Reward is a powerful tool to enhance human motor behaviour with previous research showing that during a sequential reaching movement, a monetary incentive leads to increased speed of each movement (motor vigour effect), whilst reward-based performance feedback increases the speed of transition between movements (movement fusion effect). The neurotransmitter dopamine plays a central role in the processing of reward signals and has been implicated to modulate motor vigour and regulate movement fusion. However, in humans, it is unclear if the same dopaminergic mechanism underlies both processes. To address this, we used a complex sequential reaching task in which rewards were based on movement times (MT). Crucially, MTs could be reduced via: 1) enhanced speed of individual movements (motor vigour effect) and/or 2) enhanced speed of transition between movements (movement fusion effect). 95 participants were randomly assigned to a reward or no reward group and were given either 2.5mg of the dopamine antagonist haloperidol or a placebo (control group). An independent decision-making task performed prior to the main experiment suggested that haloperidol was active during the sequential reaching task (positive control). We did not find evidence that haloperidol affected the facilitatory effects of reward on movement fusion. However, we found that haloperidol negated the reward-based effects on motor vigour. Therefore, our results suggest that a D2-antagonist differentially influences reward-based effects on movement vigour and movement fusion, indicating that the dopaminergic mechanisms underlying these two processes may be distinct.

A body of research implicates dopamine in the average speed of simple movements. However, naturalistic movements span a range of different shaped trajectories and rarely proceed at a single constant speed. Instead, speed is reduced when drawing "corners" compared to "straights" (i.e., speed modulation), and the extent of this slowing down is dependent upon the global shape of the movement trajectory (i.e., speed meta-modulation) - for example whether the shape is an ellipse or a rounded square. At present, it is not known how (or whether) dopaminergic function controls continuous changes in speed during movement execution. The current paper reports effects on these kinematic features of movement following two forms of dopamine manipulation: Study One highlights movement differences in individuals with PD both ON and OFF their dopaminergic medication (N = 32); Study Two highlights movement differences in individuals from the general population on haloperidol (a dopamine receptor blocker, or "antagonist") and placebo (N = 43). Evidence is presented implicating dopamine in speed, speed modulation and speed meta-modulation, whereby low dopamine conditions are associated with reductions in these variables. These findings move beyond vigour models implicating dopamine in average movement speed, and towards a conceptualisation that involves the modulation of speed as a function of contextual information.

Motor sequence learning gradually quickens reaction time, suggesting that sequence learning alters motor preparation processes. Interestingly, evidence has shown that preparing sequence movements decreases short intracortical inhibition (SICI) in the contralateral motor cortex (M1), but also that sequence learning alters motor preparation processes in both the contralateral and ipsilateral M1s. Therefore, one possibility is that sequence learning alters the SICI decreases occurring during motor preparation in bilateral M1s. To examine this, two novel hypotheses were tested: unilateral sequence preparation would decrease SICI in bilateral M1s, and sequence learning would alter such bilateral SICI responses. Paired-pulse transcranial magnetic stimulation was delivered over the contralateral and ipsilateral M1s to assess SICI in an index finger muscle during the preparation of sequences initiated by either the right index or little finger. In the absence of sequence learning, SICI decreased in both the contralateral and ipsilateral M1s during the preparation of sequences initiated by the right index finger, suggesting that SICI decreases in bilateral M1s during unilateral motor preparation. As sequence learning progressed, SICI decreased in the contralateral M1 whilst it increased in the ipsilateral M1. Moreover, these bilateral SICI responses were observed at the onset of motor preparation, suggesting that sequence learning altered baseline SICI levels rather than the SICI decreases occurring during motor preparation per se. Altogether, these results suggest that SICI responses in bilateral M1s reflect two motor processes: an acute decrease of inhibition during motor preparation, and a cooperative but bidirectional shift of baseline inhibition levels as sequence learning progresses.

Monetary rewards and punishments enhance motor performance and are associated with corticospinal excitability (CSE) increases within the motor cortex (M1) during movement preparation. However, such CSE changes have unclear origins. Based on converging evidence, one possibility is that they stem from increased glutamatergic (GLUTergic) facilitation and/or decreased type A gamma-aminobutyric acid (GABAA)-mediated inhibition within M1. To investigate this, paired-pulse transcranial magnetic stimulation was used over the left M1 to evaluate intracortical facilitation (ICF) and short intracortical inhibition (SICI), indirect assays of GLUTergic activity and GABAA-mediated inhibition, in an index finger muscle during the preparation of sequences initiated by either the right index or little finger. Behaviourally, rewards and punishments enhanced both reaction and movement time. During movement preparation, regardless of rewards or punishments, ICF increased when the index finger initiated sequences, whereas SICI decreased when both the index and little fingers initiated sequences. This finding suggests that GLUTergic activity increases in a finger-specific manner whilst GABAA-mediated inhibition decreases in a finger-unspecific manner during preparation. In parallel, both rewards and punishments non-specifically increased ICF, but only rewards non-specifically decreased SICI as compared to neutral. This suggests that to enhance performance rewards both increase GLUTergic activity and decrease GABAA-mediated inhibition, whereas punishments selectively increase GLUTergic activity. A control experiment revealed that such changes were not observed post-movement as participants processed reward and punishment feedback, indicating they were selective to movement preparation. Collectively, these results map the intracortical excitability changes in M1 by which incentives enhance motor performance.

Reward is a powerful tool to enhance human motor behaviour with research showing that it promotes motor sequence learning through increases in both motor vigour and movement fusion. Specifically, during a sequential reaching movement, monetary incentive leads to increased speed of each movement (vigour effect), whilst reward-based performance feedback increases speed of transition between movements (fusion effect). Therefore, motor sequence learning can be driven by distinct reward types with dissociable underlying processes. The neurotransmitter dopamine has been implicated to modulate motor vigour and regulate movement fusion. However, in humans, it is unclear if the same dopaminergic mechanism underlies both processes. To address this, we used a complex sequential reaching task in which rewards were based on movement times (MT). Crucially, MTs could be reduced via : 1) enhanced speed of individual movements (vigour effect) and/or 2) enhanced speed of transition between movements (fusion effect). 92 participants were randomly assigned to a reward and no reward group and were given either 2.5mg of the dopamine antagonist haloperidol or a placebo. Our results demonstrate that haloperidol impaired the reward-based effects on motor vigour whilst not affecting movement fusion. Thus, we illustrate that whilst both strategies are reward sensitive, they rely on dissociable mechanisms.

Monetary rewards and punishments enhance motor performance and are associated with corticospinal excitability (CSE) increases within the motor cortex (M1) during movement preparation. However, such CSE changes have unclear origins; they could stem from increased glutamatergic (GLUTergic) facilitation and/or decreased type A gamma-aminobutyric acid (GABA A )-mediated inhibition within M1. To investigate this, paired-pulse transcranial magnetic stimulation was used to assess GLUTergic facilitation and GABA A inhibition within M1 whilst participants prepared to execute 4-element finger-press sequences. Behaviourally, rewards and punishments enhanced both reaction and movement times. Neurochemically, regardless of rewards or punishments, a digit- specific increase in GLUTergic facilitation and digit- unspecific decrease in GABA A inhibition occurred during preparation as movement onset approached. In parallel, both rewards and punishments non-specifically increased GLUTergic facilitation, but only rewards non-specifically decreased GABA A inhibition during preparation. This suggests that, to enhance performance, rewards both increase GLUTergic facilitation and decrease GABA A inhibition whilst punishments selectively increase GLUTergic facilitation. A control experiment revealed that such changes were not observed post-movement as participants processed reward and punishment feedback, indicating they were selective to movement preparation. Collectively, these results map the neurochemical changes in M1 by which incentives enhance motor performance.

Optical markerless hand-tracking systems incorporated into virtual reality (VR) headsets are transforming the ability to assess fine motor skills in VR. This promises to have far-reaching implications for the increased applicability of VR across scientific, industrial, and clinical settings. However, so far, there are little data regarding the accuracy, delay, and overall performance of these types of hand-tracking systems. Here we present a novel methodological framework based on a fixed grid of targets, which can be easily applied to measure these systems' absolute positional error and delay. We also demonstrate a method to assess finger joint-angle accuracy. We used this framework to evaluate the Meta Quest 2 hand-tracking system. Our results showed an average fingertip positional error of 1.1cm, an average finger joint angle error of 9.6∘ and an average temporal delay of 45.0 ms. This methodological framework provides a powerful tool to ensure the reliability and validity of data originating from VR-based, markerless hand-tracking systems.

Although it is well established that motivational factors such as earning more money for performing well improve motor performance, how the motor system implements this improvement remains unclear. For instance, feedback-based control, which uses sensory feedback from the body to correct for errors in movement, improves with greater reward. But feedback control encompasses many feedback loops with diverse characteristics such as the brain regions involved and their response time. Which specific loops drive these performance improvements with reward is unknown, even though their diversity makes it unlikely that they are contributing uniformly. We systematically tested the effect of reward on the latency (how long for a corrective response to arise?) and gain (how large is the corrective response?) of seven distinct sensorimotor feedback loops in humans. Only the fastest feedback loops were insensitive to reward, and the earliest reward-driven changes were consistently an increase in feedback gains, not a reduction in latency. Rather, a reduction of response latencies only tended to occur in slower feedback loops. These observations were similar across sensory modalities (vision and proprioception). Our results may have implications regarding feedback control performance in athletic coaching. For instance, coaching methodologies that rely on reinforcement or 'reward shaping' may need to specifically target aspects of movement that rely on reward-sensitive feedback responses.

Background: Transcranial direct current stimulation (TDCS) is typically applied before or during a task, for periods ranging from 5 to 30 min. Hypothesis: We hypothesise that briefer stimulation epochs synchronous with individual task actions may be more effective. Methods: In two separate experiments, we applied brief bursts of event-related anodal stimulation (erTDCS) to the cerebellum during a visuomotor adaptation task. Results: The first study demonstrated that 1 s duration erTDCS time-locked to the participants' reaching actions enhanced adaptation significantly better than sham. A close replication in the second study demonstrated 0.5 s erTDCS synchronous with the reaching actions again resulted in better adaptation than standard TDCS, significantly better than sham. Stimulation either during the inter-trial intervals between movements or after movement, during assessment of visual feedback, had no significant effect. Because short duration stimulation with rapid onset and offset is more readily perceived by the par-ticipants, we additionally show that a non-electrical vibrotactile stimulation of the scalp, presented with the same timing as the erTDCS, had no significant effect. Conclusions: We conclude that short duration, event related, anodal TDCS targeting the cerebellum enhances motor adaptation compared to the standard model. We discuss possible mechanisms of action and speculate on neural learning processes that may be involved. (c) 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Dystonia is clinically defined as a disorder of posture yet there has been little systematic exploration of postural control in the laboratory. Patients with DYT-TOR1A dystonia held the handle of a planar robotic arm to make point-to-point reaching movements with their symptomatic right arm. Reaches were made from a central start box to eccentric targets (15°, 135°, 225° or 315°). Position was then held within the target box for 10s. Estimation of arm position was dependent on proprioceptive and visual feedback (experimentally manipulated with balanced pseudo-randomization: cursor visible or not visible). During the hold phase, in the dystonia group, mean velocity did not resolve to zero in either feedback condition with increased fluctuations (movements associated with a velocity peak ) consistently interrupting postural stability. By the end of the hold phase, in the dystonia group, a performance segregation across feedback conditions occurred; with visual feedback (high accuracy, low variability, in line with controls); with no visual feedback (low accuracy, high variability, significant deficit). To gain insight into mechanism a reinforcement learning model was able to reproduce empirical data if noise parameters for sensory feedback and central motor instability were varied. By using DYT-TOR1A as a prototype for dystonia, our results refine aetiological models, assist the design of biomarkers and inform rehabilitation strategies.asadnick@sgul.ac.uk|ABN Bursary

Reward has consistently been shown to enhance motor behavior; however, its beneficial effects appear to be largely unspecific. For example, reward is associated with both rapid and training-dependent improvements in performance, with a mechanistic account of these effects currently lacking. Here we tested the hypothesis that these distinct reward-based improvements are driven by dissociable reward types: monetary incentive and performance feedback. Whereas performance feedback provides in-formation on how well a motor task has been completed (knowledge of performance), monetary incentive increases the motiva-tion to perform optimally without providing a performance-based learning signal. Experiment 1 showed that groups who received monetary incentive rapidly improved movement times (MTs), using a novel sequential reaching task. In contrast, only groups with correct performance-based feedback showed learning-related improvements. Importantly, pairing both maximized MT perform-ance gains and accelerated movement fusion. Fusion describes an optimization process during which neighboring sequential movements blend together to form singular actions. Results from experiment 2 served as a replication and showed that fusion led to enhanced performance speed while also improving movement efficiency through increased smoothness. Finally, experi-ment 3 showed that these improvements in performance persist for 24 h even without reward availability. This highlights the dis-sociable impact of monetary incentive and performance feedback, with their combination maximizing performance gains and leading to stable improvements in the speed and efficiency of sequential actions. NEW & NOTEWORTHY Our work provides a mechanistic framework for how reward influences motor behavior. Specifically, we show that rapid improvements in speed and accuracy are driven by reward presented in the form of money, whereas knowledge of performance through performance feedback leads to training-based improvements. Importantly, combining both maximized performance gains and led to improvements in movement quality through fusion, which describes an optimization process during which sequential movements blend into a single action.

Reward can increase the speed and accuracy of movements in both simple and sequential reaching tasks. Two mechanisms are thought to be responsible for this: an increase in maximum velocity, due to increased muscle stiffness, resulting in faster, but energetically inefficient, individual movements; or coarticulation – the blending of sub-movements into single, smoother, more energetically efficient movements. Older adults have shown reduced sensitivity to reward in decision paradigms, but there is little research relating reward and motor performance in older adults. Using a novel online sequential reaching task, we compared the effects of reward on motor performance between young (18-23 years) and older (65-79 years) participants. We found that movement time decreased across training in all groups, and reward invigorated this decrease in both age groups. This suggests that reward is a viable facilitator of motor performance to compensate for age-related motor decline and has the potential for use in the design of rehabilitation programmes for age-related motor deficits or disease. ### Competing Interest Statement The authors have declared no competing interest.

Atypical motor learning has been suggested to underpin the development of motoric challenges (e.g., handwriting difficulties) in autism. Bayesian accounts of autistic cognition propose a mechanistic explanation for differences in the learning process in autism. Specifically, that autistic individuals overweight incoming, at the expense of prior, information and are thus less likely to (a) build stable expectations of upcoming events and (b) react to statistically surprising events. Although Bayesian accounts have been suggested to explain differences in learning across a range of domains, to date, such accounts have not been extended to motor learning. 28 autistic and 35 non-autistic controls (IQ > 70) completed a computerised task in which they learned sequences of actions. On occasional "surprising" trials, an expected action had to be replaced with an unexpected action. Sequence learning was indexed as the reaction time difference between blocks which featured a predictable sequence and those that did not. Surprise-related slowing was indexed as the reaction time difference between surprising and unsurprising trials. No differences in sequence-learning or surprise-related slowing were observed between the groups. Bayesian statistics provided anecdotal to moderate evidence to support the conclusion that sequence learning and surprise-related slowing were comparable between the two groups. We conclude that individuals with autism do not show atypicalities in response to surprising events in the context of motor sequence-learning. These data demand careful consideration of the way in which Bayesian accounts of autism can (and cannot) be extended to the domain of motor learning.

Seeking reward is a powerful tool for shaping human behaviour. While it has been demonstrated that reward invigorates performance of simple movements, its effect on more complex sequential actions is less clear. In addition, it is unknown why reward-based improvements for discrete actions are transient, i.e. performance gains are lost once reward is removed, but appear long lasting for sequential actions. We show across three experiments that reward invigorates sequential reaching performance. Driven by a reward-based increase in speed, movements also exhibited greater coarticulation, smoothness and a closer alignment to a minimum jerk trajectory. Critically, these performance gains were maintained across multiple days even after the removal of reward. We propose that coarticulation, the blending together of sub-movements into a single continuous action, provides a mechanism by which reward can invigorate sequential performance whilst also increasing efficiency. This change in efficiency appears essential for the retention of reward-based improvements in motor behaviour.

From psychology to economics, there has been substantial interest in how costs (e.g., delay, risk) are represented asymmetrically during decision-making when attempting to gain reward or avoid punishment. For example, in decision-making under risk, individuals show a tendency to prefer to avoid punishment rather than to acquire the equivalent reward (loss aversion). Although the cost of physical effort has recently received significant attention, it remains unclear whether loss aversion exists during effort-based decision-making. On the one hand, loss aversion may be hardwired due to asymmetric evolutionary pressure on losses and gains and therefore exists across decision-making contexts. On the other hand, distinct brain regions are involved with different decision costs, making it questionable whether similar asymmetries exist. Here, we demonstrate that young healthy human participants (females, 16; males, 6) exhibit loss aversion during effort-based decision-making by exerting more physical effort to avoid punishment than to gain a same-size reward. Next, we show that medicated Parkinson's disease (PD) patients (females, 9; males, 9) show a reduction in loss aversion compared with age-matched control subjects (females, 11; males, 9). Behavioral and computational analysis revealed that people with PD exerted similar physical effort in return for a reward but were less willing to produce effort to avoid punishment. Therefore, loss aversion is present during effort-based decision-making and can be modulated by altered dopaminergic state. This finding could have important implications for our understanding of clinical disorders that show a reduced willingness to exert effort in the pursuit of reward. SIGNIFICANCE STATEMENT Loss aversion—preferring to avoid punishment rather than to acquire equivalent reward—is an important concept in decision-making under risk. However, little is known about whether loss aversion also exists during decisions where the cost is physical effort. This is surprising given that motor cost shapes human behavior, and a reduced willingness to exert effort is a characteristic of many clinical disorders. Here, we show that healthy human individuals exert more effort to minimize punishment than to maximize reward (loss aversion). We also demonstrate that medicated Parkinson's disease patients exert similar effort to gain reward but less effort to avoid punishment when compared with healthy age-matched control subjects. This indicates that dopamine-dependent loss aversion is crucial for explaining effort-based decision-making.

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.