Let's decide together: Differences between individual and joint delay discounting

Effects of individual and dyadic decision-making and normative reference on delay discounting decisions

The tendency to devaluate delayed rewards, a phenomenon referred to as ‘discounting behaviour’, has been studied by wide-ranging research examining individuals choosing between sooner but smaller or later but larger rewards. Despite the fact that many real-life choices are embedded in a social context, the question of whether or not social collaboration can have an impact on such choices has not been addressed empirically. With this research, we aimed to fill this gap experimentally by implementing a novel choice selection procedure in order to study the interactive dynamics between two participants. This selection procedure allowed us to dissect the sequence of decision-making into its elements, starting from the very first individual preference to the solution of possible conflicting preferences in the dyad. In Experiment 1, we studied group decision-making on classical intertemporal choices to reveal the possible benefit of social collaboration on discounting and identified that the knowledge of the social situation in collective decision-making causes a reduction in discounting. In a pre-registered Experiment 2, we compared classical intertemporal choices with choices in a gamified version of a discounting paradigm in which the participants had a real-time experience trial by trial and for which a normative reference was present. We found that collective decision-making had a substantial impact on intertemporal decision-making, but was shaped by different types of choices. Classical intertemporal choices were rather susceptible to the contextual factors of decision-making, whereas in the gamified version that included a normative reference the decisions were reliably influenced by social collaboration and resulted in a lower discounting. The results in this paradigm replicate our original findings from former research.

Better together? Social distance affects joint probability discounting

Deciding together is common in our everyday life. However, the process of this joint decision-making plays out across different levels, for example language, intonation, or non-verbal behaviour. Here we focused on non-verbal interaction dynamics between two participants in probability discounting. We applied a gamified decision-making task in which participants performed a series of choices between a small but safe and a large but risky reward. In two experiments, we found that joint decision-making resulted in lower discounting and higher efficiency. In order to understand the underlying mechanisms in greater detail, we studied through which process this variation occurred and whether this process would be modulated by the social distance between both participants. Our findings suggested that socially close participants managed to reduce their discounting by interactive processes while socially distant participants were influenced by the social context itself. However, a higher level of efficiency was achieved through interactive processes for both groups. In summary, this study served as a fine-grained investigation of collaborative interaction processes and its significant impact on the outcome of choices with probabilistic consequences.

The social contagion of temporal discounting in small social networks

Decisions often require a tradeoff between immediate and long-term gratification. How individuals resolve such tradeoffs reflects constructs such as temporal discounting, the degree that individuals devalue delayed rewards. Recent research has started to focus on temporal decisions made in collaborative contexts (e.g., dyads, small groups). Results suggest that directly interacting with others leads to revisions in preferences, such that decision makers become more similar to their collaborative partners over time (e.g., more patient following collaboration with a patient other). What remains to be seen is whether this social influence extends to indirect social effects, such as when an individual influences another’s preferences through a shared collaborative partner. In the current study, the focus was on decisions regarding hypothetical monetary rewards. Groups of three participated in a collaborative decision-making chain, in which network member X collaborated with member Y, who then subsequently collaborated with member Z. Though network members X and Z never directly interacted, a significant indirect link was observed between member X’s pre-collaborative decision preferences and member Z’s post-collaborative decision preferences. These results demonstrate that temporal decision preferences can be transmitted through intervening connections in a small social network (i.e., social contagion), showing that indirect social influence can be empirically observed and measured in controlled environments.

Foraging optimally in social neuroscience: computations and methodological considerations

Research in social neuroscience has increasingly begun to use the tools of computational neuroscience to better understand behaviour. Such approaches have proven fruitful for probing underlying neural mechanisms. However, little attention has been paid to how the structure of experimental tasks relates to real-world decisions, and the problems that brains have evolved to solve. To go significantly beyond current understanding, we must begin to use paradigms and mathematical models from behavioural ecology, which offer insights into the decisions animals must make successfully in order to survive. One highly influential theory-marginal value theorem (MVT)-precisely characterises and provides an optimal solution to a vital foraging decision that most species must make: the patch-leaving problem. Animals must decide when to leave collecting rewards in a current patch (location) and travel somewhere else. We propose that many questions posed in social neuroscience can be approached as patch-leaving problems. A richer understanding of the neural mechanisms underlying social behaviour will be obtained by using MVT. In this 'tools of the trade' article, we outline the patch-leaving problem, the computations of MVT and discuss the application to social neuroscience. Furthermore, we consider the practical challenges and offer solutions for designing paradigms probing patch leaving, both behaviourally and when using neuroimaging techniques.