Dopamine-Dependent Loss Aversion during Effort-Based Decision-Making

The influence of reward and loss outcomes after free- and forced-tasks on voluntary task choice

In four experiments, we investigated the impact of outcomes and processing mode (free versus forced) on subsequent voluntary task-switching behavior. Participants freely chose between two tasks or were forced to perform one, and the feedback they received randomly varied after correct performance (reward or no-reward; loss or no-loss). In general, we reasoned that the most recently applied task goal is usually the most valued one, leading people to prefer task repetitions over switches. However, the task values might be additionally biased by previous outcomes and the previous processing mode. Indeed, negatively reinforcing tasks with no-reward or losses generally resulted in more subsequent switches. Additionally, participants demonstrated a stronger attachment to free- compared to forced-tasks, as indicated by more switches when the previous task was forced, suggesting that people generally value free over forced-choice task goals. Moreover, the reward manipulation had a greater influence on switching behavior following free- compared to forced-tasks in Exp. 1 and Exp. 3, suggesting a stronger emphasis on evaluating rewarding outcomes associated with free-task choices. However, this inflationary effect on task choice seemed to be limited to reward and situations where task choice and performance more strongly overlap. Specifically, there was no evidence that switching behavior was differentially influenced after free-and forced-task as a function of losses (Exp. 2) or reward when task choice and task performance were separated (Exp. 4). Overall, the results provide new insights into how the valuation of task goals based on choice freedom and outcome feedback can influence voluntary task choices.

A novel approach to anxiety level prediction using small sets of judgment and survey variables

Anxiety, a condition characterized by intense fear and persistent worry, affects millions each year and, when severe, is distressing and functionally impairing. Numerous machine learning frameworks have been developed and tested to predict features of anxiety and anxiety traits. This study extended these approaches by using a small set of interpretable judgment variables (n = 15) and contextual variables (demographics, perceived loneliness, COVID-19 history) to (1) understand the relationships between these variables and (2) develop a framework to predict anxiety levels [derived from the State Trait Anxiety Inventory (STAI)]. This set of 15 judgment variables, including loss aversion and risk aversion, models biases in reward/aversion judgments extracted from an unsupervised, short (2-3 min) picture rating task (using the International Affective Picture System) that can be completed on a smartphone. The study cohort consisted of 3476 de-identified adult participants from across the United States who were recruited using an email survey database. Using a balanced Random Forest approach with these judgment and contextual variables, STAI-derived anxiety levels were predicted with up to 81% accuracy and 0.71 AUC ROC. Normalized Gini scores showed that the most important predictors (age, loneliness, household income, employment status) contributed a total of 29-31% of the cumulative relative importance and up to 61% was contributed by judgment variables. Mediation/moderation statistics revealed that the interactions between judgment and contextual variables appears to be important for accurately predicting anxiety levels. Median shifts in judgment variables described a behavioral profile for individuals with higher anxiety levels that was characterized by less resilience, more avoidance, and more indifference behavior. This study supports the hypothesis that distinct constellations of 15 interpretable judgment variables, along with contextual variables, could yield an efficient and highly scalable system for mental health assessment. These results contribute to our understanding of underlying psychological processes that are necessary to characterize what causes variance in anxiety conditions and its behaviors, which can impact treatment development and efficacy.

Acute stress promotes effort mobilization for safety-related goals

Although the acute stress response is a highly adaptive survival mechanism, much remains unknown about how its activation impacts our decisions and actions. Based on its resource-mobilizing function, here we hypothesize that this intricate psychophysiological process may increase the willingness (motivation) to engage in effortful, energy-consuming, actions. Across two experiments (n = 80, n = 84), participants exposed to a validated stress-induction protocol, compared to a no-stress control condition, exhibited an increased willingness to exert physical effort (grip force) in the service of avoiding the possibility of experiencing aversive electrical stimulation (threat-of-shock), but not for the acquisition of rewards (money). Use of computational cognitive models linked this observation to subjective value computations that prioritize safety over the minimization of effort expenditure; especially when facing unlikely threats that can only be neutralized via high levels of grip force. Taken together, these results suggest that activation of the acute stress response can selectively alter the willingness to exert effort for safety-related goals. These findings are relevant for understanding how, under stress, we become motivated to engage in effortful actions aimed at avoiding aversive outcomes.

Predicting COVID-19 Vaccination Uptake Using a Small and Interpretable Set of Judgment and Demographic Variables: Cross-Sectional Cognitive Science Study

BACKGROUND

Despite COVID-19 vaccine mandates, many chose to forgo vaccination, raising questions about the psychology underlying how judgment affects these choices. Research shows that reward and aversion judgments are important for vaccination choice; however, no studies have integrated such cognitive science with machine learning to predict COVID-19 vaccine uptake.

OBJECTIVE

This study aims to determine the predictive power of a small but interpretable set of judgment variables using 3 machine learning algorithms to predict COVID-19 vaccine uptake and interpret what profile of judgment variables was important for prediction.

METHODS

We surveyed 3476 adults across the United States in December 2021. Participants answered demographic, COVID-19 vaccine uptake (ie, whether participants were fully vaccinated), and COVID-19 precaution questions. Participants also completed a picture-rating task using images from the International Affective Picture System. Images were rated on a Likert-type scale to calibrate the degree of liking and disliking. Ratings were computationally modeled using relative preference theory to produce a set of graphs for each participant (minimum R2>0.8). In total, 15 judgment features were extracted from these graphs, 2 being analogous to risk and loss aversion from behavioral economics. These judgment variables, along with demographics, were compared between those who were fully vaccinated and those who were not. In total, 3 machine learning approaches (random forest, balanced random forest [BRF], and logistic regression) were used to test how well judgment, demographic, and COVID-19 precaution variables predicted vaccine uptake. Mediation and moderation were implemented to assess statistical mechanisms underlying successful prediction.

RESULTS

Age, income, marital status, employment status, ethnicity, educational level, and sex differed by vaccine uptake (Wilcoxon rank sum and chi-square P<.001). Most judgment variables also differed by vaccine uptake (Wilcoxon rank sum P<.05). A similar area under the receiver operating characteristic curve (AUROC) was achieved by the 3 machine learning frameworks, although random forest and logistic regression produced specificities between 30% and 38% (vs 74.2% for BRF), indicating a lower performance in predicting unvaccinated participants. BRF achieved high precision (87.8%) and AUROC (79%) with moderate to high accuracy (70.8%) and balanced recall (69.6%) and specificity (74.2%). It should be noted that, for BRF, the negative predictive value was <50% despite good specificity. For BRF and random forest, 63% to 75% of the feature importance came from the 15 judgment variables. Furthermore, age, income, and educational level mediated relationships between judgment variables and vaccine uptake.

CONCLUSIONS

The findings demonstrate the underlying importance of judgment variables for vaccine choice and uptake, suggesting that vaccine education and messaging might target varying judgment profiles to improve uptake. These methods could also be used to aid vaccine rollouts and health care preparedness by providing location-specific details (eg, identifying areas that may experience low vaccination and high hospitalization).

Dopamine Increases Accuracy and Lengthens Deliberation Time in Explicit Motor Skill Learning

Although animal research implicates a central role for dopamine in motor skill learning, a direct causal link has yet to be established in neurotypical humans. Here, we tested if a pharmacological manipulation of dopamine alters motor learning, using a paradigm which engaged explicit, goal-directed strategies. Participants (27 females; 11 males; aged 18-29 years) first consumed either 100 mg of levodopa (n = 19), a dopamine precursor that increases dopamine availability, or placebo (n = 19). Then, during training, participants learnt the explicit strategy of aiming away from presented targets by instructed angles of varying sizes. Targets jumped mid-movement by the instructed aiming angle. Task success was thus contingent upon aiming accuracy and not speed. The effect of the dopamine manipulations on skill learning was assessed during training and after an overnight follow-up. Increasing dopamine availability at training improved aiming accuracy and lengthened reaction times, particularly for larger, more difficult aiming angles, both at training and, importantly, at follow-up, despite prominent session-by-session performance improvements in both accuracy and speed. Exogenous dopamine thus seems to result in a learnt, persistent propensity to better adhere to task goals. Results support the proposal that dopamine is important in engagement of instrumental motivation to optimize adherence to task goals, particularly when learning to execute goal-directed strategies in motor skill learning.

Testing the effect of high-definition transcranial direct current stimulation of the insular cortex to modulate decision-making and executive control

Introduction

Previous neuroimaging evidence highlighted the role of the insular and dorsal anterior cingulate cortex (dACC) in conflict monitoring and decision-making, thus supporting the translational implications of targeting these regions in neuro-stimulation treatments for clinical purposes. Recent advancements of targeting and modeling procedures for high-definition tDCS (HD-tDCS) provided methodological support for the stimulation of otherwise challenging targets, and a previous study confirmed that cathodal HD-tDCS of the dACC modulates executive control and decision-making metrics in healthy individuals. On the other hand, evidence on the effect of stimulating the insula is still needed.

Methods

We used a modeling/targeting procedure to investigate the effect of stimulating the posterior insula on Flanker and gambling tasks assessing, respectively, executive control and both loss and risk aversion in decision-making. HD-tDCS was applied through 6 small electrodes delivering anodal, cathodal or sham stimulation for 20 min in a within-subject offline design with three separate sessions.

Results

Bayesian statistical analyses on Flanker conflict effect, as well as loss and risk aversion, provided moderate evidence for the null model (i.e., absence of HD-tDCS modulation).

Discussion

These findings suggest that further research on the effect of HD-tDCS on different regions is required to define reliable targets for clinical applications. While modeling and targeting procedures for neuromodulation in clinical research could lead to innovative protocols for stand-alone treatment, or possibly in combination with cognitive training, assessing the effectiveness of insula stimulation might require sensitive metrics other than those investigated here.

Bilateral arm movements are coordinated via task-dependent negotiations between independent and codependent control, but not by a "coupling" control policy

Prior research has shown that coordination of bilateral arm movements might be attributed to either control policies that minimize performance and control costs regardless of bilateral symmetry or by control coupling, which activates bilaterally homologous muscles as a single unit to achieve symmetric performance. We hypothesize that independent bimanual control (movements of one arm are performed without influence on the other) and codependent bimanual control (two arms are constrained to move together with high spatiotemporal symmetry) are two extremes on a coordination spectrum that can be negotiated to meet infinite variations in task demands. To better understand and distinguish between these views, we designed a task where minimization of either control costs or asymmetry would yield different patterns of coordination. Participants made bilateral reaches with a shared visual cursor to a midline target. We then covertly varied the gain contribution of either hand to the shared cursor's horizontal position. Across two experiments, we show that bilateral coordination retains high task-dependent sensitivity to subtle visual feedback gain asymmetries applied to the shared cursor. Specifically, we found a change from strong spatial covariation between hands during equal gains to more independent control during asymmetric gains, which occurred rapidly and with high specificity to the dimension of gain manipulation. Furthermore, the extent of spatial covariation was graded to the magnitude of perpendicular gain asymmetry between hands. These findings suggest coordination of bilateral arm movements flexibly maneuvers along a continuous coordination spectrum in a task-dependent manner that cannot be explained by bilateral control coupling.NEW & NOTEWORTHY Minimization of performance and control costs and efferent coupling between bilaterally homologous muscle groups have been separately hypothesized to describe patterns of bimanual coordination. Here, we address whether the mechanisms mediating independent and codependent control between limbs can be weighted for successful task performance. Using bilaterally asymmetric visuomotor gain perturbations, we show bimanual coordination can be characterized as a negotiation along a spectrum between extremes of independent and codependent control, but not efferent control coupling.

Motor Decision-Making as a Common Denominator in Motor Pathology and a Possible Rehabilitation Target

Despite the substantial progress in motor rehabilitation, patient involvement and motivation remain major challenges. They are typically addressed with communicational and environmental strategies, as well as with improved goal-setting procedures. Here we suggest a new research direction and framework involving Neuroeconomics principles to investigate the role of Motor Decision-Making (MDM) parameters in motivational component and motor performance in rehabilitation. We argue that investigating NE principles could bring new approaches aimed at increasing active patient engagement in the rehabilitation process by introducing more movement choice, and adapting existing goal-setting procedures. We discuss possible MDM implementation strategies and illustrate possible research directions using examples of stroke and psychiatric disorders.

Association between cortical gyrification and white matter integrity in spinocerebellar ataxia type 3

Gray matter volume and thickness reductions have been reported in patients with spinocerebellar ataxia type 3 (SCA3), whereas cortical gyrification alterations of this disease remain largely unexplored. Using local gyrification index (LGI) and fractional anisotropy (FA) from structural and diffusion MRI data, this study investigated the cortical gyrification alterations as well as their relationship with white matter microstructural abnormalities in patients with SCA3 (n = 61) compared with healthy controls (n = 69). We found widespread reductions in cortical LGI and white matter FA in patients with SCA3 and that changes in these 2 features were also coupled. In the patient group, the LGI of the left middle frontal gyrus, bilateral insula, and superior temporal gyrus was negatively correlated with the severity of depressive symptoms, and the FA of a cluster in the left cerebellum was negatively correlated with the Scale for the Assessment and Rating of Ataxia scores. Our findings suggest that the gyrification abnormalities observed in this study may account for the clinical heterogeneity in SCA3 and are likely to be mediated by the underlying white matter microstructural abnormalities of this disease.

Decreased sensitivity to loss of options in patients with Parkinson's disease

Humans prefer to have many options when making decisions. When there is a threat of options disappearing, humans invest more to keep these options available, indicating that they are sensitive to the loss of options. This study examined whether patients with Parkinson's disease (PD), a disease characterized by dopamine depletion, try to keep options available when options are disappearing. Twenty-seven PD patients without dementia and 27 healthy controls (HCs) performed the door game, in which participants were presented with multiple alternatives in the form of three doors, each associated with a different point distribution. The participants were asked to maximize their point earnings by finding the best door. The task included two conditions. In the shutter condition, shutters gradually closed on doors that were not chosen; once the shutters completely closed, the door was no longer available. There were no shutters in the control condition. The results revealed that the HCs switched doors more often in the shutter condition than in the control condition, indicating a tendency to keep options available. However, the PD patients did not show such differences between the two conditions. The difference in the number of switches between the shutter and control conditions in the PD patients was significantly positively correlated with the distribution of dopamine transporters in the left striatum, as measured by ¹²³I-ioflupane-SPECT (DaTSCAN) images. These results suggest that PD patients are less sensitive to the loss of options, and this decreased sensitivity may be caused by a decline in dopaminergic neurotransmission.

How Can Animal Models Inform the Understanding of Cognitive Inflexibility in Patients with Anorexia Nervosa?

Deficits in cognitive flexibility are consistently seen in patients with anorexia nervosa (AN). This type of cognitive impairment is thought to be associated with the persistence of AN because it leads to deeply ingrained patterns of thought and behaviour that are highly resistant to change. Neurobiological drivers of cognitive inflexibility have some commonalities with the abnormal brain functional outcomes described in patients with AN, including disrupted prefrontal cortical function, and dysregulated dopamine and serotonin neurotransmitter systems. The activity-based anorexia (ABA) model recapitulates the key features of AN in human patients, including rapid weight loss caused by self-starvation and hyperactivity, supporting its application in investigating the cognitive and neurobiological causes of pathological weight loss. The aim of this review is to describe the relationship between AN, neural function and cognitive flexibility in human patients, and to highlight how new techniques in behavioural neuroscience can improve the utility of animal models of AN to inform the development of novel therapeutics.

Decision neuroscience and neuroeconomics: Recent progress and ongoing challenges

In the past decade, decision neuroscience and neuroeconomics have developed many new insights in the study of decision making. This review provides an overarching update on how the field has advanced in this time period. Although our initial review a decade ago outlined several theoretical, conceptual, methodological, empirical, and practical challenges, there has only been limited progress in resolving these challenges. We summarize significant trends in decision neuroscience through the lens of the challenges outlined for the field and review examples where the field has had significant, direct, and applicable impacts across economics and psychology. First, we review progress on topics including reward learning, explore-exploit decisions, risk and ambiguity, intertemporal choice, and valuation. Next, we assess the impacts of emotion, social rewards, and social context on decision making. Then, we follow up with how individual differences impact choices and new exciting developments in the prediction and neuroforecasting of future decisions. Finally, we consider how trends in decision-neuroscience research reflect progress toward resolving past challenges, discuss new and exciting applications of recent research, and identify new challenges for the field. This article is categorized under: Psychology > Reasoning and Decision Making Psychology > Emotion and Motivation.

High-definition transcranial direct current stimulation of the dorsal anterior cingulate cortex modulates decision-making and executive control

Previous neuroimaging evidence highlights the translational implications of targeting the dorsal anterior cingulate cortex (dACC), i.e. a key node of the networks underlying conflict monitoring and decision-making, in brain stimulation treatments with clinical or rehabilitative purposes. While the optimized modelling of "high-definition" current flows between multiple anode-cathode pairs might, in principle, allow to stimulate an otherwise challenging target, sensitive benchmark metrics of dACC neuromodulation are required to assess the effectiveness of this approach. On this basis, we aimed to assess the modulatory effect of anodal and cathodal high-definition tDCS (HD-tDCS) of the dACC on different facets of executive control and decision-making in healthy young individuals. A combined modelling/targeting procedure provided the optimal montage for the maximum intensity of dACC stimulation with six small "high-definition" electrodes delivering anodal, cathodal or sham HD-tDCS for 20 min in a within-subject design with three separate sessions. Following stimulation, participants performed Flanker and gambling tasks unveiling individual differences in executive control and both loss- and risk-aversion in decision-making, respectively. Compared to both anodal and sham conditions, cathodal dACC stimulation significantly affected task performance by increasing control over the Flanker conflict effect, and both loss and risk-aversion in decision-making. By confirming the feasibility and effectiveness of dACC stimulation with HD-tDCS, these findings highlight the implications of modelling and targeting procedures for neuromodulation in clinical research, whereby innovative protocols might serve as treatment addressing dysfunctional dACC activity, or combined with cognitive training, to enhance higher-order executive functioning in different neuropsychiatric conditions.

Local and distributed cortical markers of effort expenditure during sustained goal pursuit

The adaptive adjustment of behavior in pursuit of desired goals is critical for survival. To accomplish this complex feat, individuals must weigh the potential benefits of a given action against time, energy, and resource costs. Here, we examine brain responses associated with willingness to exert physical effort during the sustained pursuit of desired goals. Our analyses reveal a distributed pattern of brain activity in aspects of ventral medial prefrontal cortex that tracks with trial-level variability in effort expenditure. Indicating the brain represents echoes of effort at the point of feedback, whole-brain searchlights identified signals reflecting past effort expenditure in medial and lateral prefrontal cortices, encompassing broad swaths of frontoparietal and dorsal attention networks. These data have important implications for our understanding of how the brain's valuation mechanisms contend with the complexity of real-world dynamic environments with relevance for the study of behavior across health and disease.

The neural basis of effort valuation: A meta-analysis of functional magnetic resonance imaging studies

Choosing how much effort to expend is critical for everyday decisions. While several neuroimaging studies have examined effort-based decision-making, results have been highly heterogeneous, leaving unclear which brain regions process effort-related costs and integrate them with rewards. We conducted two meta-analyses of functional magnetic resonance imaging data to examine consistent neural correlates of effort demands (23 studies, 15 maps, 549 participants) and net value (15 studies, 11 maps, 428 participants). The pre-supplementary motor area (pre-SMA) scaled positively with pure effort demand, whereas the ventromedial prefrontal cortex (vmPFC) showed the opposite effect. Moreover, regions that have been previously implicated in value integration in other cost domains, such as the vmPFC and ventral striatum, were consistently involved in signaling net value. The opposite response patterns of the pre-SMA and vmPFC imply that they are differentially involved in the representation of effort costs and value integration. These findings provide conclusive evidence that the vmPFC is a central node for net value computation and reveal potential brain targets to treat motivation-related disorders.

Gain-loss asymmetry in delay and effort discounting of different amounts

Loss aversion entails that people attribute greater weight to losses than to equivalent gains. In terms of discounting, it is reflected in a higher discounting rate for gains than for losses. Research on delay discounting indicates that such gain-loss asymmetry may depend on the amount of the outcome being considered. Consequently, here we address the question of how gains and losses are discounted in delay or effort conditions (physical or cognitive) across four outcome amounts. Our results replicate previous findings for intertemporal choices by showing that losses are discounted more slowly than gains, but only for smaller amounts-with no evidence of an asymmetrical evaluation for larger amounts. In physical effort discounting, we found an inverse asymmetry for the smallest amount tested (gains are discounted less steeply than losses). However, this effect was absent for larger amounts. We found no evidence to support a gain-loss asymmetry in the evaluation of gains or losses in cognitive effort. Overall, our findings indicate that loss aversion may not be as pervasive as previously expected, at least when decisions are effort-based.

Action Costs Rapidly and Automatically Interfere with Reward-Based Decision-Making in a Reaching Task

It is widely assumed that we select actions we value the most. While the influence of rewards on decision-making has been extensively studied, evidence regarding the influence of motor costs is scarce. Specifically, how and when motor costs are integrated in the decision process is unclear. Twenty-two right-handed human participants performed a reward-based target selection task by reaching with their right arm toward one of two visual targets. Targets were positioned in different directions according to biomechanical preference, such that one target was systematically associated with a lower motor cost than the other. Only one of the two targets was rewarded, either in a congruent or incongruent manner with respect to the associated motor cost. A timed-response paradigm was used to manipulate participants' reaction times (RT). Results showed that when the rewarded target carried the highest motor cost, movements produced at short RT (<350 ms) were deviated toward the other (i.e., non-rewarded, low-cost (LC) target). In this context participants needed an additional 150-ms delay to reach the same percentage of rewarded trials as when the LC target was rewarded. Crucially, motor costs affected the total earnings of participants. These results demonstrate a robust interference of motor costs in a simple reward-based decision-making task. They point to the rapid and automatic integration of motor costs at an early stage of processing, potentially through the direct modulation of competing action representations in parieto-frontal regions. The progressive overcoming of this bias with increasing RT is likely achieved through top-down signaling pertaining to expected rewards.

Aging Increases Prosocial Motivation for Effort

Social cohesion relies on prosociality in increasingly aging populations. Helping other people requires effort, yet how willing people are to exert effort to benefit themselves and others, and whether such behaviors shift across the life span, is poorly understood. Using computational modeling, we tested the willingness of 95 younger adults (18-36 years old) and 92 older adults (55-84 years old) to put physical effort into self- and other-benefiting acts. Participants chose whether to work and exert force (30%-70% of maximum grip strength) for rewards (2-10 credits) accrued for themselves or, prosocially, for another. Younger adults were somewhat selfish, choosing to work more at higher effort levels for themselves, and exerted less force in prosocial work. Strikingly, compared with younger adults, older people were more willing to put in effort for others and exerted equal force for themselves and others. Increased prosociality in older people has important implications for human behavior and societal structure.

Losses Motivate Cognitive Effort More Than Gains in Effort-Based Decision Making and Performance

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

Reward-Based Improvements in Motor Control Are Driven by Multiple Error-Reducing Mechanisms

Reward has a remarkable ability to invigorate motor behavior, enabling individuals to select and execute actions with greater precision and speed. However, if reward is to be exploited in applied settings, such as rehabilitation, a thorough understanding of its underlying mechanisms is required. In a series of experiments, we first demonstrate that reward simultaneously improves the selection and execution components of a reaching movement. Specifically, reward promoted the selection of the correct action in the presence of distractors, while also improving execution through increased speed and maintenance of accuracy. These results led to a shift in the speed-accuracy functions for both selection and execution. In addition, punishment had a similar impact on action selection and execution, although it enhanced execution performance across all trials within a block, that is, its impact was noncontingent to trial value. Although the reward-driven enhancement of movement execution has been proposed to occur through enhanced feedback control, an untested possibility is that it is also driven by increased arm stiffness, an energy-consuming process that enhances limb stability. Computational analysis revealed that reward led to both an increase in feedback correction in the middle of the movement and a reduction in motor noise near the target. In line with our hypothesis, we provide novel evidence that this noise reduction is driven by a reward-dependent increase in arm stiffness. Therefore, reward drives multiple error-reduction mechanisms which enable individuals to invigorate motor performance without compromising accuracy.SIGNIFICANCE STATEMENT While reward is well-known for enhancing motor performance, how the nervous system generates these improvements is unclear. Despite recent work indicating that reward leads to enhanced feedback control, an untested possibility is that it also increases arm stiffness. We demonstrate that reward simultaneously improves the selection and execution components of a reaching movement. Furthermore, we show that punishment has a similar positive impact on performance. Importantly, by combining computational and biomechanical approaches, we show that reward leads to both improved feedback correction and an increase in stiffness. Therefore, reward drives multiple error-reduction mechanisms which enable individuals to invigorate performance without compromising accuracy. This work suggests that stiffness control plays a vital, and underappreciated, role in the reward-based imporvemenets in motor control.