From these results, it is clear that people are using face information to modify their wagering decisions in a competitive task. These results can be easily framed within a Bayesian interpretation 
and are related to ideas in Bayesian explaining away. Since an opponent's ‘style’ is a hidden state, participants must estimate it through observable variables. For example, a Bayesian estimator could assume that an opponent is random (i.e., they bet uniformly across hand value) until information to the contrary is acquired. In our experiment, the only information participants have available about their opponent's style is the trustworthiness expressed by their face. If people are using beliefs that trustworthy opponents tend to bet with high-value hands, then they should fold more frequently than against a random opponent. Indeed, participants' observed changes in betting behavior () are in agreement with this interpretation. If feedback about outcomes or information about an opponent's hand (e.g., during a showdown) were available, a Bayesian estimator would use this information to update its beliefs about the opponent, forming a posterior estimate to use for the next hand. This predicts that face information should carry greater weight for betting behavior when there is little or no additional data about an opponent available (e.g., our experiment) or with extremely noisy opponent data (e.g., novice who doesn't know how to interpret this information). It is also worth noting that even though the relative increase in errors (~3%) against trustworthy opponents seems small (), the average return on investment for the most elite online poker players is only 6.8% 
. Therefore, an increase in mistakes of this magnitude could lead to significant decreases in a player's earnings over time.
Another interpretation of this data is that people are acting irrationally by becoming more loss averse against trustworthy appearing opponents. This possibility is evidenced by increases in people's loss aversion parameters as estimated by the softmax utility model (). Although distinguishing between the rational (Bayesian) interpretation and the irrational (utility) interpretation is an important and interesting question, this experiment is unable to discriminate between the two alternatives. It is apparent that people are adjusting their wagering behavior against opponents whose faces correlate with trustworthiness, although the reason for this change in behavior is unclear. Future studies will more directly explore this distinction.
Although the faces used in this experiment are thought to optimally predict subjective ratings of trustworthiness, it is also known that impressions of trust are deeply related to other attributes, such as perceived happiness, dominance, competence, etc. 
. To investigate the possible role of these attributes, we conducted an independent rating task (Materials S1
; Figure S1
) using a different group of subjects and correlated these results with the wagering behavior observed in this study (Materials S1
). The results demonstrate that the impressions of trustworthiness also influence impressions of many other attributes that correlate with wagering decisions. Therefore, a more general conclusion is that common avoidance cues (dominant, angry, masculine) lead to more aggressive wagering decisions (i.e., increased calling), whereas approach cues (happy, friendly, trustworthy, attractive) tend to lead to conservative wagering decisions (i.e., increased folding). Although this seems contrary to evolutionary predictions, it is rational within the context of poker since approach cues may suggest the opponent has a good hand and/or is less likely to bluff. This interpretation is supported by the fact that subjects were more likely to call against opponents who were perceived to frequently bluff, and these opponents have similar subjective impression rating trends as those who are high on avoidance dimensions (See Figure S1
The increased influence of trustworthiness on reaction time () and correct decisions () around the optimal decision boundary suggests that people are using face information most for medium-value hands. This could be explained by optimal data fusion 
, which states that the more uncertainty people have about the value of their hand, the more they should weigh face information when making a betting decision. Since participants in our experiment were novices (12 of 14 play less than 10 hours/year), they may have a more reliable estimate of high-value hands since those tend to be more salient/memorable (e.g., face cards, aces, pairs, etc.) than medium- and low-value hands. Indeed, participants in our study took significantly longer to react to hands in the optimal fold region (), and also made significantly more mistakes for medium- and low-value hands (), supporting this notion.
It is also interesting that all of the changes in wagering decisions were observed against trustworthy opponents, while untrustworthy opponents did not yield any significant results. This asymmetry is even more fascinating given that people's perception of trustworthiness is more sensitive to changes between untrustworthy and neutral faces, than between neutral and trustworthy faces 
. One possible explanation stems from the assumption that people use a random opponent decision criterion in this task, unless there is information that an opponent is betting with non-random hands. In this respect, neutral and untrustworthy faces are functionally the same: neutral faces do not provide information about an opponent's style, while untrustworthy faces may suggest that opponents are betting with poor hands. However, if participants are already assuming opponents bet randomly, they cannot decrease their criterion any further. In agreement with this proposal, shows that the inflection point for the neutral (Green) and untrustworthy (Red) curves is very close to the optimal decision boundary for a random opponent. However, trustworthy faces may provide information that the opponent has a high-value hand, leading to the observed shift towards more conservative wagering behavior.
Another direction of future research will investigate if changes in people's wagering decisions against trustworthy opponents resulted from an explicit strategy, or an implicit reaction to the faces. Although we have been interpreting the results with respect to normative decision theory, research has also demonstrated that impressions of trust can occur extremely rapidly 
, and that implicit information can also modify brain activity and behavior 
. In fact, research has also shown that loss aversion is tightly related to emotional arousal 
, suggesting the loss aversion observed against trustworthy opponents () could be an implicit reaction. Therefore, future research will explore if these changes in wagering decisions are a conscious strategy or an automatic response.
In conclusion, we have shown that rapid impressions of opponents modify wagering decisions in a zero-sum game with hidden (opponent) information. Interestingly, contrary to the popular belief that the optimal poker face is neutral in appearance, the face that invokes the most betting mistakes by our subjects is has attributes that are correlated with trustworthiness. This suggests that poker players who bluff frequently may actually benefit from appearing trustworthy, since the natural tendency seems to be inferring that a trustworthy-looking player bluffs less. More generally, these results are important for competitive situations in which opponents have little or no experience with one another, such as the early stages of a game, or in one-shot negotiation situations among strangers where ‘first impressions’ matter.