The opportunity cost of time modulates cognitive effort

Catecholaminergic modulation of the cost of cognitive control in healthy older adults

Catecholamines have long been associated with cognitive control and value-based decision-making. More recently, we have shown that catecholamines also modulate value-based decision-making about whether or not to engage in cognitive control. Yet it is unclear whether catecholamines influence these decisions by altering the subjective value of control. Thus, we tested whether tyrosine, a catecholamine precursor altered the subjective value of performing a demanding working memory task among healthy older adults (60-75 years). Contrary to our prediction, tyrosine administration did not significantly increase the subjective value of conducting an N-back task for reward, as a main effect. Instead, in line with our previous study, exploratory analyses indicated that drug effects varied as a function of participants' trait impulsivity scores. Specifically, tyrosine increased the subjective value of conducting an N-back task in low impulsive participants, while reducing its value in more impulsive participants. One implication of these findings is that the over-the-counter tyrosine supplements may be accompanied by an undermining effect on the motivation to perform demanding cognitive tasks, at least in certain older adults. Taken together, these findings indicate that catecholamines can alter cognitive control by modulating motivation (rather than just the ability) to exert cognitive control.

Distinguishing cognitive effort and working memory load using scale-invariance and alpha suppression in EEG

Despite being intuitive, cognitive effort has proven difficult to define quantitatively. Here, we proposed to study cognitive effort by investigating the degree to which the brain deviates from its default state, where brain activity is scale-invariant. Specifically, we measured such deviations by examining changes in scale-invariance of brain activity as a function of task difficulty and posited suppression of scale-invariance as a proxy for exertion of cognitive effort. While there is some fMRI evidence supporting this proposition, EEG investigations on the matter are scant, despite the EEG signal being more suitable for analysis of scale invariance (i.e., having a much broader frequency range). In the current study we validated the correspondence between scale-invariance (H) of cortical activity recorded by EEG and task load during two working memory (WM) experiments with varying set sizes. Then, we used this neural signature to disentangle cognitive effort from the number of items stored in WM within participants. Our results showed monotonic decreases in H with increased set size, even after set size exceeded WM capacity. This behavior of H contrasted with behavioral performance and an oscillatory indicator of WM load (i.e., alpha-band desynchronization), both of which showed a plateau at difficulty levels surpassing WM capacity. This is the first reported evidence for the suppression of scale-invariance in EEG due to task difficulty, and our work suggests that H suppression may be used to quantify changes in cognitive effort even when working memory load is at maximum capacity.

Metacontrol of decision-making strategies in human aging

Humans employ different strategies when making decisions. Previous research has reported reduced reliance on model-based strategies with aging, but it remains unclear whether this is due to cognitive or motivational factors. Moreover, it is not clear how aging affects the metacontrol of decision making, that is the dynamic adaptation of decision-making strategies to varying situational demands. In this cross-sectional study, we tested younger and older adults in a sequential decision-making task that dissociates model-free and model-based strategies. In contrast to previous research, model-based strategies led to higher payoffs. Moreover, we manipulated the costs and benefits of model-based strategies by varying reward magnitude and the stability of the task structure. Compared to younger adults, older adults showed reduced model-based decision making and less adaptation of decision-making strategies. Our findings suggest that aging affects the metacontrol of decision-making strategies and that reduced model-based strategies in older adults are due to limited cognitive abilities.

Predicting an Outcome Less Probable yet More Desirable than the Other

Extant research suggests that the desirability of an outcome influences the way an individual makes a prediction. The current research investigated how an outcome's desirability influences the extent to which an individual evaluates its probability when making a prediction. Two studies were conducted using a single binary prediction based on the urn model. Individuals predicted which color-red or blue-a ball drawn from a bag would be, while being aware of the proportion of each color in the bag. The results of the first study indicated that individuals predicted the more probable outcome regardless of the probabilities of two outcomes. However, when the less probable outcome was more desirable, the proportion of predictions became significantly correlated and better calibrated to the actual probability. This result was interpreted as showing that, when motivated to predict the more desirable but less probable outcome, individuals evaluate its probability more effortfully. This interpretation was tested in the second study. When the probabiity- matching motivation was implemented, the proportion of individuals who predicted the less probable outcome increased significantly. However, when the less probable outcome was more desirable, the same motivation did not significantly increase the proportion of such individuals. Taken together, these results imply that individuals likely process the same probability informatio differently based on whether this information is useful for predicting a desirable outcome.

Enhanced motivation of cognitive control in Parkinson's disease

Motor and cognitive deficits in Parkinson's disease (PD) have been argued to reflect motivational deficits. In prior work, however, we have shown that motivation of cognitive control is paradoxically potentiated rather than impaired in Parkinson's disease. This is particularly surprising given the fact that Parkinson's disease is often accompanied by depression, a prototypical disorder of motivation. To replicate our previous finding and assess the effects of depression, we investigated performance of PD patients with (n = 22) and without depression (history) (n = 23) and age‐matched healthy controls (n = 23) on a task specifically designed to measure the effect of reward motivation on task‐switching. We replicated previous findings by showing contrasting effects of reward motivation on task‐switching in PD patients and age‐matched healthy controls. While the promise of high versus low reward improved task‐switching in PD, it tended to impair task‐switching in age‐matched healthy controls. There were no effects of a depression (history) diagnosis in PD patients. These findings reinforce prior observations that Parkinson's disease is accompanied by enhanced incentive motivation of cognitive control and highlight the potential of incentive motivational strategies for overcoming cognitive deficits in Parkinson's disease.

Mental labour

Mental effort is an elementary notion in our folk psychology and a familiar fixture in everyday introspective experience. However, as an object of scientific study, mental effort has remained rather elusive. Cognitive psychology has provided some tools for understanding how effort impacts performance, by linking effort with cognitive control function. What has remained less clear are the principles that govern the allocation of mental effort. Under what circumstances do people choose to invest mental effort, and when do they decline to do so? And what regulates the intensity of mental effort when it is applied? In new and promising work, these questions are being approached with the tools of behavioural economics. Though still in its infancy, this economic approach to mental effort research has already uncovered important aspects of effort-based decision-making, and points clearly to future lines of inquiry, including some intriguing opportunities presented by recent artificial intelligence research.