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Low effort tendencies are related to maladaptive proclivities. There is a lack of research on this topic, possibly because of a lack of a standardized effort discounting task. In addition to a lack of standard task, most effort discounting tasks do not control for the delay confound inherent to effort requirements. It is unknown whether the delay confound affects effort discounting. The aim of Experiment 1 was to develop a task for measuring effort discounting that might be used as a standard measure, and to evaluate the influence of the delay confound on effort discounting. The remainder of the dissertation aimed to test methods to improve effort-based decision-making. Episodic future thinking is one intervention which successfully improves decision-making. Experiment 2 examined the effects of episodic future thinking on effort discounting. In Experiment 3, a novel episodic effortful thinking exercise was tested as an intervention to improve effort-based decision-making.

This research project seeks to test whether salient socioeconomic status has an impact on individual time preferences over effort.

The ventral striatum is believed to encode the subjective value of cost-benefit options; however, this effect has notably been absent during choices that involve physical effort. Previous work in freely moving animals has revealed opposing striatal signals, with greater response to increasing effort demands and reduced responses to rewards requiring effort. Yet, the relationship between these conflicting signals remains unknown. Using functional magnetic resonance imaging with a naturalistic maze-navigation paradigm, we identified functionally segregated regions within the ventral striatum that separately encoded effort activation, movement initiation and effort discounting of rewards. In addition, activity in regions associated with effort activation and discounting oppositely predicted striatal encoding of effort during effort-based decision-making. Our results suggest that the dorsomedial region hitherto associated with action may instead represent the cost of effort and raise fundamental questions regarding the interpretation of striatal 'reward' signals in the context of effort demands. This has implications for uncovering the neural architecture underlying motivated behaviour.

When individuals set goals, they consider the subjective value (SV) of the anticipated reward and the required effort, a trade-off that is of great interest to psychological research. One approach to quantify the SVs of levels of difficulty of a cognitive task is the Cognitive Effort Discounting Paradigm by Westbrook and colleagues (2013). However, it fails to acknowledge the highly individual nature of effort, as it assumes a unidirectional, inverse relationship between task load and SVs. Therefore, it cannot map differences in effort perception that arise from traits like Need for Cognition, since individuals who enjoy effortful cognitive activities likely do not prefer the easiest level. We replicated the analysis of Westbrook and colleagues with an adapted version, the Cognitive and Affective Discounting (CAD) Paradigm. It quantifies SVs without assuming that the easiest level is preferred, thereby enabling the assessment of SVs for tasks without objective order of task load. Results show that many participants preferred a more or the most difficult level. Variance in SVs was best explained by a declining logistic contrast of the $n$-back levels and by the accuracy of responses, while reaction time as a predictor was highly volatile depending on the preprocessing pipeline. Participants with higher Need for Cognition scores perceived higher $n$-back levels as less effortful and found them less aversive. Effects of Need for Cognition on SVs in lower levels did not reach significance, as group differences only emerged in higher levels. The CAD Paradigm appears to be well suited for assessing and analysing task preferences independent of the supposed objective task difficulty.

Discounting refers to decreases in the subjective value of an outcome with increases in some attribute of that outcome. The attributes most commonly studied are delay and probability, with far less research on effort and social discounting. Although these attributes all represent costs that reduce subjective value, it is as yet unclear how the extent to which they do so is related at the individual level. Accordingly, the present study examined the degree to which individual participants discounted hypothetical monetary rewards on each of four discounting tasks in which the delay, probability, effort, and number of people with whom the money was to be shared were manipulated. At the group level, larger amounts were discounted less steeply than smaller amounts when delay and effort were varied, whereas larger amounts were discounted more steeply when probability and number of people were varied. At the individual level, the correlational pattern was examined using exploratory factor analysis. A six-factor structure (with separate factors for delay and effort, and two factors each for social and probability discounting) described the relations among indifference points. At a more molar level, a two-factor structure, which corresponded to the direction of the observed magnitude effects, described the relations among area-under-the-curve measures of discounting in the eight conditions resulting from crossing two monetary amounts with the four cost factors. We conclude that despite sharing some similarities, individual and group differences in discounting involving the different types of costs reflect mostly separate processes and traits.

ADHD is defined by behavioral symptoms that are not well characterized in relation to ADHD’s neurobiological mechanisms. This approach has limited our ability to define ADHD nosology and predict outcomes because it does not systematically examine facets of the disorder such as the inability to maintain cognitively effortful activities, as promoted in the NIMH RDoC approach. Existing data indicate ADHD is associated with differences in reward valuation and processing, but we do not know whether ADHD is also associated with higher levels of aversion to exerting cognitive effort and/or altered reward x effort interactions. Our ongoing study addresses this knowledge gap by examining individuals’ preferences between rewards associated with minimal effort and reward alternatives with a higher payoff but higher effort costs (“effort discounting”); thereby permitting us to characterize differences in biases and tradeoffs during effort-related decision-making in ADHD. The study takes advantage of a well-defined sample of ADHD-diagnosed and healthy control individuals to address three aims. First, we determine whether ADHD is associated with steeper discounting of larger, more effortful rewards. Second, we examine the subjective perception of effort in youth diagnosed with ADHD and healthy controls using tasks requiring varying levels of cognitive effort. Third, we explore relationships amongst indices of effort discounting, theoretically-related traits (e.g., grit, distress tolerance), biomarkers of effort-related decision-making (eye movements and pupil size), and various cognitive measures. Successful completion of the aims will permit us to better characterize ADHD-healthy control differences and lay a foundation for more computational approaches to ADHD diagnostic criteria.

There exist large individual differences in students’ willingness to invest cognitive effort within the academic domain. In a preregistered study, we investigated whether individual differences in adolescents’ willingness to invest cognitive effort, as assessed by an experimental effort discounting task, were related to need for cognition, academic motivation and cognitive capacity. We found that adolescents’ willingness to invest cognitive effort was related to need for cognition and cognitive capacity as indexed by task-performance. Our results demonstrate that individual differences in need for cognition and cognitive capacity contribute to differences in adolescents’ cognitive effort-investment, but academic motivation does not.

Human behavior is more strongly driven by the motivation to avoid losses than to pursue gains (loss aversion). However, there is little research on how losses influence the motivation to exert effort. We compared the effects of loss and gain incentives on cognitive task performance and effort-based decision making. In three experiments, participants performed a cognitively effortful task under gain and loss conditions and made choices about effort expenditure in a decision-making task. Results consistently showed significant loss aversion in effort-based decision making. Participants were willing to invest more effort in the loss compared to the gain condition (i.e., perform a longer duration task: Experiments 1 and 2; or higher task load: Experiment 3). On the other hand, losses did not lead to improved performance (sustained attention), or higher physiological effort (pupil diameter) in Experiments 1 and 2. In Experiment 3, losses did enhance working memory performance, but only at the highest load level. Taken together, these results suggest that loss aversion motivates higher effort investment in effort-based decision-making, while the effect of loss aversion during a performance may depend on the task type or effort level.

Summary Motivation is characterized by a willingness to overcome both cognitive and physical effort costs. Impairments in motivation are common in striatal disorders, such as Huntington’s disease (HD), but whether these impairments are isolated to particular domains of behavior is controversial. We ask whether HD differentially affects the willingness of individuals to overcome cognitive versus physical effort. We tested 20 individuals with pre-manifest HD and compared their behavior to 20 controls. Across separate trials, participants made choices about how much cognitive or physical effort they were willing to invest for reward. Our key results were that individuals with pre-manifest HD were less willing than controls to invest cognitive effort but were no different in their overall preference for physical effort. These results cannot be explained by group differences in neuropsychological or psychiatric profiles. This dissociation of cognitive- and physical-effort-based decisions provides important evidence for separable, domain-specific mechanisms of motivation., Highlights We examine cognitive and physical effort discounting in pre-manifest HD Individuals with pre-manifest HD are less cognitively motivated than controls There are no differences in physical motivation between the two groups This dissociation is not confounded by neuropsychological or psychiatric factors, Motivational impairments are common in striatal disorders, such as Huntington’s disease (HD). Atkins et al. show that individuals in the pre-manifest stage of HD are less cognitively motivated than controls but equally physically motivated. These results provide empirical support for theories that posit the existence of dissociable subtypes of apathy.

Because impulsive decision-making is correlated with many maladaptive tendencies, researchers have increasingly studied methods for reducing impulsive choice. Most research in this area has focused on reducing delay-based impulsive choice, as measured by choices between smaller, immediate or larger, delayed rewards. A second type of impulsive choice is selecting a smaller, less-effortful reward over a larger, more-effortful one. Little nonhuman research has examined experimental methods for reducing effort-based impulsive choice. Within the realm of delay-based impulsive choice, extended exposure to reinforcer delays has proven effective in reducing impulsive choices in rats. The current study took a similar tac by evaluating if reductions in effort-based impulsive choice could be achieved by providing rats with extended exposure to high-effort training, i.e., reinforcement contingencies requiring a large number of responses. Male rats were randomly assigned to one of two groups: (1) high-effort training (fixed-ratio 50) or (2) low-effort training (fixed-ratio 1). Following training, both groups completed three tests of effort-based impulsive choice. There was an initial effect of HE training on effort-based impulsive choice, however the training effect quickly diminished across sessions for two out of the three tests. Possible explanations for the lack of lasting effect are discussed.

Background: Attention-deficit/hyperactivity disorder (ADHD) is presumed to involve mental effort application difficulties. To test this assumption, we manipulated task difficulty and measured behavioral, as well as subjective and psychophysiological indices of effort.Methods: Fifteen adolescent ADHD boys and 16 controls performed two tasks. First, subjective estimates and behavioral and pupillary measures of effort were recorded across five levels of N-back task difficulties. Second, effort discounting was assessed. In the latter, participants made repeated choices between performing a difficult N-back task for a high reward versus an easier N-back task for a smaller reward.Results: Increasing task difficulty led to similar deteriorations in performance for both groups – although ADHD participants performed more poorly at all difficulty levels than controls. While ADHD and control participants rated the tasks equally difficult and discounted effort similarly, those with ADHD displayed slightly different pupil dilation patterns with increasing task difficulty.Conclusion: The behavioral results did not provide evidence for mental effort problems in adolescent boys with ADHD. The subtle physiological effects, however, suggest that adolescents with ADHD may allocate effort in a different way than controls.

Making decisions about rewards that involve delay or effort requires the integration of value and cost information. The brain areas recruited in this integration have been well characterized for delay discounting. However only a few studies have investigated how effort costs are integrated into value signals to eventually determine choice. In contrast to previous studies that have evaluated fMRI signals related to physical effort, we used a task that focused on cognitive effort. Participants discounted the value of delayed and effortful rewards. The value of cognitively effortful rewards was represented in the anterior portion of the inferior frontal gyrus and dorsolateral prefrontal cortex. Additionally, the value of the chosen option was encoded in the anterior cingulate cortex, caudate, and cerebellum. While most brain regions showed no significant dissociation between effort discounting and delay discounting, the ACC was significantly more activated in effort compared to delay discounting tasks. Finally, overlapping regions within the right orbitofrontal cortex and lateral temporal and parietal cortices encoded the value of the chosen option during both delay and effort discounting tasks. These results indicate that encoding of rewards discounted by cognitive effort and delay involves partially dissociable brain areas, but a common representation of chosen value is present in the orbitofrontal, temporal and parietal cortices.

Highlights • Apathy in the normal population is dissociable from depression and anhedonia. • Apathy in the normal population is related to the modulation of physical effort people are willing to engage. • Apathy in the normal population is associated with higher subjective effort costs for small rewards., Apathy is a common but poorly understood condition with a wide societal impact observed in several brain disorders as well as, to some extent, in the normal population. Hence the need for better characterization of the underlying mechanisms. The processes by which individuals decide to attribute physical effort to obtain rewards might be particularly relevant to relate to apathy traits. Here, we designed two paradigms to assess individual differences in physical effort production and effort-based decision-making and their relation to apathy in healthy people. Apathy scores were measured using a modified version of the Lille Apathy Rating Scale, suitable for use in a non-clinical population. In the first study, apathy scores were correlated with the degree to which stake (reward on offer) and difficulty level impacts on physical effort production. Individuals with relatively high apathy traits showed an increased modulation of effort while more motivated individuals generally exerted greater force across different levels of stake. To clarify the underlying mechanisms for this behavior, we designed a second task that allows independent titration of stake and effort levels for which subjects are willing to engage in an effortful response to obtain a reward. Our results suggest that apathy traits in the normal population are related to the way reward subjectively affects the estimation of effort costs, and more particularly manifest as decreased willingness to exert effort when rewards are small, or below threshold. The tasks we introduce here may provide useful tools to further investigate apathy in clinical populations.

Letting effort-free gratification derail us from effort-requiring goals is one reason why we fail to realize health-relevant intentions like ‘exercise regularly’. We tested the effectiveness of the self-control strategy precommitment in such effort-related conflicts, using a novel laboratory choice paradigm, where participants could precommit to an effort-requiring large reward by pre-eliminating an effort-free small reward from their choice set. Our participants used precommitment frequently and effectively, such that they reached effort-requiring large rewards more often. Using computational modelling and Bayesian model comparisons, we assessed whether participants employed precommitment to avoid anticipated willpower failures (i.e. as a self-regulatory measure) or to maximize their motivation to choose the effort-requiring option (i.e. as a self-motivational measure). Observed choices and precommitment decisions were consistent with the motivation maximization hypothesis, but not the willpower hypothesis. Our findings show that offering precommitment is effective in helping individuals optimize their motivation and choice behaviour and thereby achieve effort-requiring goals, and strongly encourage application of precommitment schemes in exercise and rehabilitation interventions. This article is part of the theme issue ‘Risk taking and impulsive behaviour: fundamental discoveries, theoretical perspectives and clinical implications’.