Temporal Dynamics of Visual Attention Allocation

We often temporally prepare our attention for an upcoming event such as a starter pistol. In such cases, our attention should be properly allocated around the expected moment of the event to process relevant sensory input efficiently. In this study, we examined the dynamic changes of attention levels near the expected moment by measuring contrast sensitivity to a target that was temporally cued by a five-second countdown. We found that the overall attention level decreased rapidly after the expected moment, while it stayed relatively constant before it. Results were not consistent with the predictions of existing explanations of temporal attention such as the hazard rate or the stimulus-driven oscillations. A control experiment ruled out the possibility that the observed pattern was due to biased time perception. In a further experiment with a wider range of cue-stimulus-intervals, we observed that attention level increased until the last 500 ms of the interval range, and thereafter, started to decrease. Based on the performances of a generative computational model, we suggest that our results reflect the nature of temporal attention that takes into account the subjectively estimated hazard rate and the probability of relevant events occurring in the near future

Neural computations underpinning the strategic management of influence in advice giving

Research on social influence has focused mainly on the target of influence (e.g., consumer and voter); thus, the cognitive and neurobiological underpinnings of the source of the influence (e.g., politicians and salesmen) remain unknown. Here, in a three-sided advice-giving game, two advisers competed to influence a client by modulating their own confidence in their advice about which lottery the client should choose. We report that advisers’ strategy depends on their level of influence on the client and their merit relative to one another. Moreover, blood-oxygenation-level-dependent (BOLD) signal in the temporo-parietal junction is modulated by adviser’s current level of influence on the client, and relative merit prediction error affects activity in medial-prefrontal cortex. Both types of social information modulate ventral striatum response. By demonstrating what happens in our mind and brain when we try to influence others, these results begin to explain the biological mechanisms that shape inter-individual differences in social conduct

Physiological Correlates of Volunteering

We review research on physiological correlates of volunteering, a neglected but promising research field. Some of these correlates seem to be causal factors influencing volunteering. Volunteers tend to have better physical health, both self-reported and expert-assessed, better mental health, and perform better on cognitive tasks. Research thus far has rarely examined neurological, neurochemical, hormonal, and genetic correlates of volunteering to any significant extent, especially controlling for other factors as potential confounds. Evolutionary theory and behavioral genetic research suggest the importance of such physiological factors in humans. Basically, many aspects of social relationships and social activities have effects on health (e.g., Newman and Roberts 2013; Uchino 2004), as the widely used biopsychosocial (BPS) model suggests (Institute of Medicine 2001). Studies of formal volunteering (FV), charitable giving, and altruistic behavior suggest that physiological characteristics are related to volunteering, including specific genes (such as oxytocin receptor [OXTR] genes, Arginine vasopressin receptor [AVPR] genes, dopamine D4 receptor [DRD4] genes, and 5-HTTLPR). We recommend that future research on physiological factors be extended to non-Western populations, focusing specifically on volunteering, and differentiating between different forms and types of volunteering and civic participation

Studying the long-term dynamics of reciprocity based on welfare tradeoff ratios

People reciprocate another person’s altruistic or spiteful intentions toward themselves over repeated interactions, but it is unclear how such other-regarding intentions are represented in people’s minds and how the dynamics of reciprocity unfold. Recent work formalizes other-regarding intentions as welfare tradeoff ratios (WTR) and demonstrates that people reciprocate by adjusting their own WTR in response to the perceived WTR of another person. However, due to the complexity and inaccuracy of existing WTR measurements, it is still infeasible to study the long-term dynamics of people’s WTR adjustment beyond a few trials. Here we develop an experimental paradigm based on nonlinear continuous decomposed games that precisely reveals to the participant the opponent's WTR and measures the participant’s WTR in a single trial. We find that participants are sensitive to the opponent’s WTR and adjust their WTR accordingly. This experimental framework enables the fine-grained investigation of the long-term dynamics of people’s intention-based reciprocity

Risk-taking in adversarial games: What can 1 billion online chess games tell us?

Humans are social beings, and most of our decisions are influenced by considerations of how others will respond. Whether in poker or political negotiations, the riskiness of a decision is often determined by the variance of the other party's possible responses. Such socially-contingent decisions can be framed in terms of adversarial games, which differ from other risky situations such as lotteries because the risk arises from uncertainty about the opponent's decisions, and not some independent stochasticity in the world. We use chess as a lens through which we can study human risk-taking behavior in adversarial decision making. We develop a novel algorithm for calculating the riskiness of each move in a chess game, and apply it to data from over 1 billion online chess games. We find that players not only exhibit state-dependent risk preferences, but also change their risk-taking strategy depending on their opponent, and that this effect differs in experts and novices

Blame the Player and the Game

How do people assign credit for others’ actions? The Correspondence Bias — a classic bias in social psychology — purports that people are predisposed to attribute behaviors to dispositional, rather than situational, factors. However, recent work suggests that the pattern of data cited as evidence of a bias may be a natural consequence of attribution under uncertainty. Here we devise a novel “Bucket-Toss” task in which we can independently and parametrically manipulate and measure situation and disposition pressures to evaluate whether attribution to dispositions and situations are consistent with probabilistic inference. We find that as the strength of the situation or disposition is varied, attributions to the other (unobserved) cause follow roughly symmetric patterns of graded attribution. Together, these results confirm that social attribution appears to be largely consistent with unbiased inference under uncertainty

Blame the Player and the Game

How do people assign credit for others’ actions? The Correspondence Bias — a classic bias in social psychology — purports that people are predisposed to attribute behaviors to dispositional, rather than situational, factors. However, recent work suggests that the pattern of data cited as evidence of a bias may be a natural consequence of attribution under uncertainty. Here we devise a novel “Bucket-Toss” task in which we can independently and parametrically manipulate and measure situation and disposition pressures to evaluate whether attribution to dispositions and situations are consistent with probabilistic inference. We find that as the strength of the situation or disposition is varied, attributions to the other (unobserved) cause follow roughly symmetric patterns of graded attribution. Together, these results confirm that social attribution appears to be largely consistent with unbiased inference under uncertainty

Humans fail to outwit adaptive rock, paper, scissors opponents

How do humans adapt when others exploit patterns in their behavior? When can people modify such patterns and when are they simply trapped? The present work explores these questions using the children's game of rock, paper, scissors (RPS). Adult participants played 300 rounds of RPS against one of eight bot opponents. The bots chose a move each round by exploiting unique sequential regularities in participant move choices. In order to avoid losing against their bot opponent, participants needed to recognize the ways in which their own behavior was predictable and disrupt the pattern. We find that for simple biases, participants were able to recognize that they were being exploited and even counter-exploit their opponents. However, for more complex sequential dependencies, participants were unable to change their behavior and lost reliably to the bots. Results provide a quantitative delineation of people's ability to identify and alter patterns in their past decisions

Inferring truth from lies

How much information can people gain from being lied to? We propose that people can infer the truth from false messages if two preconditions are met: (1) bigger lies are more costly, and (2) speakers have known, directional deception goals. We tested this with a marble-flipping task in which a judge tried to accurately estimate the number of sampled marbles, while a sender attempted to make the judge over- or underestimate. The sender could produce larger lies about the number of marbles drawn by physically clicking marbles along a lower or higher cost function. We found that judges took into consideration both the senders' goals and costs to correct for bias introduced by senders' lies. Our paradigm allows us to show that a large amount of the variation can be explained by people correcting others' lies based on the lies that they themselves would produce

Lies are crafted to the audience

Do people cater their lies to their own beliefs or others' beliefs? One dominant individual-based account considers lying to be an internal tradeoff between self-interest, norms, and morals. However, recent audience-based accounts suggests that lying behavior can be better explained within a communicative framework, wherein speakers consider others' beliefs to design plausible lies---highlighting the role of theory-of-mind in strategic lying. We tease apart these accounts by examining human lying behavior in a novel asymmetric, dyadic lying game in which speakers' beliefs differ from those they ascribe to their audience. We compare participants' average reported lie (controlling for the truth) across conditions that manipulated the player's and the audience's beliefs. We find that people spontaneously tune their lies to beliefs unique to their audience, more than to their own beliefs. These results support the audience-based account of lying: estimates of how listeners will respond determine how people decide to lie