bellucci1,2,3, Thomas F Münte4,5, Soyoung Q Park6,7,8,9.
Abstract
In many instances in life, our decisions' outcomes hinge on someone else's choices (i.e., under social uncertainty). Behavioral and pharmacological work has previously focused on different types of uncertainty, such as risk and ambiguity, but not so much on risk behaviors under social uncertainty. Here, in two different studies using a double-blind, placebo-controlled, within-subject design, we administrated citalopram (a selective-serotonin-reuptake inhibitor) to male participants and investigated decisions in a gambling task under social and nonsocial uncertainty. In the social condition, gamble outcomes were determined by another participant. In the nonsocial condition, gamble outcomes were determined by a coin toss. We observed increased gamble acceptance under social uncertainty, especially for gambles with lower gains and higher losses, which might be indicative of a positivity bias in social expectations in conditions of high uncertainty about others' behaviors. A similar effect was found for citalopram, which increased overall acceptance behavior for gambles irrespective of the source of uncertainty (social/nonsocial). These results provide insights into the cognitive and neurochemical processes underlying decisions under social uncertainty, with implications for research in risk-taking behaviors in healthy and clinical populations.Entities:
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Year: 2022 PMID: 35715450 PMCID: PMC9205937 DOI: 10.1038/s41598-022-13778-x
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.996
Figure 1Behavioral paradigm. Timeline of the behavioral paradigm. Participants had to decide whether to accept or reject a gamble with depicted gains and losses. Determination of current gamble’s outcomes was depicted above the gamble. A coin-tossing hand indicated that the gamble’s outcome was decided by the participant with a coin toss (nonsocial condition). A manikin indicated that the gamble’s outcome was decided by another participant (social condition).
Mixed-effects Bayesian regression model.
| Regressors | Study1 | Study 2 |
|---|---|---|
| Intercept | − 1.88 (2.25) | − 2.00 (0.32)* |
| Treatment (Tr) | 0.62 (0.13)* | 0.46 (0.07)* |
| Social condition (S) | 0.35 (0.13)* | 0.22 (0.07)* |
| Value difference (VD) | 0.30 (0.01)* | 0.30 (0.01)* |
| Tr * S | − 0.12 (0.17) | − 0.03 (0.1)* |
| Tr * VD | − 0.02 (0.01)* | − 0.03 (0.01)* |
| S * VD | − 0.03 (0.01)* | − 0.04 (0.01)* |
| VD * S *Tr | 0.003 (0.02) | 0.01 (0.01) |
| Age | − 0.04 (0.09) | − 0.01 (0.02) |
Point posterior parameter estimates (mean) and posterior parameter estimate uncertainty (standard deviation) for the Bayesian mixed-effects logistic regressions of the two studies. Treatment (Tr) codes for the citalopram (1) and placebo (0) session. Social condition (S) codes for the social (1) and nonsocial (0) contexts. VD = difference of the gamble’s values.
*Posterior parameter estimates for which the 89% highest density interval does not include zero.
Figure 2Effects of social uncertainty and serotonin on acceptance behavior. (A) Under social uncertainty, participants were more likely to accept a gamble of smaller and negative value differences in Study 1 and Study 2. P(Accept) is the probability of accepting a gamble. (B) Citalopram administration increased the likelihood of gamble acceptance especially for smaller value differences in Study 1 and Study 2. (C) Average acceptance and rejection behavior for citalopram and placebo.
Figure 3Greater acceptance of gambles of smaller outcome values under serotonin. Gambles with lower outcome value differences were on average more likely to be accepted after citalopram administration as compared to placebo. P(Accept) is the probability of accepting a gamble in Study 1 (above) and Study 2 (below).