Seizing the Opportunity: Lifespan Differences in the Effects of the Opportunity Cost of Time on Cognitive Control

Previous work suggests that lifespan developmental differences in cognitive control reflect maturational and aging-related changes in prefrontal cortex functioning. However, complementary explanations exist: It could be that children and older adults differ from younger adults in how they balance the effort of engaging in control against its potential benefits. Here we test whether the degree of cognitive effort expenditure depends on the opportunity cost of time (average reward rate per unit time): if the average reward rate is high, participants should withhold cognitive effort whereas if it is low, they should invest more. In Experiment 1, we examine this hypothesis in children, adolescents, younger, and older adults, by applying a reward rate manipulation in two cognitive control tasks: a modified Erikson Flanker and a task-switching paradigm. We found that young adults and adolescents reflexively withheld effort when the opportunity cost of time was high, whereas older adults and, to a lesser degree children, invested more resources to accumulate reward as quickly as possible. We tentatively interpret these results in terms of age- and task-specific differences in the processing of the opportunity cost of time. We qualify our findings in a second experiment in younger adults in which we address an alternative explanation of our results and show that the observed age differences in effort expenditure may not result from differences in task difficulty. To conclude, we think that our results present an interesting first step at relating opportunity costs to motivational processes across the lifespan. We frame the implications of further work in this area within a recent developmental model of resource-rationality, which points to developmental sweet spots in cognitive control.

The opportunity cost of time modulates cognitive effort

A spate of recent work demonstrates that humans seek to avoid the expenditure of cognitive effort, much like physical effort or economic resources. Less is clear, however, about the circumstances dictating how and when people decide to expend cognitive effort. Here we adopt a popular theory of opportunity costs and response vigor and to elucidate this question. This account, grounded in Reinforcement Learning, formalizes a trade-off between two costs: the harder work assumed necessary to emit faster actions and the opportunity cost inherent in acting more slowly (i.e., the delay that results to the next reward and subsequent rewards). Recent work reveals that the opportunity cost of time—operationalized as the average reward rate per unit time, theorized to be signaled by tonic dopamine levels, modulates the speed with which a person responds in a simple discrimination tasks. We extend this framework to cognitive effort in a diverse range of cognitive tasks, for which 1) the amount of cognitive effort demanded from the task varies from trial to trial and 2) the putative expenditure of cognitive effort holds measureable consequences in terms of accuracy and response time. In the domains of cognitive control, perceptual decision-making, and task-switching, we found that subjects tuned their level of effort exertion in accordance with the experienced average reward rate: when the opportunity cost of time was high, subjects made more errors and responded more quickly, which we interpret as a withdrawal of cognitive effort. That is, expenditure of cognitive effort appeared to be modulated by the opportunity cost of time. Further, and consistent with our account, the strength of this modulation was predicted by individual differences in efficacy of cognitive control. Taken together, our results elucidate the circumstances dictating how and when people expend cognitive effort.

A Neural Mechanism for the Opportunity Cost of Time

Recent interest has focused on a class of decision problems in which subjects encounter options serially and must decide when to leave an option in search of a better one, rather than directly comparing simultaneously presented options. Although such problems have a rich history in animal foraging and economics, relatively little is known about their neural substrates. Suggestively, however, a separate literature has argued that the key decision variable in these tasks – the opportunity cost of time, given by the average reward rate – may also govern behavioral vigor and may be reported by tonic dopamine (DA).In this study, we test whether this putative dopaminergic opportunity cost signal plays an analogous role in serial decisions by examining the behavior of patients with Parkinson’s disease (PD), on and off their DA replacement medication, in a patch-foraging task. In these tasks, subjects’ decisions about when to leave a depleting resource implicitly reflect their beliefs about the opportunity cost of time spent harvesting that resource. Consistent with the opportunity cost hypothesis, umedicated patients harvested longer than matched controls, and medication remediated this deficit. These effects were not explained by motor perseveration. Our results suggest a functional role for DA, and an associated cognitive deficit in PD, in a type of decision process that may be distinct from (but related to) the neuromodulator’s well studied roles in behavioral invigoration and learning from rewards.Significance StatementThis study addresses two important questions whose answers are, unexpectedly, linked. First, what is the scope of cognitive functions of the neuromodulator dopamine, whose contributions – for instance, as assessed by both the motoric and more subtle cognitive deficits of patients with PD, which depletes dopamine – range from movement to reward and decision-making? Second, what are the neural mechanisms supporting an important but understudied class of problems, in which, rather than choose among a set of alternatives (like apples and oranges), one makes serial decisions about whether to stick with an option (like a job, or a mate) or seek another? We demonstrate a novel cognitive deficit in PD that integrates this function into the web of DA’s contributions.

Why Don't Present-Biased Agents Make Commitments?

Present-biased preferences engender a demand for commitment. Commitment is a problematic prediction, since we see so little of it. I quantitatively explore the reasons for the “missing” commitment. Extending the procrastination model in Carroll et al. (2009), I show how equilibrium commitment is related to (i) the standard deviation of the opportunity cost of time, (ii) the cost of delay, (iii) the degree of partial naivete, and (iv) the direct cost of commitment. The calibrated model demonstrates that the perceived benefits of commitment are often overwhelmed by the costs of commitment. Demand for commitment is a special case rather than the general case.