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

Dynamic Self-Regulation and Multiple-Goal Pursuit

Self-regulation is the dynamic process by which people manage competing demands on their time and resources as they strive to achieve desired outcomes, while simultaneously preventing or avoiding undesired outcomes. In this article, we review the current state of knowledge regarding the process by which people manage these types of demands. We review studies in the organizational, cognitive, social psychology, and human factors literatures that have examined the process by which people (a) manage task demands when working on a single task or goal; (b) select which tasks or goals they work on, and the timing and order in which they work on them; and (c) make adjustments to the goals that they are pursuing. We review formal theories that have been developed to account for these phenomena and examine the prospects for an integrative account of self-regulation that can explain the broad range of empirical phenomena examined across different subdisciplines within psychology.

Stages of dysfunctional decision-making in addiction

Drug use is a choice with immediate positive outcomes, but long-term negative consequences. Thus, the repeated use of drugs in the face of negative consequences suggests dysfunction in the cognitive mechanisms underpinning decision-making. This cognitive dysfunction can be mapped into three stages: the formation of preferences involving valuation of decision options; choice implementation including motivation, self-regulation and inhibitory processes; and feedback processing implicating reinforcement learning. This article reviews behavioral studies that have examined alterations in these three stages of decision-making in people with substance use disorders. Relative to healthy individuals, those with alcohol, cannabis, stimulant and opioid use disorders value risky options more highly during the formation of preferences; have a greater appetite for superficially attractive rewards during choice implementation; and are both more efficient in learning from rewards and less efficient in learning from losses during feedback processing. These observed decision-making deficits are most likely due to both premorbid factors and drug-induced effects. Because decision-making deficits have been prospectively associated with a greater risk of drug relapse, we advocate for greater research on modulating the component stages that give rise to dysfunctional decision-making in disorders of addiction.

The emotive nature of conflict monitoring in the medial prefrontal cortex

The detection of conflict between incompatible impulses, thoughts, and actions is a ubiquitous source of motivation across theories of goal-directed action. In this overview, we explore the hypothesis that conflict is emotive, integrating perspectives from affective science and cognitive neuroscience. Initially, we review evidence suggesting that the mental and biological processes that monitor for information processing conflict-particularly those generated by the anterior midcingulate cortex-track the affective significance of conflict and use this signal to motivate increased control. In this sense, variation in control resembles a form of affect regulation in which control implementation counteracts the aversive experience of conflict. We also highlight emerging evidence proposing that states and dispositions associated with acceptance facilitate control by tuning individuals to the emotive nature of conflict, before proposing avenues for future research, including investigating the role of affect in reinforcement learning and decision making.

Modulation of ventral striatal activity by cognitive effort

Effort discounting theory suggests that the value of a reward should be lower if it was effortful to obtain, whereas contrast theory suggests that the contrast between the costly effort and the reward makes the reward seem more valuable. To test these alternative hypotheses, we used functional magnetic resonance imaging (fMRI) as participants engaged in feedback-based learning that required low or high cognitive effort to obtain positive feedback, while the objective amount of information provided by feedback remained constant. In the low effort condition, a single image was presented with four response options. In the high effort condition, two images were presented, each with two response options, and correct feedback was presented only when participants responded correctly to both of the images. Accuracy was significantly lower for the high effort condition, and all participants reported that the high effort condition was more difficult. A region of the ventral striatum selected for sensitivity to feedback value also showed increased activation to feedback presentation associated with the high effort condition relative to the low effort condition, when controlling for activation from corresponding control conditions where feedback was random. These results suggest that increased cognitive effort produces corresponding increases in positive feedback-related ventral striatum activity, in line with the predictions made by contrast theory. The accomplishment of obtaining a hard-earned intrinsic reward, such as positive feedback, may be particularly likely to promote reward-related brain activity.

How effortful is cognitive control? Insights from a novel method measuring single-trial evoked beta-adrenergic cardiac reactivity

The ability to adjust attentional focus to varying levels of task demands depends on the adaptive recruitment of cognitive control processes. The present study investigated for the first time whether the mobilization of cognitive control during response-conflict trials in a flanker task is associated with effort-related sympathetic activity as measured by changes in the RZ-interval at a single-trial level, thus providing an alternative to the pre-ejection period (PEP) which can only be reliably measured in ensemble-averaged data. We predicted that response conflict leads to a physiological orienting response (i.e. heart rate slowing) and increases in effort as reflected by changes in myocardial beta-adrenergic activity (i.e. decreased RZ interval). Our results indeed showed that response conflict led to cardiac deceleration and decreased RZ interval. However, the temporal overlap of the observed heart rate and RZ interval changes suggests that the effect on the latter reflects a change in cardiac pre-load (Frank-Starling mechanism). Our study was thus unable to provide evidence for the expected link between cognitive control and cardiovascular effort. However, it demonstrated that our single-trial analysis enables the assessment of transient changes in cardiac sympathetic activity, thus providing a promising tool for future studies that aim to investigate effort at a single-trial level.

When Does Model-Based Control Pay Off?

Many accounts of decision making and reinforcement learning posit the existence of two distinct systems that control choice: a fast, automatic system and a slow, deliberative system. Recent research formalizes this distinction by mapping these systems to “model-free” and “model-based” strategies in reinforcement learning. Model-free strategies are computationally cheap, but sometimes inaccurate, because action values can be accessed by inspecting a look-up table constructed through trial-and-error. In contrast, model-based strategies compute action values through planning in a causal model of the environment, which is more accurate but also more cognitively demanding. It is assumed that this trade-off between accuracy and computational demand plays an important role in the arbitration between the two strategies, but we show that the hallmark task for dissociating model-free and model-based strategies, as well as several related variants, do not embody such a trade-off. We describe five factors that reduce the effectiveness of the model-based strategy on these tasks by reducing its accuracy in estimating reward outcomes and decreasing the importance of its choices. Based on these observations, we describe a version of the task that formally and empirically obtains an accuracy-demand trade-off between model-free and model-based strategies. Moreover, we show that human participants spontaneously increase their reliance on model-based control on this task, compared to the original paradigm. Our novel task and our computational analyses may prove important in subsequent empirical investigations of how humans balance accuracy and demand.

When you make a choice about what groceries to get for dinner, you can rely on two different strategies. You can make your choice by relying on habit, simply buying the items you need to make a meal that is second nature to you. However, you can also plan your actions in a more deliberative way, realizing that the friend who will join you is a vegetarian, and therefore you should not make the burgers that have become a staple in your cooking. These two strategies differ in how computationally demanding and accurate they are. While the habitual strategy is less computationally demanding (costs less effort and time), the deliberative strategy is more accurate. Scientists have been able to study the distinction between these strategies using a task that allows them to measure how much people rely on habit and planning strategies. Interestingly, we have discovered that in this task, the deliberative strategy does not increase performance accuracy, and hence does not induce a trade-off between accuracy and demand. We describe why this happens, and improve the task so that it embodies an accuracy-demand trade-off, providing evidence for theories of cost-based arbitration between cognitive strategies.

Down with Retirement: Implications of Embodied Cognition for Healthy Aging

Cognitive and neurocognitive approaches to human healthy aging attribute age-related decline to the biologically caused loss of cognitive-control functions. However, an embodied-cognition approach to aging implies a more interactive view according to which cognitive control emerges from, and relies on a person’s active encounters with his or her physical and social environment. We argue that the availability of cognitive-control resources does not only rely on biological processes but also on the degree of active maintenance, that is, on the systematic use of the available control resources. Unfortunately, there is evidence that the degree of actual use might systematically underestimate resource availability, which implies that elderly individuals do not fully exploit their cognitive potential. We discuss evidence for this possibility from three aging-related issues: the reduction of dopaminergic supply, loneliness, and the loss of body strength. All three phenomena point to a downward spiral, in which losses of cognitive-control resources do not only directly impair performance but also more indirectly discourage individuals from making use of them, which in turn suggests underuse and a lack of maintenance—leading to further loss. On the positive side, the possibility of underuse points to not yet fully exploited reservoirs of cognitive control, which calls for more systematic theorizing and experimentation on how cognitive control can be enhanced, as well as for reconsiderations of societal practices that are likely to undermine the active maintenance of control resources—such as retirement laws.

Quantifying motivation with effort-based decision-making paradigms in health and disease

Motivation can be characterized as a series of cost-benefit valuations, in which we weigh the amount of effort we are willing to expend (the cost of an action) in return for particular rewards (its benefits). Human motivation has traditionally been measured with self-report and questionnaire-based tools, but an inherent limitation of these methods is that they are unable to provide a mechanistic explanation of the processes underlying motivated behavior. A major goal of current research is to quantify motivation objectively with effort-based decision-making paradigms, by drawing on a rich literature from nonhuman animals. Here, we review this approach by considering the development of these paradigms in the laboratory setting over the last three decades, and their more recent translation to understanding choice behavior in humans. A strength of this effort-based approach to motivation is that it is capable of capturing the wide range of individual differences, and offers the potential to dissect motivation into its component elements, thus providing the basis for more accurate taxonomic classifications. Clinically, modeling approaches might provide greater sensitivity and specificity to diagnosing disorders of motivation, for example, in being able to detect subclinical disorders of motivation, or distinguish a disorder of motivation from related but separate syndromes, such as depression. Despite the great potential in applying effort-based paradigms to index human motivation, we discuss several caveats to interpreting current and future studies, and the challenges in translating these approaches to the clinical setting.

Patterns of theta oscillation reflect the neural basis of individual differences in epistemic motivation

Theta oscillations in the EEG have been shown to reflect ongoing cognitive processes related to mental effort. Here, we show that the pattern of theta oscillation in response to varying cognitive demands reflects stable individual differences in the personality trait epistemic motivation: Individuals with high levels of epistemic motivation recruit relatively more cognitive resources in response to situations possessing high, compared to low, cognitive demand; individuals with low levels do not show such a specific response. Our results provide direct evidence for the theory of the construct need for cognition and add to our understanding of the neural processes underlying theta oscillations. More generally, we provide an explanation how individual differences in personality traits might be represented on a neural level.

Dopamine Does Double Duty in Motivating Cognitive Effort

Cognitive control is subjectively costly, suggesting that engagement is modulated in relationship to incentive state. Dopamine appears to play key roles. In particular, dopamine may mediate cognitive effort by two broad classes of functions: (1) modulating the functional parameters of working memory circuits subserving effortful cognition, and (2) mediating value-learning and decision-making about effortful cognitive action. Here, we tie together these two lines of research, proposing how dopamine serves "double duty", translating incentive information into cognitive motivation.

Age differences in learning emerge from an insufficient representation of uncertainty in older adults

Healthy aging can lead to impairments in learning that affect many laboratory and real-life tasks. These tasks often involve the acquisition of dynamic contingencies, which requires adjusting the rate of learning to environmental statistics. For example, learning rate should increase when expectations are uncertain (uncertainty), outcomes are surprising (surprise) or contingencies are more likely to change (hazard rate). In this study, we combine computational modelling with an age-comparative behavioural study to test whether age-related learning deficits emerge from a failure to optimize learning according to the three factors mentioned above. Our results suggest that learning deficits observed in healthy older adults are driven by a diminished capacity to represent and use uncertainty to guide learning. These findings provide insight into age-related cognitive changes and demonstrate how learning deficits can emerge from a failure to accurately assess how much should be learned.

The ability to learn decreases with old age especially in a dynamically changing environment, however the precise nature of this decline is not understood. Nassar and colleagues report that older adults show a reduced ability to learn from uncertain outcomes compared to younger adults.

Negative symptoms are associated with an increased subjective cost of cognitive effort

Motivational deficits in schizophrenia are proposed to be attributable in part to abnormal effort-cost computations. Inflated subjective cognitive effort costs may explain diminished functioning in schizophrenia to the extent that they drive avoidance of complex decision-making and planning. Although previous data support inflated subjective physical effort costs for individuals with schizophrenia, evidence on cognitive effort is mixed. We exploited the methodological advantages of a recently developed cognitive effort-discounting paradigm (Westbrook, Kester, & Braver, 2013) to examine effort-cost computations in schizophrenia. The paradigm quantifies subjective costs in terms of explicit, continuous discounting of monetary rewards based on parametrically varied demands (levels N of the N-back working memory task), holding objective features of task duration and reward likelihood constant. Both healthy participants (N = 25) and schizophrenia patients (N = 25) showed systematic influences of reward and task demands on choice patterns. Critically, however, participants with schizophrenia discounted rewards more steeply as a function of effort, indicating that effort was more costly for this group. Moreover, discounting varied robustly with symptomatology, such that schizophrenia patients with greater clinically rated negative symptom severity discounted rewards more steeply. These findings extend the current literature on abnormal-effort cost computations in schizophrenia by establishing a clear relationship between the costliness of cognitive effort and negative symptoms. (PsycINFO Database Record

The Neurobiology of Motivational Deficits in Depression--An Update on Candidate Pathomechanisms

Anhedonia has long been recognized as a central feature of major depression, yet its neurobiological underpinnings remain poorly understood. While clinical definitions of anhedonia have historically emphasized reductions in pleasure and positive emotionality, there has been growing evidence that motivation may be substantially impaired as well. Here, we review recent evidence suggesting that motivational deficits may reflect an important dimension of symptomatology that is discrete from traditional definitions of anhedonia in terms of both behavior and pathophysiology. In summarizing this work, we highlight two candidate neurobiological mechanisms--elevated inflammation and reduced synaptic plasticity--that may underlie observed reductions in motivation and reinforcement learning in depression.

Situational Strategies for Self-Control

Exercising self-control is often difficult, whether declining a drink in order to drive home safely, passing on the chocolate cake to stay on a diet, or ignoring text messages to finish reading an important paper. But enacting self-control is not always difficult, particularly when it takes the form of proactively choosing or changing situations in ways that weaken undesirable impulses or potentiate desirable ones. Examples of situational self-control include the partygoer who chooses a seat far from where drinks are being poured, the dieter who asks the waiter not to bring around the dessert cart, and the student who goes to the library without a cell phone. Using the process model of self-control, we argue that the full range of self-control strategies can be organized by considering the timeline of the developing tempting impulse. Because impulses tend to grow stronger over time, situational self-control strategies-which can nip a tempting impulse in the bud-may be especially effective in preventing undesirable action. Ironically, we may underappreciate situational self-control for the same reason it is so effective-namely, that by manipulating our circumstances to advantage, we are often able to minimize the in-the-moment experience of intrapsychic struggle typically associated with exercising self-control.

Need for Cognitive Closure Modulates How Perceptual Decisions Are Affected by Task Difficulty and Outcome Relevance

The aim of this study was to assess the extent to which Need for Cognitive Closure (NCC), an individual-level epistemic motivation, can explain inter-individual variability in the cognitive effort invested on a perceptual decision making task (the random motion task). High levels of NCC are manifested in a preference for clarity, order and structure and a desire for firm and stable knowledge. The study evaluated how NCC moderates the impact of two variables known to increase the amount of cognitive effort invested on a task, namely task ambiguity (i.e., the difficulty of the perceptual discrimination) and outcome relevance (i.e., the monetary gain associated with a correct discrimination). Based on previous work and current design, we assumed that reaction times (RTs) on our motion discrimination task represent a valid index of effort investment. Task ambiguity was associated with increased cognitive effort in participants with low or medium NCC but, interestingly, it did not affect the RTs of participants with high NCC. A different pattern of association was observed for outcome relevance; high outcome relevance increased cognitive effort in participants with moderate or high NCC, but did not affect the performance of low NCC participants. In summary, the performance of individuals with low NCC was affected by task difficulty but not by outcome relevance, whereas individuals with high NCC were influenced by outcome relevance but not by task difficulty; only participants with medium NCC were affected by both task difficulty and outcome relevance. These results suggest that perceptual decision making is influenced by the interaction between context and NCC.

The role of cognitive effort in subjective reward devaluation and risky decision-making

Motivation is underpinned by cost-benefit valuations where costs—such as physical effort or outcome risk—are subjectively weighed against available rewards. However, in many environments risks pertain not to the variance of outcomes, but to variance in the possible levels of effort required to obtain rewards (effort risks). Moreover, motivation is often guided by the extent to which cognitive—not physical—effort devalues rewards (effort discounting). Yet, very little is known about the mechanisms that underpin the influence of cognitive effort risks or discounting on motivation. We used two cost-benefit decision-making tasks to probe subjective sensitivity to cognitive effort (number of shifts of spatial attention) and to effort risks. Our results show that shifts of spatial attention when monitoring rapidly presented visual stimuli are perceived as effortful and devalue rewards. Additionally, most people are risk-averse, preferring safe, known amounts of effort over risky offers. However, there was no correlation between their effort and risk sensitivity. We show for the first time that people are averse to variance in the possible amount of cognitive effort to be exerted. These results suggest that cognitive effort sensitivity and risk sensitivity are underpinned by distinct psychological and neurobiological mechanisms.

Virtual reality and neuropsychological assessment: The reliability of a virtual kitchen to assess daily-life activities in victims of traumatic brain injury

Traumatic brain injury (TBI) causes impairments affecting instrumental activities of daily living (IADL). However, few studies have considered virtual reality as an ecologically valid tool for the assessment of IADL in patients who have sustained a TBI. The main objective of the present study was to examine the use of the Nonimmersive Virtual Coffee Task (NI-VCT) for IADL assessment in patients with TBI. We analyzed the performance of 19 adults suffering from TBI and 19 healthy controls (HCs) in the real and virtual tasks of making coffee with a coffee machine, as well as in global IQ and executive functions. Patients performed worse than HCs on both real and virtual tasks and on all tests of executive functions. Correlation analyses revealed that NI-VCT scores were related to scores on the real task. Moreover, regression analyses demonstrated that performance on NI-VCT matched real-task performance. Our results support the idea that the virtual kitchen is a valid tool for IADL assessment in patients who have sustained a TBI.

Cognitive effort avoidance and detection in people with schizophrenia

Many people with schizophrenia exhibit avolition, a difficulty initiating and maintaining goal-directed behavior, considered to be a key negative symptom of the disorder. Recent evidence indicates that patients with higher levels of negative symptoms differ from healthy controls in showing an exaggerated cost of the physical effort needed to obtain a potential reward. We examined whether patients show an exaggerated avoidance of cognitive effort, using the demand selection task developed by Kool, McGuire, Rosen, and Botvinick (Journal of Experimental Psychology. General, 139, 665-682, 2010). A total of 83 people with schizophrenia or schizoaffective disorder and 71 healthy volunteers participated in three experiments where instructions varied. In the standard task (Experiment 1), neither controls nor patients showed expected cognitive demand avoidance. With enhanced instructions (Experiment 2), controls demonstrated greater demand avoidance than patients. In Experiment 3, patients showed nonsignificant reductions in demand avoidance, relative to controls. In a control experiment, patients showed significantly reduced ability to detect the effort demands associated with different response alternatives. In both groups, the ability to detect effort demands was associated with increased effort avoidance. In both groups, increased cognitive effort avoidance was associated with higher IQ and general neuropsychological ability. No significant correlations between demand avoidance and negative symptom severity were observed. Thus, it appears that individual differences in general intellectual ability and effort detection are related to cognitive effort avoidance and likely account for the subtle reduction in effort avoidance observed in schizophrenia.

Cognitive cost as dynamic allocation of energetic resources

While it is widely recognized that thinking is somehow costly, involving cognitive effort and producing mental fatigue, these costs have alternatively been assumed to exist, treated as the brain's assessment of lost opportunities, or suggested to be metabolic but with implausible biological bases. We present a model of cognitive cost based on the novel idea that the brain senses and plans for longer-term allocation of metabolic resources by purposively conserving brain activity. We identify several distinct ways the brain might control its metabolic output, and show how a control-theoretic model that models decision-making with an energy budget can explain cognitive effort avoidance in terms of an optimal allocation of limited energetic resources. The model accounts for both subject responsiveness to reward and the detrimental effects of hypoglycemia on cognitive function. A critical component of the model is using astrocytic glycogen as a plausible basis for limited energetic reserves. Glycogen acts as an energy buffer that can temporarily support high neural activity beyond the rate supported by blood glucose supply. The published dynamics of glycogen depletion and repletion are consonant with a broad array of phenomena associated with cognitive cost. Our model thus subsumes both the “cost/benefit” and “limited resource” models of cognitive cost while retaining valuable contributions of each. We discuss how the rational control of metabolic resources could underpin the control of attention, working memory, cognitive look ahead, and model-free vs. model-based policy learning.

Cognitive control predicts use of model-based reinforcement learning

Accounts of decision-making and its neural substrates have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental work suggest that this classic distinction between behaviorally and neurally dissociable systems for habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning (RL), called model-free and model-based RL, but the cognitive or computational processes by which one system may dominate over the other in the control of behavior is a matter of ongoing investigation. To elucidate this question, we leverage the theoretical framework of cognitive control, demonstrating that individual differences in utilization of goal-related contextual information--in the service of overcoming habitual, stimulus-driven responses--in established cognitive control paradigms predict model-based behavior in a separate, sequential choice task. The behavioral correspondence between cognitive control and model-based RL compellingly suggests that a common set of processes may underpin the two behaviors. In particular, computational mechanisms originally proposed to underlie controlled behavior may be applicable to understanding the interactions between model-based and model-free choice behavior.

Separate and overlapping brain areas encode subjective value during delay and effort discounting

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.

Cognitive effort: A neuroeconomic approach

Cognitive effort has been implicated in numerous theories regarding normal and aberrant behavior and the physiological response to engagement with demanding tasks. Yet, despite broad interest, no unifying, operational definition of cognitive effort itself has been proposed. Here, we argue that the most intuitive and epistemologically valuable treatment is in terms of effort-based decision-making, and advocate a neuroeconomics-focused research strategy. We first outline psychological and neuroscientific theories of cognitive effort. Then we describe the benefits of a neuroeconomic research strategy, highlighting how it affords greater inferential traction than do traditional markers of cognitive effort, including self-reports and physiologic markers of autonomic arousal. Finally, we sketch a future series of studies that can leverage the full potential of the neuroeconomic approach toward understanding the cognitive and neural mechanisms that give rise to phenomenal, subjective cognitive effort.

The Impact of Motivation and Task Difficulty on Resource Engagement: Differential Influences on Cardiovascular Responses of Young and Older Adults

This study examined whether the level of cognitive engagement older adults were willing to invest is disproportionately influenced by the personal implications of the task, as suggested by Selective Engagement Theory. We experimentally altered the personal implications of the task by manipulating participants accountability for their performance. Young (N = 50) and older (N = 50) adults performed a memory-search task of moderate difficulty but within the capabilities of both age groups. Both physiological (systolic blood pressure responsivity; SBP-R) and subjective (NASA-TLX) measures of cognitive effort were assessed across all difficulty levels. The results replicated findings from previous research that indicated older adults must exert more effort than younger adults to achieve the same level of objective performance. Most importantly, our results showed that older adults were especially sensitive to our accountability manipulation, with the difference in SBP-R between accountability conditions being greater for older than for young adults. Finally, we found that there was little relation between subjective measures of workload and our physiological measures of task engagement. Together, the results of this study provide continued support for the Selective Engagement Theory.

Mechanisms of motivation-cognition interaction: challenges and opportunities

Recent years have seen a rejuvenation of interest in studies of motivation-cognition interactions arising from many different areas of psychology and neuroscience. The present issue of Cognitive, Affective, & Behavioral Neuroscience provides a sampling of some of the latest research from a number of these different areas. In this introductory article, we provide an overview of the current state of the field, in terms of key research developments and candidate neural mechanisms receiving focused investigation as potential sources of motivation-cognition interaction. However, our primary goal is conceptual: to highlight the distinct perspectives taken by different research areas, in terms of how motivation is defined, the relevant dimensions and dissociations that are emphasized, and the theoretical questions being targeted. Together, these distinctions present both challenges and opportunities for efforts aiming toward a more unified and cross-disciplinary approach. We identify a set of pressing research questions calling for this sort of cross-disciplinary approach, with the explicit goal of encouraging integrative and collaborative investigations directed toward them.

The Effects of Cognitive Control and Time on Frontal Beta Oscillations

Frontal beta oscillations are associated with top-down control mechanisms but also change over time during a task. It is unclear whether change over time represents another control function or a neural instantiation of vigilance decrements over time, the time-on-task effect. We investigated how frontal beta oscillations are modulated by cognitive control and time. We used frontal chronic electrocorticography in monkeys performing a trial-and-error task, comprising search and repetition phases. Specific beta oscillations in the delay period of each trial were modulated by task phase and adaptation to feedback. Beta oscillations in this same period showed a significant within-session change. These separate modulations of beta oscillations did not interact. Crucially, and in contrast to previous investigations, we examined modulations of beta around spontaneous pauses in work. After pauses, the beta power modulation was reset and the cognitive control effect was maintained. Cognitive performance was also maintained whereas behavioral signs of fatigue continued to increase. We propose that these beta oscillations reflect multiple factors contributing to the regulation of cognitive control. Due to the effect of pauses, the time-sensitive factor cannot be a neural correlate of time-on-task but may reflect attentional effort.

Multitasking versus multiplexing: Toward a normative account of limitations in the simultaneous execution of control-demanding behaviors

Why is it that behaviors that rely on control, so striking in their diversity and flexibility, are also subject to such striking limitations? Typically, people cannot engage in more than a few-and usually only a single-control-demanding task at a time. This limitation was a defining element in the earliest conceptualizations of controlled processing; it remains one of the most widely accepted axioms of cognitive psychology, and is even the basis for some laws (e.g., against the use of mobile devices while driving). Remarkably, however, the source of this limitation is still not understood. Here, we examine one potential source of this limitation, in terms of a trade-off between the flexibility and efficiency of representation ("multiplexing") and the simultaneous engagement of different processing pathways ("multitasking"). We show that even a modest amount of multiplexing rapidly introduces cross-talk among processing pathways, thereby constraining the number that can be productively engaged at once. We propose that, given the large number of advantages of efficient coding, the human brain has favored this over the capacity for multitasking of control-demanding processes.

Adults’ age-related differences in strategy perseveration are modulated by response-stimulus intervals and problem features

Ageing results in the tendency of older adults to repeat the same strategy across consecutive problems more often than young adults, even when such strategy perseveration is not appropriate. Here, we examined how these age-related differences in strategy perseveration are modulated by response-stimulus intervals and problem characteristics. We asked participants to select the best strategy while accomplishing a computational estimation task (i.e., provide approximate sums to two-digit addition problems like 38 + 74). We found that participants repeated the same strategy across consecutive problems more often when the duration between their response and next problem display was short (300 ms) than when it was long (1300 ms). We also found more strategy perseverations in older than in young adults under short Response-Stimulus Intervals, but not under long Response-Stimulus Intervals. Finally, age-related differences in strategy perseveration decreased when problem features helped participants to select the best strategy. These modulations of age-related differences in strategy perseveration by response-stimulus intervals and characteristics of target problems are important for furthering our understanding of mechanisms underlying strategy perseveration and, more generally, ageing effects on strategy selection.

Assessment of Adult Age differences in Task Engagement: The Utility of Systolic Blood Pressure

The constructs of effort and engagement are central to many theoretical frameworks associated with the study of aging. Age differences in the effort associated with effortful cognitive operations have been hypothesized to account for aging effects in ability, and shifting goals and motivation have been hypothesized to be associated with differential levels of engagement across situations in younger and older adults. Unfortunately, the assessment of effort and engagement-constructs that we view as relatively synonymous-has suffered in the field of aging due to the lack of well-validated measures. We suggest that systolic blood pressure might provide an easy and valid means for examining age differences in mental effort, and present evidence in support of its usage. Existing findings clearly support its potential utility, but further empirical and theoretical work is necessary.

Motivation and cognitive control: from behavior to neural mechanism

Research on cognitive control and executive function has long recognized the relevance of motivational factors. Recently, however, the topic has come increasingly to center stage, with a surge of new studies examining the interface of motivation and cognitive control. In the present article we survey research situated at this interface, considering work from cognitive and social psychology and behavioral economics, but with a particular focus on neuroscience research. We organize existing findings into three core areas, considering them in the light of currently vying theoretical perspectives. Based on the accumulated evidence, we advocate for a view of control function that treats it as a domain of reward-based decision making. More broadly, we argue that neuroscientific evidence plays a critical role in understanding the mechanisms by which motivation and cognitive control interact. Opportunities for further cross-fertilization between behavioral and neuroscientific research are highlighted.

Selective Engagement of Cognitive Resources: Motivational Influences on Older Adults' Cognitive Functioning

In this article, I present a framework for understanding the impact of aging-related declines in cognitive resources on functioning. I make the assumption that aging is associated with an increase in the costs of cognitive engagement, as reflected in both the effort required to achieve a specific level of task performance and the associated depletion or fatigue effects. I further argue that these costs result in older adults being increasingly selective in the engagement of cognitive resources in response to these declines. This selectivity is reflected in (a) a reduction in the intrinsic motivation to engage in cognitively demanding activities, which, in part, accounts for general reductions in engagement in such activities, and (b) greater sensitivity to the self-related implications of a given task. Both processes are adaptive if viewed in terms of resource conservation, but the former may also be maladaptive to the extent that it results in older adults restricting participation in cognitively demanding activities that could ultimately benefit cognitive health. I review supportive research and make the general case for the importance of considering motivational factors in understanding aging effects on cognitive functioning.

The role of the striatum in effort-based decision-making in the absence of reward

Decision-making involves weighing costs against benefits, for instance, in terms of the effort it takes to obtain a reward of a given magnitude. This evaluation process has been linked to the dorsal anterior cingulate cortex (dACC) and the striatum, with activation in these brain structures reflecting the discounting effect of effort on reward. Here, we investigate how cognitive effort influences neural choice processes in the absence of an extrinsic reward. Using functional magnetic resonance imaging in humans, we used an effort-based decision-making task in which participants were required to choose between two options for a subsequent flanker task that differed in the amount of cognitive effort. Cognitive effort was manipulated by varying the proportion of incongruent trials associated with each choice option. Choice-locked activation in the striatum was higher when participants chose voluntarily for the more effortful alternative but displayed the opposite trend on forced-choice trials. The dACC revealed a similar, yet only trend-level significant, activation pattern. Our results imply that activation levels in the striatum reflect a cost-benefit analysis, in which a balance is made between effort discounting and the intrinsic motivation to choose a cognitively challenging task. Moreover, our findings indicate that it matters whether this challenge is voluntarily chosen or externally imposed. As such, the present findings contrast with classical findings on effort discounting that found reductions in striatum activation for higher effort by finding enhancements of the same neural circuits when a cognitively challenging task is voluntarily selected and does not entail the danger of losing reward.

The economics of cognitive effort

If cognitive effort indexes opportunity costs, it should be investigated like other cost factors including risk and delay. We discuss recent methodological advances in behavioral economics and neuroeconomics, highlighting our own work in measuring the subjective (economic) value of cognitive effort. We discuss the implications of Kurzban et al.'s proposal and how some of its predictions may be untestable without behavioral economic formalisms.

The expected value of control: an integrative theory of anterior cingulate cortex function

The dorsal anterior cingulate cortex (dACC) has a near-ubiquitous presence in the neuroscience of cognitive control. It has been implicated in a diversity of functions, from reward processing and performance monitoring to the execution of control and action selection. Here, we propose that this diversity can be understood in terms of a single underlying function: allocation of control based on an evaluation of the expected value of control (EVC). We present a normative model of EVC that integrates three critical factors: the expected payoff from a controlled process, the amount of control that must be invested to achieve that payoff, and the cost in terms of cognitive effort. We propose that dACC integrates this information, using it to determine whether, where and how much control to allocate. We then consider how the EVC model can explain the diverse array of findings concerning dACC function.

Neural substrates underlying effort computation in schizophrenia

The lack of initiative, drive or effort in patients with schizophrenia is linked to marked functional impairments. However, our assessment of effort and motivation is crude, relying on clinical rating scales based largely on patient recall. In order to better understand the neurobiology of effort in schizophrenia, we need more rigorous measurements of this construct. In the behavioural neuroscience literature, decades of work has been carried out developing various paradigms to examine the neural underpinnings of an animal's willingness to expend effort for a reward. Here, we shall review this literature on the nature of paradigms used in rodents to assess effort, as well as those used in humans. Next, the neurobiology of these effort-based decisions will be discussed. We shall then review what is known about effort in schizophrenia, and what might be inferred from experiments done in other human populations. Lastly, we shall discuss future directions of research that may assist in shedding light on the neurobiology of effort cost computations in schizophrenia.