Visuomotor Mapping Research Articles

The role of training variability for model-based and model-free learning of an arbitrary visuomotor mapping.

A fundamental feature of the human brain is its capacity to learn novel motor skills. This capacity requires the formation of vastly different visuomotor mappings. Using a grid navigation task, we investigated whether training variability would enhance the flexible use of a visuomotor mapping (key-to-direction rule), leading to better generalization performance. Experiments 1 and 2 show that participants trained to move between multiple start-target pairs exhibited greater generalization to both distal and proximal targets compared to participants trained to move between a single pair. This finding suggests that limited variability can impair decisions even in simple tasks without planning. In addition, during the training phase, participants exposed to higher variability were more inclined to choose options that, counterintuitively, moved the cursor away from the target while minimizing its actual distance under the constrained mapping, suggesting a greater engagement in model-based computations. In Experiments 3 and 4, we showed that the limited generalization performance in participants trained with a single pair can be enhanced by a short period of variability introduced early in learning or by incorporating stochasticity into the visuomotor mapping. Our computational modeling analyses revealed that a hybrid model between model-free and model-based computations with different mixing weights for the training and generalization phases, best described participants' data. Importantly, the differences in the model-based weights between our experimental groups, paralleled the behavioral findings during training and generalization. Taken together, our results suggest that training variability enables the flexible use of the visuomotor mapping, potentially by preventing the consolidation of habits due to the continuous demand to change responses.

Visuomotor prediction during action planning in the human frontoparietal cortex and cerebellum.

The concept of forward models in the brain, classically applied to describing on-line motor control, can in principle be extended to action planning, i.e. assuming forward sensory predictions are issued during the mere preparation of movements. To test this idea, we combined a delayed movement task with a virtual reality based manipulation of visuomotor congruence during functional magnetic resonance imaging. Participants executed simple hand movements after a delay. During the delay, two aspects of the upcoming movement could be cued: the movement type and the visuomotor mapping (i.e. congruence of executed hand movements and visual movement feedback by a glove-controlled virtual hand). Frontoparietal areas showed increased delay period activity when preparing pre-specified movements (cued > uncued). The cerebellum showed increased activity during the preparation for incongruent > congruent visuomotor mappings. The left anterior intraparietal sulcus showed an interaction effect, responding most strongly when a pre-specified (cued) movement was prepared under expected visuomotor incongruence. These results suggest that motor planning entails a forward prediction of visual body movement feedback, which can be adjusted in anticipation of nonstandard visuomotor mappings, and which is likely computed by the cerebellum and integrated with state estimates for (planned) control in the anterior intraparietal sulcus.

A Randomization-Based, Model-Free Approach to Functional Neuroimaging: A Proof of Concept.

Functional neuroimaging analysis takes noisy multidimensional measurements as input and produces statistical inferences regarding the functional properties of brain regions as output. Such inferences are most commonly model-based, in that they assume a model of how neural activity translates to the measured signal (blood oxygenation level-dependent signal in the case of functional MRI). The use of models increases statistical sensitivity and makes it possible to ask fine-grained theoretical questions. However, this comes at the cost of making theoretical assumptions about the underlying data-generating process. An advantage of model-free approaches is that they can be used in cases where model assumptions are known not to hold. To this end, we introduce a randomization-based, model-free approach to functional neuroimaging. TWISTER randomization makes it possible to infer functional selectivity from correlations between experimental runs. We provide a proof of concept in the form of a visuomotor mapping experiment and discuss the possible strengths and limitations of this new approach in light of our empirical results.

"Leap before you look": Conditions that suppress explicit, knowledge-based learning during visuomotor adaptation.

When learning a novel visuomotor mapping (e.g., mirror writing), accuracy can improve quickly through explicit, knowledge-based learning (e.g., aim left to go right), but after practice, implicit or procedural learning takes over, producing fast, natural movements. This procedural learning occurs automatically, whereas it has recently been found that knowledge-based learning can be suppressed by the gradual introduction of the novel mapping when participants must make fast movements and visuomotor perturbations are small (e.g., 30° rotations). We explored the range of task instructions, perturbation parameters, and feedback that preclude or encourage this suppression. Using a reaching task with a rotation between screen position and movement direction, we found that knowledge-based learning could be suppressed even for an extreme 90° rotation, but only if it was introduced gradually and only under instructions to move quickly. If the rotation was introduced abruptly or if instructions emphasized accuracy over speed, knowledge-based learning occurred. A second experiment indicated that knowledge-based learning always occurred in the absence of continuous motion feedback, evidenced by the time course of learning, the aftereffects of learning when the rotation was abruptly removed, and the outcome of formal model comparison between a dual-state (procedural and knowledge-based) versus a single-state (procedural only) learning model of the data. A third experiment replicated the findings and verified that the knowledge-based component of the dual-state model corresponded to explicit aiming, whereas the procedural component was slow to unlearn. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The effects of auditory consequences on visuomotor adaptation and motor memory.

Sensorimotor adaptation is a form of motor learning that is essential for maintaining motor performance across the lifespan and is integral to recovery of function after neurological injury. Recent research indicates that experiencing a balance-threatening physical consequence when making a movement error during adaptation can enhance subsequent motor memory. This is perhaps not surprising, as learning to avoid injury is critical for our survival and well-being. Reward and punishment can also differentially modify aspects of motor learning. However, it remains unclear whether other forms of non-physical consequences can impact motor learning. Here we tested the hypothesis that a loud acoustic stimulus linked to a movement error during adaptation could lead to greater generalization and consolidation. Two groups of participants (n = 12 each) adapted to a new, prism-induced visuomotor mapping while performing a precision walking task. One group experienced an unexpected loud acoustic stimulus (85 dB tone) when making foot-placement errors during adaptation. This auditory consequence group adapted faster and showed greater generalization with an interlimb transfer task, but not greater generalization to an obstacle avoidance task. Both groups showed faster relearning (i.e., savings) during the second testing session one week later despite the presence of an interference block of trials following initial adaptation, indicating successful consolidation. However, we did not find significant differences between groups with relearning during session 2. Overall, our results suggest that auditory consequences may serve as a useful method to improve motor learning, though further research is required.

Modulations of stretch reflex by altering visuomotor contexts.

Various functional modulations of the stretch reflex help to stabilize actions, but the computational mechanism behind its context-dependent tuning remains unclear. While many studies have demonstrated that motor contexts associated with the task goal cause functional modulation of the stretch reflex of upper limbs, it is not well understood how visual contexts independent of the task requirements affect the stretch reflex. To explore this issue, we conducted two experiments testing 20 healthy human participants (age range 20-45, average 31.3 ± 9.0), in which visual contexts were manipulated in a visually guided reaching task. During wrist flexion movements toward a visual target, a mechanical load was applied to the wrist joint to evoke stretch reflex of wrist flexor muscle (flexor carpi radialis). The first experiment (n = 10) examined the effect of altering the visuomotor transformation on the stretch reflex that was evaluated with surface electromyogram. We found that the amplitude of the stretch reflex decreased (p = 0.024) when a rotational transformation of 90° was introduced between the hand movement and the visual cursor, whereas the amplitude did not significantly change (p = 0.26) when the rotational transformation was accompanied by a head rotation so that the configuration of visual feedback was maintained in visual coordinates. The results suggest that the stretch reflex was regulated depending on whether the visuomotor mapping had already been acquired or not. In the second experiment (n = 10), we examined how uncertainty in the visual target or hand cursor affects the stretch reflex by removing these visual stimuli. We found that the reflex amplitude was reduced by the disappearance of the hand cursor (p = 0.039), but was not affected by removal of the visual target (p = 0.27), suggesting that the visual state of the body and target contribute differently to the reflex tuning. These findings support the idea that visual updating of the body state is crucial for regulation of quick motor control driven by proprioceptive signals.

The effects of prior exposure to prism lenses on de novo motor skill learning.

Motor learning involves plasticity in a network of brain areas across the cortex and cerebellum. Such traces of learning have the potential to affect subsequent learning of other tasks. In some cases, prior learning can interfere with subsequent learning, but it may be possible to potentiate learning of one task with a prior task if they are sufficiently different. Because prism adaptation involves extensive neuroplasticity, we reasoned that the elevated excitability of neurons could increase their readiness to undergo structural changes, and in turn, create an optimal state for learning a subsequent task. We tested this idea, selecting two different forms of learning tasks, asking whether exposure to a sensorimotor adaptation task can improve subsequent de novo motor skill learning. Participants first learned a new visuomotor mapping induced by prism glasses in which prism strength varied trial-to-trial. Immediately after and the next day, we tested participants on a mirror tracing task, a form of de novo skill learning. Prism-trained and control participants both learned the mirror tracing task, with similar reductions in error and increases in distance traced. Both groups also showed evidence of offline performance gains between the end of day 1 and the start of day 2. However, we did not detect differences between groups. Overall, our results do not support the idea that prism adaptation learning can potentiate subsequent de novo learning. We discuss factors that may have contributed to this result.

Low-Dose Ketamine-Induced Deficits in Arbitrary Visuomotor Mapping in Monkeys.

Ketamine, an NMDA antagonist, is widely used in clinical settings. Recently, low-dose ketamine has gained attention because of its promising role as a rapid antidepressant. However, the effects of low-dose ketamine on brain function, particularly higher cognitive functions of primate brains, are not fully understood. In this study, we used two macaques as subjects and found that acute low-dose ketamine administration significantly impaired the ability for arbitrary visuomotor mapping (AVM), a form of associative learning (AL) essential for flexible behaviors, including executions of learned stimuli-response contingency or learning of new contingencies. We conducted in-depth analyses and identified intrinsic characteristics of these ketamine-induced functional deficits, including lowered accuracy, prolonged time for planning and movement execution, increased tendency to make errors when visual cues are changed from trial to trial, and stronger impact on combining associative learning and another key higher cognitive function, working memory (WM). Our results shed new light on how associative learning relies on the NMDA-mediated synaptic transmission of the brain and contribute to a better understanding of the potential acute side effects of low-dose ketamine on cognition, which can help facilitate its safe usage in medical practice.

Changes in error-correction behavior according to visuomotor maps in goal-directed projection tasks.

Humans can move objects to target positions out of their reach with certain accuracy by throwing or hitting them with tools. However, the outcome-the final object position-after the same movement varies due to various internal and external factors. Therefore, to improve outcome accuracy, humans correct their movements in the following trial as necessary by estimating the relationship between movement and visual outcome (visuomotor map). In the present study, we compared participants' error-correction behaviors to visual errors under three conditions, wherein the relationship between joystick movement direction and cursor projection direction on the monitor covertly differed. This allowed us to examine whether the error-correction behavior changed depending on the visuomotor map. Moreover, to determine whether participants maintain the visuomotor map regardless of the visual error size (cursor projection) and proprioceptive errors (joystick movement), we for the first time focused on whether temporary visual errors deviating from the conventional relationship between joystick movement direction and cursor projection direction (i.e., visual perturbation) are ignored. The visual information was occasionally perturbed in two ways to create a situation wherein the visual error was larger or smaller than the proprioceptive error. We found that participants changed their error-correction behaviors according to the conditions and could ignore visual perturbations. This suggests that humans can be implicitly aware of differences in visuomotor maps and adapt accordingly to visual errors.NEW & NOTEWORTHY We found that participants changed their error-correction behaviors according to the conditions and could ignore visual perturbations. This suggests that humans can be implicitly aware of differences in visuomotor maps and adapt accordingly to visual errors. These findings provide suggestions for how to notice and adapt our movements to the environment and our own dynamically changing conditions, to perform accurate movements consistently.

Brain oscillatory correlates of visuomotor adaptive learning

Sensorimotor adaptation involves the recalibration of the mapping between motor command and sensory feedback in response to movement errors. Although adaptation operates within individual movements on a trial-to-trial basis, it can also undergo learning when adaptive responses improve over the course of many trials. Brain oscillatory activities related to these “adaptation” and “learning” processes remain unclear. The main reason for this is that previous studies principally focused on the beta band, which confined the outcome message to trial-to-trial adaptation. To provide a wider understanding of adaptive learning, we decoded visuomotor tasks with constant, random or no perturbation from EEG recordings in different bandwidths and brain regions using a multiple kernel learning approach. These different experimental tasks were intended to separate trial-to-trial adaptation from the formation of the new visuomotor mapping across trials. We found changes in EEG power in the post-movement period during the course of the visuomotor-constant rotation task, in particular an increased (i) theta power in prefrontal region, (ii) beta power in supplementary motor area, and (iii) gamma power in motor regions. Classifying the visuomotor task with constant rotation versus those with random or no rotation, we were able to relate power changes in beta band mainly to trial-to-trial adaptation to error while changes in theta band would relate rather to the learning of the new mapping. Altogether, this suggested that there is a tight relationship between modulation of the synchronization of low (theta) and higher (essentially beta) frequency oscillations in prefrontal and sensorimotor regions, respectively, and adaptive learning.

Composition and decomposition of visuomotor maps during manual tracking.

Adapting hand movements to changes in our body or the environment is essential for skilled motor behavior, as is the ability to flexibly combine experience gathered in separate contexts. However, it has been shown that when adapting hand movements to two different visuomotor perturbations in succession, interference effects can occur. Here, we investigate whether these interference effects compromise our ability to adapt to the superposition of the two perturbations. Participants tracked with a joystick, a visual target that followed a smooth but an unpredictable trajectory. Four separate groups of participants (total n = 83) completed one block of 50 trials under each of three mappings: one in which the cursor was rotated by 90° (ROTATION), one in which the cursor mimicked the behavior of a mass-spring system (SPRING), and one in which the SPRING and ROTATION mappings were superimposed (SPROT). The order of the blocks differed across groups. Although interference effects were found when switching between SPRING and ROTATION, participants who performed these blocks first performed better in SPROT than participants who had no prior experience with SPRING and ROTATION (i.e., composition). Moreover, participants who started with SPROT exhibited better performance under SPRING and ROTATION than participants who had no prior experience with each of these mappings (i.e., decomposition). Additional analyses confirmed that these effects resulted from components of learning that were specific to the rotational and spring perturbations. These results show that interference effects do not preclude the ability to compose/decompose various forms of visuomotor adaptation.NEW & NOTEWORTHY The ability to compose/decompose task representations is critical for both cognitive and behavioral flexibility. Here, we show that this ability extends to two forms of visuomotor adaptation in which humans have to perform visually guided hand movements. Despite the presence of interference effects when switching between visuomotor maps, we show that participants are able to flexibly compose or decompose knowledge acquired in previous sessions. These results further demonstrate the flexibility of sensorimotor adaptation in humans.

Savings in sensorimotor learning during balance-challenged walking but not reaching.

Safe and successful motor performance relies on the ability to adapt to physiological and environmental change and retain what is learned. An open question is what factors maximize this retention? One overlooked factor is the degree to which balance is challenged during learning. We propose that the greater need for control and/or perceived threat of falling or injury associated with balance-challenging tasks increases the value assigned to maintaining a learned visuomotor mapping (i.e., the new relationship between visual input and motor output). And we propose that a greater-valued mapping is a more retainable mapping, as it serves to benefit future motor performance. Thus, we tested the hypothesis that challenging balance enhances motor memory, reflected by greater recall and faster relearning (i.e., savings). Four groups of participants adapted to a novel visuomotor mapping induced by prism lenses while performing a reaching or walking task, with and without an additional balance challenge. We found that challenging balance did not disrupt visuomotor adaptation during reaching or walking. We then probed recall and savings by having participants repeat the adaptation protocol 1 wk later. For reaching, we found evidence of initial recall, though neither group demonstrated savings upon reexposure to the prisms. In contrast, both walking groups demonstrated significant initial recall and savings. In addition, we found that challenging balance significantly enhanced savings during walking. Taken together, our results demonstrate the robustness of motor memories formed during walking and highlight the potential influence of balance control on sensorimotor learning.NEW & NOTEWORTHY Most everyday tasks challenge our balance. Yet, this aspect of daily motor behavior is often overlooked in adaptation paradigms. Here, we show that challenging balance does not impair sensorimotor adaptation during precision reaching and walking tasks. Furthermore, we show that challenging balance enhances savings of a learned visuomotor mapping during walking. These results provide evidence for the potential performance benefits associated with learning during unconstrained, naturalistic behaviors.

“Neural differences in expert guitarists during over-learned non-standard visuomotor mapping of abstract versus concrete information”

Using visual information to perform actions is a fundamental aspect of human behavior. Musicians commonly translate visual information into action using both concrete and abstract visual information. We exposed expert guitarists to four types of familiar visual depictions of action instruction including musical notation (very abstract), tablature (abstract), chord diagrams (more concrete), and actual pictures of guitars chords being formed (very concrete). These were shown during fMRI scanning as the guitarists formed the appropriate chords (as visually depicted) on a magnet safe guitar fret board with strings, or where they simply viewed the visual stimuli without an action. Whole brain contrasts revealed that the right precuneus was more active for abstract instruction while an occipito-insular circuit was more active for concrete instruction. The current findings highlight that the degree of over-learned visual abstraction is an important factor modulating visual-motor processing.

How aging affects visuomotor adaptation and retention in a precision walking paradigm

Motor learning is a lifelong process. However, age-related changes to musculoskeletal and sensory systems alter the relationship (or mapping) between sensory input and motor output, and thus potentially affect motor learning. Here we asked whether age affects the ability to adapt to and retain a novel visuomotor mapping learned during overground walking. We divided participants into one of three groups (n = 12 each) based on chronological age: a younger-aged group (20–39 years old); a middle-aged group (40–59 years old); and an older-aged group (60–80 years old). Participants learned a new visuomotor mapping, induced by prism lenses, during a precision walking task. We assessed retention one-week later. We did not detect significant effects of age on measures of adaptation or savings (defined as faster relearning). However, we found that older adults demonstrated reduced initial recall of the mapping, reflected by greater foot-placement error during the first adaptation trial one-week later. Additionally, we found that increased age significantly associated with reduced initial recall. Overall, our results suggest that aging does not impair adaptation and that older adults can demonstrate visuomotor savings. However, older adults require some initial context during relearning to recall the appropriate mapping.

Sensorimotor control and linear visuomotor gains.

In everyday life, we often use graphical interfaces where the visual space is mapped to the motor space with a visuomotor gain called the control display gain. One of the key objectives in the field of Human Computer Interaction is to design this control display gain so as to enhance users' performance. Although the control display gain involved in operating systems has been found to improve users' pointing performance, the reasons for this improvement have not yet been fully elucidated, especially because the control display gains on operating systems are both non-constant and non-linear. Here, we tested non-constant but linear velocity-based control display gains to determine which parameters were responsible for pointing performance changes based on analyses of the movement kinematics. Using a Fitts' paradigm, constant gains of 1 and 3 were compared with a linearly increasing gain (i.e., the control display gain increases with the motor velocity) and a decreasing gain (i.e., the control display gain decreases with the motor velocity). Three movements with various indexes of difficulty (ID) were tested (3, 5 and 7 bits). The increasing gain was expected to increase the velocity of the initial impulse phase and decrease that of the correction phase, thus decreasing the movement time (MT), and the contrary in the case of the decreasing gain. Although the decreasing gain increased MT at ID3, the increasing gain was found to be less efficient than the constant gain of 3, probably because a non-constant gain between the motion and its visual consequences disrupted the sensorimotor control. In addition, the kinematic analyses of the movements suggested that the motion profile was planned by the central nervous system based on the visuomotor gain at maximum motor velocity, as common features were observed between the constant gain of 1 and the decreasing gain, and between the constant gain of 3 and the increasing gain. By contrast, the amplitude of the velocity profile seemed to be specific to each particular visuomotor mapping process.

Enhanced visuomotor learning and generalization in expert surgeons.

Although human motor learning has been intensively studied for many decades, it remains unknown whether group differences are present in expert cohorts that must routinely cope with and learn new visuomotor mappings such as expert minimally invasive surgeons. We found that expert surgeons compensate for a visuomotor perturbation more rapidly than naive controls. Modelling indicates that these differences in expert behavioural performance reflects greater trial-to-trial retention, as opposed to greater trial-to-trial learning rate. We also found that surgeons generalize to novel reach directions more broadly than controls, a result which was subsequently confirmed by our modelling. In general, our findings show that minimally invasive surgeons exhibit enhanced visuomotor learning and spatial generalization.

Challenging balance during sensorimotor adaptation increases generalization

From reaching to walking, real-life experience suggests that people can generalize between motor behaviors. One possible explanation for this generalization is that real-life behaviors often challenge our balance. We propose that the exacerbated body motions associated with balance-challenged whole body movements increase the value to the nervous system of using a comprehensive internal model to control the task. Because it is less customized to a specific task, a more comprehensive model is also a more generalizable model. Here we tested the hypothesis that challenging balance during adaptation would increase generalization of a newly learned internal model. We encouraged participants to learn a new internal model using prism lenses that created a new visuomotor mapping. Four groups of participants adapted to prisms while performing either a standing-based reaching or precision walking task, with or without a manipulation that challenged balance. To assess generalization after the adaptation phase, participants performed a single trial of each of the other groups' tasks without prisms. We found that both the reaching and walking balance-challenged groups showed significantly greater generalization to the equivalent, nonadapted task than the balance-unchallenged groups. Additionally, we found some evidence that all groups generalized across tasks, for example, from walking to reaching and vice versa, regardless of balance manipulation. Overall, our results demonstrate that challenging balance increases the degree to which a newly learned internal model generalizes to untrained movements.NEW & NOTEWORTHY Real-life experience indicates that people can generalize between motor behaviors. Here we show that challenging balance during the learning of a new internal model increases the degree of generalization to untrained movements for both reaching and walking tasks. These results suggest that the effects of challenging balance are not specific to the task but instead apply to motor learning more broadly.

From motor to visually guided bimanual affordance learning

The mechanisms of how the brain orchestrates multi-limb joint action have yet to be elucidated and few computational sensorimotor (SM) learning approaches have dealt with the problem of acquiring bimanual affordances. We propose a series of bidirectional (forward/inverse) SM maps and its associated learning processes that generalize from uni- to bimanual interaction (and affordances) naturally, reinforcing the motor equivalence property. The SM maps range from a SM nature to a solely sensory one: full body control, delta SM control (through small action changes), delta sensory co-variation (how body-related perceptual cues covariate with object-related ones). We make several contributions on how these SM maps are learned: (1) Context and Behavior-Based Babbling: generalizing goal babbling to the interleaving of absolute and local goals including guidance of reflexive behaviors; (2) Event-Based Learning: learning steps are driven by visual, haptic events; and (3) Affordance Gradients: the vectorial field gradients in which an object can be manipulated. Our modeling of bimanual affordances is in line with current robotic research in forward visuomotor mappings and visual servoing, enforces the motor equivalence property, and is also consistent with neurophysiological findings like the multiplicative encoding scheme.

Hands Ahead in Mind and Motion: Active Inference in Peripersonal Hand Space.

According to theories of anticipatory behavior control, actions are initiated by predicting their sensory outcomes. From the perspective of event-predictive cognition and active inference, predictive processes activate currently desired events and event boundaries, as well as the expected sensorimotor mappings necessary to realize them, dependent on the involved predicted uncertainties before actual motor control unfolds. Accordingly, we asked whether peripersonal hand space is remapped in an uncertainty anticipating manner while grasping and placing bottles in a virtual reality (VR) setup. To investigate, we combined the crossmodal congruency paradigm with virtual object interactions in two experiments. As expected, an anticipatory crossmodal congruency effect (aCCE) at the future finger position on the bottle was detected. Moreover, a manipulation of the visuo-motor mapping of the participants’ virtual hand while approaching the bottle selectively reduced the aCCE at movement onset. Our results support theories of event-predictive, anticipatory behavior control and active inference, showing that expected uncertainties in movement control indeed influence anticipatory stimulus processing.

Predictive error processing distinguishes between relevant and irrelevant errors after visuomotor learning.

Error processing is an important aspect of learning. The detection and online correction of an error as well as error-based adaptation of subsequent movements enables humans to improve behavior. For this improvement, it is necessary to differentiate between relevant and irrelevant errors. Behavioral adaptations are only reasonable when an error is attributed to one's own behavior and therefore regarded as relevant for subsequent adjustments, whereas irrelevant errors caused by unsystematic external influences should be disregarded. Here, we ask whether error predictions as indexed by the error-related negativity (Ne/ERN) can be used to differentiate relevant and irrelevant errors in movements with a complex visuomotor mapping. Using event-related potentials, we compared the neural activation between relevant (self-induced/internal) errors and irrelevant (externally manipulated) errors in a virtual goal-oriented throwing task. Results show that the Ne/ERN responds more strongly to self-induced errors, while the feedback-related negativity (FRN) more strongly correlates with externally manipulated errors. Moreover, subsequent behavioral adjustments were larger in the relevant compared to the irrelevant error trials. We conclude that predictive processes, marked by the Ne/ERN, can subserve error attribution in naturalistic, complex visuomotor tasks like throwing.