The dissociable effects of reward on sequential motor behavior.

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 information on how well a motor task has been completed (knowledge of performance), monetary incentive increases the motivation 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 performance 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, experiment 3 showed that these improvements in performance persist for 24 h even without reward availability. This highlights the dissociable 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-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.

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

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.

Domain-Specific Working Memory, But Not Dopamine-Related Genetic Variability, Shapes Reward-Based Motor Learning.

The addition of rewarding feedback to motor learning tasks has been shown to increase the retention of learning, spurring interest in its possible utility for rehabilitation. However, motor tasks using rewarding feedback have repeatedly been shown to lead to great interindividual variability in performance. Understanding the causes of such variability is vital for maximizing the potential benefits of reward-based motor learning. Thus, using a large human cohort of both sexes (n = 241), we examined whether spatial (SWM), verbal, and mental rotation (RWM) working memory capacity and dopamine-related genetic profiles were associated with performance in two reward-based motor tasks. The first task assessed the participant's ability to follow a slowly shifting reward region based on hit/miss (binary) feedback. The second task investigated the participant's capacity to preserve performance with binary feedback after adapting to the rotation with full visual feedback. Our results demonstrate that higher SWM is associated with greater success and an enhanced capacity to reproduce a successful motor action, measured as change in reach angle following reward. In contrast, higher RWM was predictive of an increased propensity to express an explicit strategy when required to make large reach angle adjustments. Therefore, SWM and RWM were reliable, but dissociable, predictors of success during reward-based motor learning. Change in reach direction following failure was also a strong predictor of success rate, although we observed no consistent relationship with working memory. Surprisingly, no dopamine-related genotypes predicted performance. Therefore, working memory capacity plays a pivotal role in determining individual ability in reward-based motor learning.SIGNIFICANCE STATEMENT Reward-based motor learning tasks have repeatedly been shown to lead to idiosyncratic behaviors that cause varying degrees of task success. Yet, the factors determining an individual's capacity to use reward-based feedback are unclear. Here, we assessed a wide range of possible candidate predictors, and demonstrate that domain-specific working memory plays an essential role in determining individual capacity to use reward-based feedback. Surprisingly, genetic variations in dopamine availability were not found to play a role. This is in stark contrast with seminal work in the reinforcement and decision-making literature, which show strong and replicated effects of the same dopaminergic genes in decision-making. Therefore, our results provide novel insights into reward-based motor learning, highlighting a key role for domain-specific working memory capacity.

Reward-driven enhancements in motor control are robust to TMS manipulation.

A wealth of evidence describes the strong positive impact that reward has on motor control at the behavioural level. However, surprisingly little is known regarding the neural mechanisms which underpin these effects, beyond a reliance on the dopaminergic system. In recent work, we developed a task that enabled the dissociation of the selection and execution components of an upper limb reaching movement. Our results demonstrated that both selection and execution are concommitently enhanced by immediate reward availability. Here, we investigate what the neural underpinnings of each component may be. To this end, we aimed to alter the cortical excitability of the ventromedial prefrontal cortex and supplementary motor area using continuous theta-burst transcranial magnetic stimulation (cTBS) in a within-participant design (N = 23). Both cortical areas are involved in determining an individual's sensitivity to reward and physical effort, and we hypothesised that a change in excitability would result in the reward-driven effects on action selection and execution to be altered, respectively. To increase statistical power, participants were pre-selected based on their sensitivity to reward in the reaching task. While reward did lead to enhanced performance during the cTBS sessions and a control sham session, cTBS was ineffective in altering these effects. These results may provide evidence that other areas, such as the primary motor cortex or the premotor area, may drive the reward-based enhancements of motor performance.

Age-dependent Pavlovian biases influence motor decision-making.

Motor decision-making is an essential component of everyday life which requires weighing potential rewards and punishments against the probability of successfully executing an action. To achieve this, humans rely on two key mechanisms; a flexible, instrumental, value-dependent process and a hardwired, Pavlovian, value-independent process. In economic decision-making, age-related decline in risk taking is explained by reduced Pavlovian biases that promote action toward reward. Although healthy ageing has also been associated with decreased risk-taking in motor decision-making, it is currently unknown whether this is a result of changes in Pavlovian biases, instrumental processes or a combination of both. Using a newly established approach-avoidance computational model together with a novel app-based motor decision-making task, we measured sensitivity to reward and punishment when participants (n = 26,532) made a 'go/no-go' motor gamble based on their perceived ability to execute a complex action. We show that motor decision-making can be better explained by a model with both instrumental and Pavlovian parameters, and reveal age-related changes across punishment- and reward-based instrumental and Pavlovian processes. However, the most striking effect of ageing was a decrease in Pavlovian attraction towards rewards, which was associated with a reduction in optimality of choice behaviour. In a subset of participants who also played an independent economic decision-making task (n = 17,220), we found similar decision-making tendencies for motor and economic domains across a majority of age groups. Pavlovian biases, therefore, play an important role in not only explaining motor decision-making behaviour but also the changes which occur through normal ageing. This provides a deeper understanding of the mechanisms which shape motor decision-making across the lifespan.

Contribution of explicit processes to reinforcement-based motor learning.

Despite increasing interest in the role of reward in motor learning, the underlying mechanisms remain ill defined. In particular, the contribution of explicit processes to reward-based motor learning is unclear. To address this, we examined subjects' ( n = 30) ability to learn to compensate for a gradually introduced 25° visuomotor rotation with only reward-based feedback (binary success/failure). Only two-thirds of subjects ( n = 20) were successful at the maximum angle. The remaining subjects initially followed the rotation but after a variable number of trials began to reach at an insufficiently large angle and subsequently returned to near-baseline performance ( n = 10). Furthermore, those who were successful accomplished this via a large explicit component, evidenced by a reduction in reach angle when they were asked to remove any strategy they employed. However, both groups displayed a small degree of remaining retention even after the removal of this explicit component. All subjects made greater and more variable changes in reach angle after incorrect (unrewarded) trials. However, subjects who failed to learn showed decreased sensitivity to errors, even in the initial period in which they followed the rotation, a pattern previously found in parkinsonian patients. In a second experiment, the addition of a secondary mental rotation task completely abolished learning ( n = 10), while a control group replicated the results of the first experiment ( n = 10). These results emphasize a pivotal role of explicit processes during reinforcement-based motor learning, and the susceptibility of this form of learning to disruption has important implications for its potential therapeutic benefits. NEW & NOTEWORTHY We demonstrate that learning a visuomotor rotation with only reward-based feedback is principally accomplished via the development of a large explicit component. Furthermore, this form of learning is susceptible to disruption with a secondary task. The results suggest that future experiments utilizing reward-based feedback should aim to dissect the roles of implicit and explicit reinforcement learning systems. Therapeutic motor learning approaches based on reward should be aware of the sensitivity to disruption.

Delineating cerebellar mechanisms in DYT11 myoclonus-dystonia.

BACKGROUND: Recent research has highlighted the role of the cerebellum in the pathophysiology of myoclonus-dystonia syndrome as a result of mutations in the ɛ-sarcoglycan gene (DYT11). Specifically, a cerebellar-dependent saccadic adaptation task is dramatically impaired in this patient group. OBJECTIVES: The objective of this study was to investigate whether saccadic deficits coexist with impairments of limb adaptation to provide a potential mechanism linking cerebellar dysfunction to the movement disorder within symptomatic body regions. METHODS: Limb adaptation to visuomotor (visual feedback rotated by 30°) and forcefield (force applied by robot to deviate arm) perturbations were examined in 5 patients with DYT11 and 10 aged-matched controls. RESULTS: Patients with DYT11 successfully adapted to both types of perturbation. Modelled and averaged summary metrics that captured adaptation behaviors were equivalent to the control group across conditions. CONCLUSIONS: DYT11 is not characterized by a uniform deficit in adaptation. The previously observed large deficit in saccadic adaption is not reflected in an equivalent deficit in limb adaptation in symptomatic body regions. We suggest potential mechanisms at the root of this discordance and identify key research questions that need future study. © 2018 International Parkinson and Movement Disorder Society.

Predicting explorative motor learning using decision-making and motor noise.

A fundamental problem faced by humans is learning to select motor actions based on noisy sensory information and incomplete knowledge of the world. Recently, a number of authors have asked whether this type of motor learning problem might be very similar to a range of higher-level decision-making problems. If so, participant behaviour on a high-level decision-making task could be predictive of their performance during a motor learning task. To investigate this question, we studied performance during an explorative motor learning task and a decision-making task which had a similar underlying structure with the exception that it was not subject to motor (execution) noise. We also collected an independent measurement of each participant's level of motor noise. Our analysis showed that explorative motor learning and decision-making could be modelled as the (approximately) optimal solution to a Partially Observable Markov Decision Process bounded by noisy neural information processing. The model was able to predict participant performance in motor learning by using parameters estimated from the decision-making task and the separate motor noise measurement. This suggests that explorative motor learning can be formalised as a sequential decision-making process that is adjusted for motor noise, and raises interesting questions regarding the neural origin of explorative motor learning.

Neural changes associated with cerebellar tDCS studied using MR spectroscopy.

Anodal cerebellar transcranial direct current stimulation (tDCS) is known to enhance motor learning, and therefore, has been suggested to hold promise as a therapeutic intervention. However, the neural mechanisms underpinning the effects of cerebellar tDCS are currently unknown. We investigated the neural changes associated with cerebellar tDCS using magnetic resonance spectroscopy (MRS). 34 healthy participants were divided into two groups which received either concurrent anodal or sham cerebellar tDCS during a visuomotor adaptation task. The anodal group underwent an additional session involving MRS in which the main inhibitory and excitatory neurotransmitters: GABA and glutamate (Glu) were measured pre-, during, and post anodal cerebellar tDCS, but without the behavioural task. We found no significant group-level changes in GABA or glutamate during- or post-tDCS compared to pre-tDCS levels, however, there was large degree of variability across participants. Although cerebellar tDCS did not affect visuomotor adaptation, surprisingly cerebellar tDCS increased motor memory retention with this being strongly correlated with a decrease in cerebellar glutamate levels during tDCS across participants. This work provides novel insights regarding the neural mechanisms which may underlie cerebellar tDCS, but also reveals limitations in the ability to produce robust effects across participants and between studies.

No consistent effect of cerebellar transcranial direct current stimulation on visuomotor adaptation.

Cerebellar transcranial direct current stimulation (ctDCS) is known to enhance adaptation to a novel visual rotation (visuomotor adaptation), and it is suggested to hold promise as a therapeutic intervention. However, it is unknown whether this effect is robust across varying task parameters. This question is crucial if ctDCS is to be used clinically, because it must have a consistent and robust effect across a relatively wide range of behaviors. The aim of this study was to examine the effect of ctDCS on visuomotor adaptation across a wide range of task parameters that were systematically varied. Therefore, 192 young healthy individuals participated in 1 of 7 visuomotor adaptation experiments in either an anodal or sham ctDCS group. Each experiment examined whether ctDCS had a positive effect on adaptation when a unique feature of the task was altered: position of the monitor, offline tDCS, use of a tool, and perturbation schedule. Although we initially replicated the previously reported positive effect of ctDCS on visuomotor adaptation, this was not maintained during a second replication study or across a large range of varying task parameters. At the very least, this may call into question the validity of using ctDCS within a clinical context where a robust and consistent effect across behavior would be required.NEW & NOTEWORTHY Cerebellar transcranial direct current stimulation (ctDCS) is known to enhance motor adaptation and thus holds promise as a therapeutic intervention. However, understanding the reliability of ctDCS across varying task parameters is crucial. To examine this, we investigated whether ctDCS enhanced visuomotor adaptation across a range of varying task parameters. We found ctDCS to have no consistent effect on visuomotor adaptation, questioning the validity of using ctDCS within a clinical context.

Reward and punishment enhance motor adaptation in stroke.

BACKGROUND AND OBJECTIVE: The effects of motor learning, such as motor adaptation, in stroke rehabilitation are often transient, thus mandating approaches that enhance the amount of learning and retention. Previously, we showed in young individuals that reward and punishment feedback have dissociable effects on motor adaptation, with punishment improving adaptation and reward enhancing retention. If these findings were able to generalise to patients with stroke, they would provide a way to optimise motor learning in these patients. Therefore, we tested this in 45 patients with chronic stroke allocated in three groups. METHODS: Patients performed reaching movements with their paretic arm with a robotic manipulandum. After training (day 1), day 2 involved adaptation to a novel force field. During the adaptation phase, patients received performance-based feedback according to the group they were allocated: reward, punishment or no feedback (neutral). On day 3, patients readapted to the force field but all groups now received neutral feedback. RESULTS: All patients adapted, with reward and punishment groups displaying greater adaptation and readaptation than the neutral group, irrespective of demographic, cognitive or functional differences. Remarkably, the reward and punishment groups adapted to similar degree as healthy controls. Finally, the reward group showed greater retention. CONCLUSIONS: This study provides, for the first time, evidence that reward and punishment can enhance motor adaptation in patients with stroke. Further research on reinforcement-based motor learning regimes is warranted to translate these promising results into clinical practice and improve motor rehabilitation outcomes in patients with stroke.

Consensus Paper: Towards a Systems-Level View of Cerebellar Function: the Interplay Between Cerebellum, Basal Ganglia, and Cortex.

Despite increasing evidence suggesting the cerebellum works in concert with the cortex and basal ganglia, the nature of the reciprocal interactions between these three brain regions remains unclear. This consensus paper gathers diverse recent views on a variety of important roles played by the cerebellum within the cerebello-basal ganglia-thalamo-cortical system across a range of motor and cognitive functions. The paper includes theoretical and empirical contributions, which cover the following topics: recent evidence supporting the dynamical interplay between cerebellum, basal ganglia, and cortical areas in humans and other animals; theoretical neuroscience perspectives and empirical evidence on the reciprocal influences between cerebellum, basal ganglia, and cortex in learning and control processes; and data suggesting possible roles of the cerebellum in basal ganglia movement disorders. Although starting from different backgrounds and dealing with different topics, all the contributors agree that viewing the cerebellum, basal ganglia, and cortex as an integrated system enables us to understand the function of these areas in radically different ways. In addition, there is unanimous consensus between the authors that future experimental and computational work is needed to understand the function of cerebellar-basal ganglia circuitry in both motor and non-motor functions. The paper reports the most advanced perspectives on the role of the cerebellum within the cerebello-basal ganglia-thalamo-cortical system and illustrates other elements of consensus as well as disagreements and open questions in the field.

The Role of Dopamine in Temporal Uncertainty.

The temporal preparation of motor responses to external events (temporal preparation) relies on internal representations of the accumulated elapsed time (temporal representations) before an event occurs and on estimates about its most likely time of occurrence (temporal expectations). The precision (inverse of uncertainty) of temporal preparation, however, is limited by two sources of uncertainty. One is intrinsic to the nervous system and scales with the length of elapsed time such that temporal representations are least precise for longest time durations. The other is external and arises from temporal variability of events in the outside world. The precision of temporal expectations thus decreases if events become more variable in time. It has long been recognized that the processing of time durations within the range of hundreds of milliseconds (interval timing) strongly depends on dopaminergic (DA) transmission. The role of DA for the precision of temporal preparation in humans, however, remains unclear. This study therefore directly assesses the role of DA in the precision of temporal preparation of motor responses in healthy humans. In a placebo-controlled double-blind design using a selective D2-receptor antagonist (sulpiride) and D1/D2 receptor antagonist (haloperidol), participants performed a variable foreperiod reaching task, under different conditions of internal and external temporal uncertainty. DA blockade produced a striking impairment in the ability of extracting temporal expectations across trials and on the precision of temporal representations within a trial. Large Weber fractions for interval timing, estimated by fitting subjective hazard functions, confirmed that this effect was driven by an increased uncertainty in the way participants were experiencing time. This provides novel evidence that DA regulates the precision with which we process time when preparing for an action.

Laterality Differences in Cerebellar-Motor Cortex Connectivity.

Lateralization of function is an important organizational feature of the motor system. Each effector is predominantly controlled by the contralateral cerebral cortex and the ipsilateral cerebellum. Transcranial magnetic stimulation studies have revealed hemispheric differences in the stimulation strength required to evoke a muscle response from the primary motor cortex (M1), with the dominant hemisphere typically requiring less stimulation than the nondominant. The current study assessed whether the strength of the connection between the cerebellum and M1 (CB-M1), known to change in association with motor learning, have hemispheric differences and whether these differences have any behavioral correlate. We observed, in right-handed individuals, that the connection between the right cerebellum and left M1 is typically stronger than the contralateral network. Behaviorally, we detected no lateralized learning processes, though we did find a significant effect on the amplitude of reaching movements across hands. Furthermore, we observed that the strength of the CB-M1 connection is correlated with the amplitude variability of reaching movements, a measure of movement precision, where stronger connectivity was associated with better precision. These findings indicate that lateralization in the motor system is present beyond the primary motor cortex, and points to an association between cerebellar M1 connectivity and movement execution.

Age-dependent distractor suppression across the vision and motor domain.

The ability to inhibit distracting information-distractor suppression-is a fundamental process for the visual and motor systems. Whereas aging is typically linked to a general decline in cognitive processing, a specific impairment in distractor suppression is found during visual attention tasks. Despite this, the effect of aging on a human's capacity to inhibit distracting information during a motor task is currently unknown. Therefore, we tested the ability of young and older adults to inhibit distracting information during a visual attention (global-local) and a motor (reaching) task. When faced with distractors, younger and older adults displayed significant behavioral impairments (accuracy and speed) across both tasks. However, these deficits were substantially enhanced in older adults. Intriguingly, the amount of distractor impairment observed within each participant was correlated across the visual and motor tasks, irrespective of age group. Thus, while all participants' ability to inhibit distractors was correlated across the visual and motor domain, older adults displayed a generalized distractor inhibition deficit. We propose that a shift from proactive to reactive control in older adults could explain such impairment. These results may have important implications regarding the ability of older adults to effectively deal with distractors during complex visuomotor tasks such as driving.

Two distinct interneuron circuits in human motor cortex are linked to different subsets of physiological and behavioral plasticity.

How does a single brain region participate in multiple behaviors? Here we argue that two separate interneuron circuits in the primary motor cortex (M1) contribute differently to two varieties of physiological and behavioral plasticity. To test this in human brain noninvasively, we used transcranial magnetic stimulation (TMS) of M1 hand area to activate two independent sets of synaptic inputs to corticospinal neurons by changing the direction of current induced in the brain: posterior-to-anterior current (PA inputs) and anterior-to-posterior current (AP inputs). We demonstrate that excitability changes produced by repetitive activation of AP inputs depend on cerebellar activity and selectively alter model-based motor learning. In contrast, the changes observed with repetitive stimulation of PA inputs are independent of cerebellar activity and specifically modulate model-free motor learning. The findings are highly suggestive that separate circuits in M1 subserve different forms of motor learning.

The role of dopamine in motor flexibility.

Humans carry out many daily tasks in a seemingly automatic fashion. However, when unexpected changes in the environment occur, we have the capacity to inhibit prepotent behavior and replace it with an alternative one. Such behavioral flexibility is a hallmark of executive functions. The neurotransmitter dopamine is known to be crucial for fast, efficient, and accurate cognitive flexibility. Despite the perceived similarities between cognitive and motor flexibility, less is known regarding the role of dopamine within the motor domain. Therefore, the aim of this study was to determine the role of dopamine in motor flexibility. In a double-blind, five-session, within-subject pharmacological experiment, human participants performed an RT task within a probabilistic context that was either predictable or unpredictable. The probabilistic nature of the predictable context resulted in prediction errors. This required participants to replace the prepotent or prepared action with an unprepared action (motor flexibility). The task was overlearned, and changes in context were explicitly instructed, thus controlling for contributions from other dopamine-related processes such as probabilistic or reversal learning and interactions with other types of uncertainty. We found that dopamine receptor blockade by high-dose haloperidol (D1/D2 dopamine receptors) impaired participants' ability to react to unexpected events occurring in a predictable context, which elicit large prediction errors and necessitate motor flexibility. This effect was not observed with selective D2 receptor blockade (sulpiride), with a general increase in tonic dopamine levels (levodopa), or during an unpredictable context, which evoked minimal prediction error. We propose that dopamine is vital in responding to low-level prediction errors about stimulus outcome that requires motor flexibility.

Punishment-induced behavioral and neurophysiological variability reveals dopamine-dependent selection of kinematic movement parameters.

Action selection describes the high-level process that selects between competing movements. In animals, behavioral variability is critical for the motor exploration required to select the action that optimizes reward and minimizes cost/punishment and is guided by dopamine (DA). The aim of this study was to test in humans whether low-level movement parameters are affected by punishment and reward in ways similar to high-level action selection. Moreover, we addressed the proposed dependence of behavioral and neurophysiological variability on DA and whether this may underpin the exploration of kinematic parameters. Participants performed an out-and-back index finger movement and were instructed that monetary reward and punishment were based on its maximal acceleration (MA). In fact, the feedback was not contingent on the participant's behavior but predetermined. Blocks highly biased toward punishment were associated with increased MA variability relative to blocks either with reward or without feedback. This increase in behavioral variability was positively correlated with neurophysiological variability, as measured by changes in corticospinal excitability with transcranial magnetic stimulation over the primary motor cortex. Following the administration of a DA antagonist, the variability associated with punishment diminished and the correlation between behavioral and neurophysiological variability no longer existed. Similar changes in variability were not observed when participants executed a predetermined MA, nor did DA influence resting neurophysiological variability. Thus, under conditions of punishment, DA-dependent processes influence the selection of low-level movement parameters. We propose that the enhanced behavioral variability reflects the exploration of kinematic parameters for less punishing, or conversely more rewarding, outcomes.

Normal motor adaptation in cervical dystonia: a fundamental cerebellar computation is intact.

The potential role of the cerebellum in the pathophysiology of dystonia has become a focus of recent research. However, direct evidence for a cerebellar contribution in humans with dystonia is difficult to obtain. We examined motor adaptation, a test of cerebellar function, in 20 subjects with primary cervical dystonia and an equal number of aged matched controls. Adaptation to both visuomotor (distorting visual feedback by 30°) and forcefield (applying a velocity-dependent force) conditions were tested. Our hypothesis was that cerebellar abnormalities observed in dystonia research would translate into deficits of cerebellar adaptation. We also examined the relationship between adaptation and dystonic head tremor as many primary tremor models implicate the cerebellothalamocortical network which is specifically tested by this motor paradigm. Rates of adaptation (learning) in cervical dystonia were identical to healthy controls in both visuomotor and forcefield tasks. Furthermore, the ability to adapt was not clearly related to clinical features of dystonic head tremor. We have shown that a key motor control function of the cerebellum is intact in the most common form of primary dystonia. These results have important implications for current anatomical models of the pathophysiology of dystonia. It is important to attempt to progress from general statements that implicate the cerebellum to a more specific evidence-based model. The role of the cerebellum in this enigmatic disease perhaps remains to be proven.