Disentangling choice value and choice conflict in sequential decisions under risk

People Place Larger Bets When Risky Choices Provide a Postbet Option to Cash Out

After a risky choice, decision makers must frequently wait out a delay period before the outcome of their choice becomes known. In contemporary sports-betting apps, decision makers can "cash out" of their bet during this delay period by accepting a discounted immediate payout. An important open question is how availability of a postchoice cash-out option alters choice. We investigated this question using a novel gambling task that incorporated a cash-out option during the delay between bet and outcome. Across two experiments (N = 240 adults, recruited via Prolific), cash-out availability increased participants' bet amounts by up to 35%. Participants who were more likely to cash out when odds deteriorated were less likely to cash out when odds improved. Furthermore, the effect of cash-out availability on bet amounts was positively correlated with individual differences in cash-out propensity for bets with deteriorating odds only. These results suggest that cash-out availability may promote larger bets by allowing bettors to avoid losing their entire stake.

Continuous decision to wait for a future reward is guided by fronto-hippocampal anticipatory dynamics

Deciding whether to wait for a future reward is crucial for surviving in an uncertain world. While seeking rewards, agents anticipate a reward in the present environment and constantly face a trade-off between staying in their environment or leaving it. It remains unclear, however, how humans make continuous decisions in such situations. Here, we show that anticipatory activity in the anterior prefrontal cortex, ventrolateral prefrontal cortex, and hippocampus underpins continuous stay-leave decision-making. Participants awaited real liquid rewards available after tens of seconds, and their continuous decision was tracked by dynamic brain activity associated with the anticipation of a reward. Participants stopped waiting more frequently and sooner after they experienced longer delays and received smaller rewards. When the dynamic anticipatory brain activity was enhanced in the anterior prefrontal cortex, participants remained in their current environment, but when this activity diminished, they left the environment. Moreover, while experiencing a delayed reward in a novel environment, the ventrolateral prefrontal cortex and hippocampus showed anticipatory activity. Finally, the activity in the anterior prefrontal cortex and ventrolateral prefrontal cortex was enhanced in participants adopting a leave strategy, whereas those remaining stationary showed enhanced hippocampal activity. Our results suggest that fronto-hippocampal anticipatory dynamics underlie continuous decision-making while anticipating a future reward.

Dissecting the neurocomputational bases of patch-switching

The survival and well-being of humans require solving the patch-switching problem: we must decide when to stop collecting rewards in a current patch and travel somewhere else where gains may be higher. Previous studies suggested that frontal regions are underpinned by several processes in the context of foraging decisions such as tracking task difficulty, and/or the value of exploring the environment. To dissociate between these processes, participants completed an fMRI patch-switching learning task inspired by behavioral ecology. By analyzing >11,000 trials collected across 21 participants, we found that the activation in the cingulate cortex was closely related to several patch-switching-related variables including the decision to leave the current patch, the encounter of a new patch, the harvest value, and the relative forage value. Learning-induced changes in the patch-switching threshold were tracked by activity within frontoparietal regions including the superior frontal gyrus and angular gyrus. Our findings suggest that frontoparietal regions shape patch-switching learning apart from encoding classical non-learning foraging processes. These findings provide a novel neurobiological understanding of how learning emerges neurocomputationally shaping patch-switching behavior with implications in real-life choices such as job selection and pave the way for future studies to probe the causal role of these neurobiological mechanisms.