What is the subjective cost of cognitive effort? Load, trait, and aging effects revealed by economic preference

Thinking in action: Need for Cognition predicts Self-Control together with Action Orientation

Need for Cognition describes relatively stable interindividual differences in cognitive motivation. Previous research has shown relations of Need for Cognition to Self-Control–a capacity that can be broadly defined as resistance to temptation–yet, the processes underlying this relation remain unclear. One explanation for the prediction of Self-Control by Need for Cognition can be an increased motivation to invest cognitive effort with higher levels of Need for Cognition. Another possible link could be that individual differences in the implementation of Self-Control intentions may play a moderating or mediating role for the predictive value of Need for Cognition. Such individual differences in the self-motivated initiation and maintenance of intentions are described by dispositional Action Orientation. Therefore, in the present study, Action Orientation was examined with regard to its possible role in explaining the relation of Need for Cognition to Self-Control. In a sample of 1209 young adults, Self-Control was assessed with two different self-report instruments and moderation and mediation models of the relationship between Need for Cognition, Action Orientation, and Self-Control were tested. While there was no evidence for a moderating role of Action Orientation in explaining the relation of Need for Cognition and Self-Control, Action Orientation was found to partly mediate this relation with a remaining direct effect of Need for Cognition on Self-Control. These results add to the conceptual understanding of Need for Cognition and demonstrate the relevance of trait variables to predict Self-Control.

Understanding the cognitive miser: Cue-utilization in effort-based decision making

The notion that individuals adapt their behaviors in ways that are sensitive to the effortfulness of cognitive processing is pervasive in psychology. In the current set of experiments, we provide a test of a cue-utilization account of how individuals decide which course of action is more or less effortful. In particular, we contrast the influences of time costs and demands on executive control with the influence of an available effort cue. Using a variant of the demand selection task (DST) that specifically focused on making effort-based decisions, we provide evidence that effort-based decisions can be dissociated from both time costs and demands on executive control in a manner predicted by a cue-utilization account.

Why not try harder? Computational approach to motivation deficits in neuro-psychiatric diseases

Motivation deficits, such as apathy, are pervasive in both neurological and psychiatric diseases. Even when they are not the core symptom, they reduce quality of life, compromise functional outcome and increase the burden for caregivers. They are currently assessed with clinical scales that do not give any mechanistic insight susceptible to guide therapeutic intervention. Here, we present another approach that consists of phenotyping the behaviour of patients in motivation tests, using computational models. These formal models impose a precise and operational definition of motivation that is embedded in decision theory. Motivation can be defined as the function that orients and activates the behaviour according to two attributes: a content (the goal) and a quantity (the goal value). Decision theory offers a way to quantify motivation, as the cost that patients would accept to endure in order to get the benefit of achieving their goal. We then review basic and clinical studies that have investigated the trade-off between the expected cost entailed by potential actions and the expected benefit associated with potential rewards. These studies have shown that the trade-off between effort and reward involves specific cortical, subcortical and neuromodulatory systems, such that it may be shifted in particular clinical conditions, and reinstated by appropriate treatments. Finally, we emphasize the promises of computational phenotyping for clinical purposes. Ideally, there would be a one-to-one mapping between specific neural components and distinct computational variables and processes of the decision model. Thus, fitting computational models to patients' behaviour would allow inferring of the dysfunctional mechanism in both cognitive terms (e.g. hyposensitivity to reward) and neural terms (e.g. lack of dopamine). This computational approach may therefore not only give insight into the motivation deficit but also help personalize treatment.

After-effects of self-control: The reward responsivity hypothesis

Exercising self-control can be phenomenologically aversive. Insofar as individuals strive to maintain a positive emotional state, one consequence of exercising self-control may thus be a temporarily tuning toward or amplification of reward-related impulses (perhaps arising to countermand the aversive feelings that stem from self-control). Reward-relevant after-effects are relatively underappreciated in self-control research. In the current paper, we review theory and research pertaining to the idea that exercising self-control increases reward responsivity. First, we review theoretical models of self-control focusing on the relationship between control systems and reward systems. Second, we review behavioral studies regarding the effects of exercising self-control on subsequent reactivity to food, money, drugs, and positive emotional images. Third, we review findings from functional neuroimaging and electroencephalographic research pertaining to the reward responsivity hypothesis. We then call for additional research to integrate how, when, and under what circumstances self-control exertion influences reward processing. Such an endeavor will help to advance research and theory on self-control by offering a more precise characterization of the dynamic interactions between control systems and reward systems.

Motivation and cognitive control in depression

Depression is linked to deficits in cognitive control and a host of other cognitive impairments arise as a consequence of these deficits. Despite of their important role in depression, there are no mechanistic models of cognitive control deficits in depression. In this paper we propose how these deficits can emerge from the interaction between motivational and cognitive processes. We review depression-related impairments in key components of motivation along with new cognitive neuroscience models that focus on the role of motivation in the decision-making about cognitive control allocation. Based on this review we propose a unifying framework which connects motivational and cognitive control deficits in depression. This framework is rooted in computational models of cognitive control and offers a mechanistic understanding of cognitive control deficits in depression.

The Subjective Value of Cognitive Effort is Encoded by a Domain-General Valuation Network

Cognitive control is necessary for goal-directed behavior, yet people treat cognitive control demand as a cost, which discounts the value of rewards in a similar manner as other costs, such as delay or risk. It is unclear, however, whether the subjective value (SV) of cognitive effort is encoded in the same putatively domain-general brain valuation network implicated in other cost domains, or instead engages a distinct frontoparietal network, as implied by recent studies. Here, we provide rigorous evidence that the valuation network, with core foci in the ventromedial prefrontal cortex and ventral striatum, also encodes SV during cognitive effort-based decision-making in healthy, male and female adult humans. We doubly dissociate this network from frontoparietal regions that are instead recruited as a function of decision difficulty. We show that the domain-general valuation network jointly and independently encodes both reward benefits and cognitive effort costs. We also demonstrate that cognitive effort SV signals predict choice and are influenced by state and trait motivation, including sensitivity to reward and anticipated task performance. These findings unify cognitive effort with other cost domains, and suggest candidate neural mechanisms underlying state and trait variation in willingness to expend cognitive effort.SIGNIFICANCE STATEMENT Subjective effort costs are increasingly understood to diminish cognitive control over task performance and can thus undermine functioning across health and disease. Yet, we are only beginning to understand how decisions about cognitive effort are made. A key question is how subjective values are computed. Recent work suggests that the value of cognitive effort might be computed by networks that are distinct from those involved in other domains like intertemporal and risky decision-making, implying distinct mechanisms. Here we demonstrate that the domain-general network also encodes effort-discounted value, linking cognitive effort closely with other domains. Our results thus elucidate key mechanisms supporting decisions about cognitive effort, and point to candidate neural targets for intervention in disorders involving impaired cognitive motivation.

The transdiagnostic structure of mental effort avoidance

The law of least mental effort states that, everything else being equal, the brain tries to minimize mental effort expenditure during task performance by avoiding decisions that require greater cognitive demands. Prior studies have shown associations between disruptions in effort expenditure and specific psychiatric illnesses (e.g., schizophrenia and depression) or clinically-related symptoms and traits (e.g., anhedonia and apathy), yet no research has explored this issue transdiagnostically. Specifically, this research has largely focused on a single diagnostic category, symptom, or trait. However, abnormalities in effort expression could be related to several different psychiatrically-relevant constructs that cut across diagnostic boundaries. Therefore, we examined the relationship between avoidance of mental effort and a diverse set of clinically-related symptoms and traits, and transdiagnostic latent factors in a large sample (n = 811). Only lack of perseverance, a dimension of impulsiveness, was associated with increased avoidance of mental effort. In contrast, several constructs were associated with less mental effort avoidance, including positive urgency, distress intolerance, obsessive-compulsive symptoms, disordered eating, and a factor consisting of compulsive behavior and intrusive thoughts. These findings demonstrate that deviations from normative effort expenditure are associated with a number of constructs that are common to several forms of psychiatric illness.

Cue awareness in avoiding effortful control

Based on a recent metacognitive account, cognitive effort is the result of an inferential evaluation made over explicitly available cues. Following from this account, we present here a pre-registered experiment that tested the specific hypothesis that explicit awareness of cues that are aligned with cognitive demand is a prerequisite in avoiding effortful lines of action. We attempted to modulate levels of effort avoidance behavior by introducing an incentive (between-subjects) to monitor two lines of action that, unbeknownst to individuals, varied in the probability of a task switch. Importantly, previous research has demonstrated that the difference in these probabilities is relatively opaque to individuals. We did not find strong evidence for our incentive manipulation having an effect on demand avoidance as indexed by individuals' choices in a block of the task where avoiding effort was instructed. However, we do find that being aware of the task-switching cue appears to increase the likelihood of demand avoidance. We consider these results within the context of the metacognition of cognitive effort.

Deliberate reasoning is not affected by language

BACKGROUND

Millions of people use a second language every day. Does this have an effect on their decision-making? Are decisions in a second language more deliberate? Two mechanisms have been proposed: reduced emotionality or increased deliberation. Most studies so far used problems where both mechanisms could contribute to a foreign language effect. Here, we aimed to identify whether deliberate reasoning increases for problems that are devoid of any emotional connotation when using a second language or having to switch between native and second language.

METHOD

We measured deliberate reasoning with items from the cognitive reflection test, ratio bias, a probability matching task, and base rate neglect items. We recruited over 500 participants from Norway and the Netherlands that had English as their second language. Participants were randomly assigned to either the native, switching or second language condition. We measured: number of correctly answered items-deliberate reasoning score, perceived effort, perceived accuracy or confidence, and language proficiency.

RESULTS

Deliberate reasoning was not increased when using a second language or when having to switch between native and second language. All three groups performed equally well. Significant predictors of deliberate reasoning were age, gender, education, perceived effort, and confidence but not the language context. Participants with low English proficiency spent more time reading compared to more fluent speakers.

CONCLUSION

There is no advantage of second language on deliberate reasoning in the absence of time pressure. Deliberation was not increased by providing items in a second language, but through the willingness to spend cognitive effort and time to read carefully.

A Pilot Study of Behavioral, Physiological, and Subjective Responses to Varying Mental Effort Requirements in Attention-Deficit/Hyperactivity Disorder

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.

Computational neuroscience across the lifespan: Promises and pitfalls

In recent years, the application of computational modeling in studies on age-related changes in decision making and learning has gained in popularity. One advantage of computational models is that they provide access to latent variables that cannot be directly observed from behavior. In combination with experimental manipulations, these latent variables can help to test hypotheses about age-related changes in behavioral and neurobiological measures at a level of specificity that is not achievable with descriptive analysis approaches alone. This level of specificity can in turn be beneficial to establish the identity of the corresponding behavioral and neurobiological mechanisms. In this paper, we will illustrate applications of computational methods using examples of lifespan research on risk taking, strategy selection and reinforcement learning. We will elaborate on problems that can occur when computational neuroscience methods are applied to data of different age groups. Finally, we will discuss potential targets for future applications and outline general shortcomings of computational neuroscience methods for research on human lifespan development.

An information-theoretic perspective on the costs of cognition

In statistics and machine learning, model accuracy is traded off with complexity, which can be viewed as the amount of information extracted from the data. Here, we discuss how cognitive costs can be expressed in terms of similar information costs, i.e. as a function of the amount of information required to update a person's prior knowledge (or internal model) to effectively solve a task. We then examine the theoretical consequences that ensue from this assumption. This framework naturally explains why some tasks - for example, unfamiliar or dual tasks - are costly and permits to quantify these costs using information-theoretic measures. Finally, we discuss brain implementation of this principle and show that subjective cognitive costs can originate either from local or global capacity limitations on information processing or from increased rate of metabolic alterations. These views shed light on the potential adaptive value of cost-avoidance mechanisms.

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.

The neural basis of motivational influences on cognitive control

Cognitive control mechanisms support the deliberate regulation of thought and behavior based on current goals. Recent work suggests that motivational incentives improve cognitive control and has begun to elucidate critical neural substrates. We conducted a quantitative meta-analysis of neuroimaging studies of motivated cognitive control using activation likelihood estimation (ALE) and Neurosynth to delineate the brain regions that are consistently activated across studies. The analysis included studies that investigated changes in brain activation during cognitive control tasks when reward incentives were present versus absent. The ALE analysis revealed consistent recruitment in regions associated with the frontoparietal control network including the inferior frontal sulcus and intraparietal sulcus, as well as regions associated with the salience network including the anterior insula and anterior mid-cingulate cortex. As a complementary analysis, we performed a large-scale exploratory meta-analysis using Neurosynth to identify regions that are recruited in studies using of the terms cognitive control and incentive. This analysis replicated the ALE results and also identified the rostrolateral prefrontal cortex, caudate nucleus, nucleus accumbens, medial thalamus, inferior frontal junction, premotor cortex, and hippocampus. Finally, we separately compared recruitment during cue and target periods, which tap into proactive engagement of rule-outcome associations, and the mobilization of appropriate viscero-motor states to execute a response, respectively. We found that largely distinct sets of brain regions are recruited during cue and target periods. Altogether, these findings suggest that flexible interactions between frontoparietal, salience, and dopaminergic midbrain-striatal networks may allow control demands to be precisely tailored based on expected value.

Effort-Based Decision-Making in Schizophrenia

Motivational impairment has long been associated with schizophrenia but the underlying mechanisms are not clearly understood. Recently, a small but growing literature has suggested that aberrant effort-based decision-making may be a potential contributory mechanism for motivational impairments in psychosis. Specifically, multiple reports have consistently demonstrated that individuals with schizophrenia are less willing than healthy controls to expend effort to obtain rewards. Further, this effort-based decision-making deficit has been shown to correlate with severity of negative symptoms and level of functioning, in many but not all studies. In the current review, we summarize this literature and discuss several factors that may underlie aberrant effort-based decision-making in schizophrenia.

Intellectual Investment, Dopaminergic Gene Variation, and Life Events: A Critical Examination

Need for Cognition (NFC) and Openness to Ideas are intellectual investment traits that are characterized by a tendency to seek out, engage in and enjoy effortful cognitive activity. Little, however, is known about the extent to which they are influenced by genetic and environmental factors. With the present contribution, we aim at furthering our knowledge on the mechanisms underlying intellectual investment traits by following-up on a recent investigation of the role of dopaminergic gene variation in intellectual investment. Employing a standard approach that relied on null-hypothesis significance testing, we found that, first, two dopaminergic genetic variants interacted in modulating individual differences in NFC, but not in Openness to Ideas; that, second, negative life events played a role in the modulation of Openness to Ideas, but not of NFC; and that, third, negative life events as assessed using another measure were only marginally related to Openness to Ideas while positive life events were associated with both Openness to Ideas and NFC, with the latter effect being also dependent on DRD4 exon III genotype. However, employing a Bayesian approach, the assumption of a genetic effect on investment traits was overall not supported, while the assumption of a role of positive life events in the modulation of investment traits could be confirmed, with a tentative increment in the prediction of NFC by adding an interaction of positive life events and DRD4 variation to the main effect of positive life events. Our findings underscore the importance to use different approaches in the field of personality neuroscience. To gain deeper insight into the basis of personality traits does not only require to consider genetic as well as environmental influences and their interplay, but also requires more differentiated statistical analyses that can at least in part tackle the often inconsistent findings in this field.

Neural systems of cognitive demand avoidance

Cognitive effort is typically aversive, evident in people's tendency to avoid cognitively demanding tasks. The 'cost of control' hypothesis suggests that engagement of cognitive control systems of the brain makes a task costly and the currency of that cost is a reduction in anticipated rewards. However, prior studies have relied on binary hard versus easy task subtractions to manipulate cognitive effort and so have not tested this hypothesis in "dose-response" fashion. In a sample of 50 participants, we parametrically manipulated the level of effort during fMRI scanning by systematically increasing cognitive control demands during a demand-selection paradigm over six levels. As expected, frontoparietal control network (FPN) activity increased, and reward network activity decreased, as control demands increased across tasks. However, avoidance behavior was not attributable to the change in FPN activity, lending only partial support to the cost of control hypothesis. By contrast, we unexpectedly observed that the de-activation of a task-negative brain network corresponding to the Default Mode Network (DMN) across levels of the cognitive control manipulation predicted the change in avoidance. In summary, we find partial support for the cost of control hypothesis, while highlighting the role of task-negative brain networks in modulating effort avoidance behavior.

Reward circuitry activation reflects social preferences in the face of cognitive effort

Research at the intersection of social neuroscience and cognitive effort is an interesting new area for exploration. There is great potential to broaden our understanding of how social context and cognitive effort processes, currently addressed in disparate literatures, interact with one another. In this paper, we briefly review the literature on cognitive effort, focusing on effort-linked valuation and the gap in the literature regarding cognitive effort in the social domain. Next, we present a study designed to explore valuation processes linked to cognitive effort within the social context of an inequality manipulation. More specifically, we created monetary inequality among the participant (SELF, endowed with $50) and two confederates: one also endowed with $50 (OTHER HIGH) and another with only $5 (OTHER LOW). We then scanned participants using fMRI as they attempted to earn bonus payments for themselves and others through a cognitively effortful feedback-based learning task. Positive feedback produced significantly greater activation than negative feedback in key valuation regions, the ventral striatum (VS) and ventromedial prefrontal cortex (vmPFC), both when participants were performing the task on their own behalf and when earning rewards for others. While reward-related activity in the VS was exaggerated for SELF compared to OTHER HIGH for both positive and negative feedback, activity in the vmPFC did not distinguish between recipients in the group-level results. Furthermore, participants naturally fell into two groups: those most engaged when playing for themselves and those who reported engagement for others. While Self-Engaged participants showed differences between the SELF and both OTHER conditions in the VS and vmPFC, Other-Engaged participants only showed an attenuated response to negative feedback for OTHER HIGH compared to SELF in the VS and no differences between recipient conditions in the vmPFC. Together, this work shows the importance of individual differences and the fragility of advantageous inequality aversion in the face of cognitive effort, highlighting the need to study cognitive effort in the social domain.

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.

Subjective value representations during effort, probability and time discounting across adulthood

Every day, humans make countless decisions that require the integration of information about potential benefits (i.e. rewards) with other decision features (i.e. effort required, probability of an outcome or time delays). Here, we examine the overlap and dissociation of behavioral preferences and neural representations of subjective value in the context of three different decision features (physical effort, probability and time delays) in a healthy adult life span sample. While undergoing functional neuroimaging, participants (N = 75) made incentive compatible choices between a smaller monetary reward with lower physical effort, higher probability, or a shorter time delay versus a larger monetary reward with higher physical effort, lower probability, or a longer time delay. Behavioral preferences were estimated from observed choices, and subjective values were computed using individual hyperbolic discount functions. We found that discount rates were uncorrelated across tasks. Despite this apparent behavioral dissociation between preferences, we found overlapping subjective value-related activity in the medial prefrontal cortex across all three tasks. We found no consistent evidence for age differences in either preferences or the neural representations of subjective value across adulthood. These results suggest that while the tolerance of decision features is behaviorally dissociable, subjective value signals share a common representation across adulthood.

Planning Complexity Registers as a Cost in Metacontrol

Decision-making algorithms face a basic tradeoff between accuracy and effort (i.e., computational demands). It is widely agreed that humans can choose between multiple decision-making processes that embody different solutions to this tradeoff: Some are computationally cheap but inaccurate, whereas others are computationally expensive but accurate. Recent progress in understanding this tradeoff has been catalyzed by formalizing it in terms of model-free (i.e., habitual) versus model-based (i.e., planning) approaches to reinforcement learning. Intuitively, if two tasks offer the same rewards for accuracy but one of them is much more demanding, we might expect people to rely on habit more in the difficult task: Devoting significant computation to achieve slight marginal accuracy gains would not be "worth it." We test and verify this prediction in a sequential reinforcement learning task. Because our paradigm is amenable to formal analysis, it contributes to the development of a computational model of how people balance the costs and benefits of different decision-making processes in a task-specific manner; in other words, how we decide when hard thinking is worth it.

Effort-cost decision-making in psychosis and depression: could a similar behavioral deficit arise from disparate psychological and neural mechanisms?

Motivational impairment is a common feature of both depression and psychosis; however, the psychological and neural mechanisms that give rise to motivational impairment in these disorders are poorly understood. Recent research has suggested that aberrant effort-cost decision-making (ECDM) may be a potential contributor to motivational impairment in both psychosis and depression. ECDM refers to choices that individuals make regarding the amount of 'work' they are willing to expend to obtain a certain outcome or reward. Recent experimental work has suggested that those with psychosis and depression may be less willing to expend effort to obtain rewards compared with controls, and that this effort deficit is related to motivational impairment in both disorders. In the current review, we aim to summarize the current literature on ECDM in psychosis and depression, providing evidence for transdiagnostic impairment. Next, we discuss evidence for the hypothesis that a seemingly similar behavioral ECDM deficit might arise from disparate psychological and neural mechanisms. Specifically, we argue that effort deficits in psychosis might be largely driven by deficits in cognitive control and the neural correlates of cognitive control processes, while effort deficits in depression might be largely driven by reduced reward responsivity and the associated neural correlates of reward responsivity. Finally, we will provide some discussion regarding future directions, as well as interpretative challenges to consider when examining ECDM transdiagnostically.

The Effort Paradox: Effort Is Both Costly and Valued

According to prominent models in cognitive psychology, neuroscience, and economics, effort (be it physical or mental) is costly: when given a choice, humans and non-human animals alike tend to avoid effort. Here, we suggest that the opposite is also true and review extensive evidence that effort can also add value. Not only can the same outcomes be more rewarding if we apply more (not less) effort, sometimes we select options precisely because they require effort. Given the increasing recognition of effort's role in motivation, cognitive control, and value-based decision-making, considering this neglected side of effort will not only improve formal computational models, but also provide clues about how to promote sustained mental effort across time.

Interactions of Motivation and Cognitive Control

There is general agreement that both motivation and cognitive control play critical roles in shaping goal-directed behavior, but only recently has scientific interest focused around the question of motivation-control interactions. Here we briefly survey this literature, organizing contemporary findings around three issues: 1) whether motivation preferentially impacts cognitive control processes, 2) the neural mechanisms that underlie motivation-cognition interactions, and 3) why motivation might be relevant for overcoming the costs of control. Dopamine (DA) is discussed as a key neuromodulator in these motivation-cognition interactions. We conclude by highlighting open issues, specifically Pavlovian versus instrumental control distinctions and effects of motivational valence and conflict, which could benefit from future research attention.

Is Listening in Noise Worth It? The Neurobiology of Speech Recognition in Challenging Listening Conditions

This review examines findings from functional neuroimaging studies of speech recognition in noise to provide a neural systems level explanation for the effort and fatigue that can be experienced during speech recognition in challenging listening conditions. Neuroimaging studies of speech recognition consistently demonstrate that challenging listening conditions engage neural systems that are used to monitor and optimize performance across a wide range of tasks. These systems appear to improve speech recognition in younger and older adults, but sustained engagement of these systems also appears to produce an experience of effort and fatigue that may affect the value of communication. When considered in the broader context of the neuroimaging and decision making literature, the speech recognition findings from functional imaging studies indicate that the expected value, or expected level of speech recognition given the difficulty of listening conditions, should be considered when measuring effort and fatigue. The authors propose that the behavioral economics or neuroeconomics of listening can provide a conceptual and experimental framework for understanding effort and fatigue that may have clinical significance.

Dopamine and Proximity in Motivation and Cognitive Control

Cognitive control - the ability to override a salient or prepotent action to execute a more deliberate one - is required for flexible, goal-directed behavior, and yet it is subjectively costly: decision-makers avoid allocating control resources, even when doing so affords more valuable outcomes. Dopamine likely offsets effort costs just as it does for physical effort. And yet, dopamine can also promote impulsive action, undermining control. We propose a novel hypothesis that reconciles opposing effects of dopamine on cognitive control: during action selection, striatal dopamine biases benefits relative to costs, but does so preferentially for "proximal" motor and cognitive actions. Considering the nature of instrumental affordances and their dynamics during action selection facilitates a parsimonious interpretation and conserved corticostriatal mechanisms across physical and cognitive domains.

Cognitive capacity limitations and Need for Cognition differentially predict reward-induced cognitive effort expenditure

While psychological, economic, and neuroscientific accounts of behavior broadly maintain that people minimize expenditure of cognitive effort, empirical work reveals how reward incentives can mobilize increased cognitive effort expenditure. Recent theories posit that the decision to expend effort is governed, in part, by a cost-benefit tradeoff whereby the potential benefits of mental effort can offset the perceived costs of effort exertion. Taking an individual differences approach, the present study examined whether one's executive function capacity, as measured by Stroop interference, predicts the extent to which reward incentives reduce switch costs in a task-switching paradigm, which indexes additional expenditure of cognitive effort. In accordance with the predictions of a cost-benefit account of effort, we found that a low executive function capacity-and, relatedly, a low intrinsic motivation to expend effort (measured by Need for Cognition)-predicted larger increase in cognitive effort expenditure in response to monetary reward incentives, while individuals with greater executive function capacity-and greater intrinsic motivation to expend effort-were less responsive to reward incentives. These findings suggest that an individual's cost-benefit tradeoff is constrained by the perceived costs of exerting cognitive effort.

A Novel Communication Value Task Demonstrates Evidence of Response Bias in Cases with Presbyacusis

Decision-making about the expected value of an experience or behavior can explain hearing health behaviors in older adults with hearing loss. Forty-four middle-aged to older adults (68.45 ± 7.73 years) performed a task in which they were asked to decide whether information from a surgeon or an administrative assistant would be important to their health in hypothetical communication scenarios across visual signal-to-noise ratios (SNR). Participants also could choose to view the briefly presented sentences multiple times. The number of these effortful attempts to read the stimuli served as a measure of demand for information to make a health importance decision. Participants with poorer high frequency hearing more frequently decided that information was important to their health compared to participants with better high frequency hearing. This appeared to reflect a response bias because participants with high frequency hearing loss demonstrated shorter response latencies when they rated the sentences as important to their health. However, elevated high frequency hearing thresholds did not predict demand for information to make a health importance decision. The results highlight the utility of a performance-based measure to characterize effort and expected value from performing tasks in older adults with hearing loss.

Anticipating cognitive effort: roles of perceived error-likelihood and time demands

Why are some actions evaluated as effortful? In the present set of experiments we address this question by examining individuals' perception of effort when faced with a trade-off between two putative cognitive costs: how much time a task takes vs. how error-prone it is. Specifically, we were interested in whether individuals anticipate engaging in a small amount of hard work (i.e., low time requirement, but high error-likelihood) vs. a large amount of easy work (i.e., high time requirement, but low error-likelihood) as being more effortful. In between-subject designs, Experiments 1 through 3 demonstrated that individuals anticipate options that are high in perceived error-likelihood (yet less time consuming) as more effortful than options that are perceived to be more time consuming (yet low in error-likelihood). Further, when asked to evaluate which of the two tasks was (a) more effortful, (b) more error-prone, and (c) more time consuming, effort-based and error-based choices closely tracked one another, but this was not the case for time-based choices. Utilizing a within-subject design, Experiment 4 demonstrated overall similar pattern of judgments as Experiments 1 through 3. However, both judgments of error-likelihood and time demand similarly predicted effort judgments. Results are discussed within the context of extant accounts of cognitive control, with considerations of how error-likelihood and time demands may independently and conjunctively factor into judgments of cognitive effort.

Assessing the role of reward in task selection using a reward-based voluntary task switching paradigm

People exhibit a remarkable ability to both maintain controlled focus on executing a single task and flexibly shift between executing several tasks. Researchers studying human multitasking have traditionally focused on the cognitive control mechanisms that allow for such stable and flexible task execution, but there has been a recent interest in how cognitive control mechanisms drive the decision of task selection. The present research operationalizes a foraging analogy to investigate what factors drive the decision to either exploit task repetitions or explore task switches. A novel paradigm-reward-based voluntary task switching-ascribes point values to tasks where the overall goal is to accumulate points as quickly as possible. The reward structure generally rewards switching tasks, thereby juxtaposing the motivation to gain increased reward (by exploring task switches) against the motivation to perform quickly (by exploiting task repetitions). Results suggest that people are highly sensitive to changes in both reward and effort demands when making task selections, and that the task selection process is efficient and flexible. We argue that a cost-benefit mechanism might underlie decisions in multitasking contexts, whereby people compute task selections based on both the reward available for selecting a task and the effort necessary to execute a task.

Using the Diffusion Model to Explain Cognitive Deficits in Attention Deficit Hyperactivity Disorder

Slow, variable, and error-prone performance on speeded reaction time (RT) tasks has been well documented in childhood ADHD, but equally well documented is the context-dependent nature of those deficits, particularly with respect to event rate. As event rates increase (or, as the interstimulus intervals become shorter), RTs decrease, a pattern of performance that has long been interpreted as evidence that cognitive deficits in ADHD are a downstream consequence of a fundamental difficulty in the regulation of arousal to meet task demands. We test the extent to which this is a misinterpretation of the data that occurs when RT and accuracy are considered separately, as is common in neurocognitive research. In two samples of children aged 8-10 with (N = 97; 33 girls) and without (N = 39; 26 girls) ADHD, we used the diffusion model, an influential computational model of RT, to examine the effect of event rate on inhibitory control in a go-no-go task. Contrary to longstanding belief, we found that fast event rates slowed the rate at which children with ADHD accumulated evidence to make a decision to "no-go", as indexed by drift rate. This in turn resulted in a higher proportion of failed inhibits, and occurred despite increased task engagement, as reflected by changes in the starting point of the decision process. Thus, although faster event rates increased task engagement among children with ADHD, the increased engagement was unable to counteract the concurrent slowing of processing speed to "no-go" decisions. Implications for theoretical models of ADHD and treatments are discussed.

Frontal theta accounts for individual differences in the cost of conflict on decision making

Cognitive conflict is often experienced as a difficult, frustrating, and aversive state. Recent studies have indicated that conflict acts as an implicit cost during learning, valuation, and the instantiation of cognitive control. Here we investigated if an implicit manipulation of conflict also influences explicit decision making to risk. Participants were required to perform a Balloon Analogue Risk Task wherein the virtual balloon was inflated by performing a flankers task. By varying the percent of incongruent flanker trials between balloons, we hypothesized that participants would pump the balloon fewer times in conditions of higher conflict and that frontal midline theta would account for significant variance in this relationship. Across two studies, we demonstrate that conflict did not elicit reliable behavioral changes in this task across participants. However, individual differences in frontal theta power accounted for significant variance by predicting diminished balloon pumps. Thus, while conflict costs may act as investments to some individuals (invigorating behavior), it is aversive to others (diminishing behavior), and frontal midline theta power accounts for these varying behavioral tendencies between individuals. These findings demonstrate how frontal midline theta is not only a candidate mechanism for implementing cognitive control, but it is sensitive to the inherent costs therein.

Cost-Benefit Arbitration Between Multiple Reinforcement-Learning Systems

Human behavior is sometimes determined by habit and other times by goal-directed planning. Modern reinforcement-learning theories formalize this distinction as a competition between a computationally cheap but inaccurate model-free system that gives rise to habits and a computationally expensive but accurate model-based system that implements planning. It is unclear, however, how people choose to allocate control between these systems. Here, we propose that arbitration occurs by comparing each system’s task-specific costs and benefits. To investigate this proposal, we conducted two experiments showing that people increase model-based control when it achieves greater accuracy than model-free control, and especially when the rewards of accurate performance are amplified. In contrast, they are insensitive to reward amplification when model-based and model-free control yield equivalent accuracy. This suggests that humans adaptively balance habitual and planned action through on-line cost-benefit analysis.

Quantifying the psychological value of goal achievement

It is often assumed that people put forth the least amount of effort necessary to obtain a reward. This assumption is consistent with so-called "rational" economic models of behavior. Yet these models rarely take into account the motivating effects of goals, which may lead to departures from objective reward maximizing behavior. We present an experiment in which people make a series of prioritization decisions whilst pursuing two approach or avoidance goals. Participants were rewarded $10 if they achieved both goals on a randomly selected trial, and either $0, $2.50, $5, $7.50, or $10 if they achieved only one. Bayesian parameter estimation was used to examine the subjective values that people placed on various goal achievement outcomes. The results suggested that people often discounted the achievement of the first goal, relative to a reward maximizing model, particularly when pursuing avoidance goals. These results were most evident among participants who could obtain the full reward after achieving just one goal, yet behaved as if achieving one goal was only half as valuable as achieving both. Our findings question the notion that people put forth the least amount of effort required to obtain a reward. They suggest that when tasks have explicit goals, people may even sacrifice financial reward to achieve the goals.

Control and Effort Costs Influence the Motivational Consequences of Choice

The act of making a choice, apart from any outcomes the choice may yield, has, paradoxically, been linked to both the enhancement and the detriment of intrinsic motivation. Research has implicated two factors in potentially mediating these contradictory effects: the personal control conferred by a choice and the costs associated with a choice. Across four experiments, utilizing a physical effort task disguised as a simple video game, we systematically varied costs across two levels of physical effort requirements (Low-Requirement, High-Requirement) and control over effort costs across three levels of choice (Free-Choice, Restricted-Choice, and No-Choice) to disambiguate how these factors affect the motivational consequences of choosing within an effortful task. Together, our results indicated that, in the face of effort requirements, illusory control alone may not sufficiently enhance perceptions of personal control to boost intrinsic motivation; rather, the experience of actual control may be necessary to overcome effort costs and elevate performance. Additionally, we demonstrated that conditions of illusory control, while otherwise unmotivating, can through association with the experience of free-choice, be transformed to have a positive effect on motivation.