Short-term motor plasticity revealed in a visuomotor decision-making task

Short-Term Modulation of Online Monocular Visuomotor Function

Previous literature suggests that correcting ongoing movements is more effective when using the dominant limb and seeing with the dominant eye. Specifically, individuals are more effective at adjusting their movement to account for an imperceptibly perturbed or changed target location (i.e., online movement correction), when vision is available to the dominant eye. However, less is known if visual-motor functions based on monocular information can undergo short-term neuroplastic changes after a bout of practice, to improve online correction processes. Participants (n = 12) performed pointing movements monocularly and their ability to correct their movement towards an imperceptibly displaced target was assessed. On the first day, the eye associated with smaller correction amplitudes was exclusively trained during acquisition. While correction amplitude was assessed again with both eyes monocularly, only the eye with smaller correction amplitudes in the pre-test showed significant improvement in delayed retention. These results indicate that monocular visuomotor pathways can undergo short-term neuroplastic changes.

Decision heuristics in contexts integrating action selection and execution

Heuristics can inform human decision making in complex environments through a reduction of computational requirements (accuracy-resource trade-off) and a robustness to overparameterisation (less-is-more). However, tasks capturing the efficiency of heuristics typically ignore action proficiency in determining rewards. The requisite movement parameterisation in sensorimotor control questions whether heuristics preserve efficiency when actions are nontrivial. We developed a novel action selection-execution task requiring joint optimisation of action selection and spatio-temporal skillful execution. State-appropriate choices could be determined by a simple spatial heuristic, or by more complex planning. Computational models of action selection parsimoniously distinguished human participants who adopted the heuristic from those using a more complex planning strategy. Broader comparative analyses then revealed that participants using the heuristic showed combined decisional (selection) and skill (execution) advantages, consistent with a less-is-more framework. In addition, the skill advantage of the heuristic group was predominantly in the core spatial features that also shaped their decision policy, evidence that the dimensions of information guiding action selection might be yoked to salient features in skill learning.

Action planning and control under uncertainty emerge through a desirability-driven competition between parallel encoding motor plans

Living in an uncertain world, nearly all of our decisions are made with some degree of uncertainty about the consequences of actions selected. Although a significant progress has been made in understanding how the sensorimotor system incorporates uncertainty into the decision-making process, the preponderance of studies focus on tasks in which selection and action are two separate processes. First people select among alternative options and then initiate an action to implement the choice. However, we often make decisions during ongoing actions in which the value and availability of the alternatives can change with time and previous actions. The current study aims to decipher how the brain deals with uncertainty in decisions that evolve while acting. To address this question, we trained individuals to perform rapid reaching movements towards two potential targets, where the true target location was revealed only after the movement initiation. We found that reaction time and initial approach direction are correlated, where initial movements towards intermediate locations have longer reaction times than movements that aim directly to the target locations. Interestingly, the association between reaction time and approach direction was independent of the target probability. By modeling the task within a recently proposed neurodynamical framework, we showed that action planning and control under uncertainty emerge through a desirability-driven competition between motor plans that are encoded in parallel.

Attentional capture in goal-directed action during childhood, adolescence, and early adulthood

Attentional capture occurs when salient but task-irrelevant information disrupts our ability to respond to task-relevant information. Although attentional capture costs have been found to decrease between childhood and adulthood, it is currently unclear the extent to which such age-related changes reflect an improved ability to recover from attentional capture or to avoid attentional capture. In addition, recent research using hand-tracking techniques with adults indicates that attentional capture by a distractor can generate response activations corresponding to the distractor's location, consistent with action-centered models of attention. However, it is unknown whether attentional capture can also result in the capture of action in children and adolescents. Therefore, we presented 5-year-olds, 9-year-olds, 13- and 14-year-olds, and adults (N = 96) with a singleton search task in which participants responded by reaching to touch targets on a digital display. Consistent with action-centered models of attention, distractor effects were evident in each age group's movement trajectories. In contrast to movement trajectories, movement times revealed significant age-related reductions in the costs of attentional capture, suggesting that age-related improvements in attentional control may be driven in part by an enhanced ability to recover from-as opposed to avoid-attentional capture. Children's performance was also significantly affected by response repetition effects, indicating that children may be more susceptible to interference from a wider range of task-irrelevant factors than adults. In addition to presenting novel insights into the development of attention and action, these results highlight the benefits of incorporating hand-tracking techniques into developmental research.

Reaching for known unknowns: Rapid reach decisions accurately reflect the future state of dynamic probabilistic information

Everyday tasks such as catching a ball appear effortless, but in fact require complex interactions and tight temporal coordination between the brain's visual and motor systems. What makes such interceptive actions particularly impressive is the capacity of the brain to account for temporal delays in the central nervous system-a limitation that can be mitigated by making predictions about the environment as well as one's own actions. Here, we wanted to assess how well human participants can plan an upcoming movement based on a dynamic, predictable stimulus that is not the target of action. A central stationary or rotating stimulus determined the probability that each of two potential targets would be the eventual target of a rapid reach-to-touch movement. We examined the extent to which reach movement trajectories convey internal predictions about the future state of dynamic probabilistic information conveyed by the rotating stimulus. We show that movement trajectories reflect the target probabilities determined at movement onset, suggesting that humans rapidly and accurately integrate visuospatial predictions and estimates of their own reaction times to effectively guide action.

Repetita iuvant: repetition facilitates online planning of sequential movements

Beyond being essential for long-term motor-skill development, movement repetition has immediate benefits on performance, increasing speed and accuracy of a second execution. While repetition effects have been reported for single reaching movements, it has yet to be determined whether they also occur for movement sequences, and what aspects of sequence production are improved. We addressed these questions in two behavioral experiments using a discrete sequence production (DSP) task in which human volunteers had to perform short sequences of finger movements. In experiment 1, we presented participants with randomly varying sequences and manipulated 1) whether the same sequence was repeated on successive trials and 2) whether participants had to execute the sequence (Go) or not (No-Go). We establish that sequence repetition led to immediate improvements in speed without associated accuracy costs. The largest benefit was observed in the middle part of a sequence, suggesting that sequence repetition facilitated online planning. This claim was further supported by experiment 2, in which we kept a set of sequences fixed throughout the experiment, thus allowing participants to develop sequence-specific learning: once the need for online planning decreased, the benefit of repetition disappeared. Finally, we found that repetition-related improvements only occurred for the trials that had been preceded by sequence production, suggesting that action selection and sequence preplanning may not be sufficient to reap the benefits of repetition. Together, these results show that repetition can enhance representations at the level of movement sequences (rather than of individual movements) and facilitate online planning.NEW & NOTEWORTHY Even for overlearned motor skills such as reaching, movement repetition improves performance. How brain processes associated with motor planning or execution benefit from repetition, however, remains unclear. We report the novel finding of repetition effects for sequential movements. Our results show that repetition benefits are tied to improved online planning of upcoming sequence elements. We also highlight how actual movement experience appears to be more beneficial than mental rehearsal for observing short-term repetition effects.

Increased preparation time reduces, but does not abolish, action history bias of saccadic eye movements

The characteristics of movements are strongly history-dependent. Marinovic et al. (Marinovic W, Poh E, de Rugy A, Carroll TJ. eLife 6: e26713, 2017) showed that past experience influences the execution of limb movements through a combination of temporally stable processes that are strictly use dependent and dynamically evolving and context-dependent processes that reflect prediction of future actions. Here we tested the basis of history-dependent biases for multiple spatiotemporal features of saccadic eye movements under two preparation time conditions (long and short). Twenty people performed saccades to visual targets. To prompt context-specific expectations of most likely target locations, 1 of 12 potential target locations was specified on ~85% of the trials and each remaining target was presented on ~1% trials. In long preparation trials participants were shown the location of the next target 1 s before its presentation onset, whereas in short preparation trials each target was first specified as the cue to move. Saccade reaction times and direction were biased by recent saccade history but according to distinct spatial tuning profiles. Biases were purely expectation related for saccadic reaction times, which increased linearly as the distance from the repeated target location increased when preparation time was short but were similar to all targets when preparation time was long. By contrast, the directions of saccades were biased toward the repeated target in both preparation time conditions, although to a lesser extent when the target location was precued (long preparation). The results suggest that saccade history affects saccade dynamics via both use- and expectation-dependent mechanisms and that movement history has dissociable effects on reaction time and saccadic direction. NEW & NOTEWORTHY The characteristics of our movements are influenced not only by concurrent sensory inputs but also by how we have moved in the past. For limb movements, history effects involve both use-dependent processes due strictly to movement repetition and processes that reflect prediction of future actions. Here we show that saccade history also affects saccade dynamics via use- and expectation-dependent mechanisms but that movement history has dissociable effects on saccade reaction time and direction.

Confidence judgments during ratio comparisons reveal a Bayesian bias

Rational numbers are essential in mathematics and decision-making but humans often and erroneously rely on the magnitude of the numerator or denominator to determine the relative size of a quotient. The source of this flawed whole number strategy is poorly understood. Here we test the Bayesian hypothesis that the human bias toward large values in the numerator or denominator of a ratio estimate is the result of higher confidence in large samples. Larger values are considered a better (more certain) instance of that ratio than the same ratio composed of smaller values. We collected confidence measures explicitly (Experiment 1) and implicitly (Experiment 2) during subjects' comparisons of non-symbolic proportions (images with arrays of orange and blue dots). We manipulated the discernibility of the fractions to control difficulty and varied the cardinality and congruency of the numerators, denominators, and ratio values (e.g. 8/20 vs. 5/10 and 16/40 vs. 10/20). The results revealed that subjects' confidence during ratio comparisons was modulated by the numerical magnitude of the fraction's components, consistent with a Bayesian perception of relative ratios. The results suggest that the large number bias could arise from greater confidence in large samples.

Action history influences subsequent movement via two distinct processes

The characteristics of goal-directed actions tend to resemble those of previously executed actions, but it is unclear whether such effects depend strictly on action history, or also reflect context-dependent processes related to predictive motor planning. Here we manipulated the time available to initiate movements after a target was specified, and studied the effects of predictable movement sequences, to systematically dissociate effects of the most recently executed movement from the movement required next. We found that directional biases due to recent movement history strongly depend upon movement preparation time, suggesting an important contribution from predictive planning. However predictive biases co-exist with an independent source of bias that depends only on recent movement history. The results indicate that past experience influences movement execution through a combination of temporally-stable processes that are strictly use-dependent, and dynamically-evolving and context-dependent processes that reflect prediction of future actions.

Rapid target foraging with reach or gaze: The hand looks further ahead than the eye

Real-world tasks typically consist of a series of target-directed actions and often require choices about which targets to act on and in what order. Such choice behavior can be assessed from an optimal foraging perspective whereby target selection is shaped by a balance between rewards and costs. Here we evaluated such decision-making in a rapid movement foraging task. On a given trial, participants were presented with 15 targets of varying size and value and were instructed to harvest as much reward as possible by either moving a handle to the targets (hand task) or by briefly fixating them (eye task). The short trial duration enabled participants to harvest about half the targets, ensuring that total reward was due to choice behavior. We developed a probabilistic model to predict target-by-target harvesting choices that considered the rewards and movement-related costs (i.e., target distance and size) associated with the current target as well as future targets. In the hand task, in comparison to the eye task, target choice was more strongly influenced by movement-related costs and took into account a greater number of future targets, consistent with the greater costs associated with arm movement. In both tasks, participants exhibited near-optimal behaviour and in a constrained version of the hand task in which choices could only be based on target positions, participants consistently chose among the shortest movement paths. Our results demonstrate that people can rapidly and effectively integrate values and movement-related costs associated with current and future targets when sequentially harvesting targets.

Many natural tasks involve a series of decisions about which target to acquire next, either with our gaze or hand. We examined the factors influencing such decisions using a task in which targets of varying value and size are sequentially acquired by eye or hand movements. By developing a probabilistic model of decision-making behavior we show that eye movement decisions are made in isolation, independent of potential future targets, and are primarily determined by target value. In contrast, hand movement decisions consider multiple future targets and are strongly shaped by movement-related costs. By examining decision-making in sequential actions, our results and model represent a significant advance over previous work that has focused primarily on decisions about single actions.

Rapid Automatic Motor Encoding of Competing Reach Options

Mounting neural evidence suggests that, in situations in which there are multiple potential targets for action, the brain prepares, in parallel, competing movements associated with these targets, prior to implementing one of them. Central to this interpretation is the idea that competing viewed targets, prior to selection, are rapidly and automatically transformed into corresponding motor representations. Here, by applying target-specific, gradual visuomotor rotations and dissociating, unbeknownst to participants, the visual direction of potential targets from the direction of the movements required to reach the same targets, we provide direct evidence for this provocative idea. Our results offer strong empirical support for theories suggesting that competing action options are automatically represented in terms of the movements required to attain them. The rapid motor encoding of potential targets may support the fast optimization of motor costs under conditions of target uncertainty and allow the motor system to inform decisions about target selection.

The sequential encoding of competing action goals involves dynamic restructuring of motor plans in working memory

Recent neural and behavioral findings provide support for the influential idea that in situations in which multiple action options are presented simultaneously, we prepare action plans for each competing option before deciding between and executing one of those plans. However, in natural, everyday environments, our available action options frequently change from one moment to the next, and there is often uncertainty as to whether additional options will become available before having to select a particular course of action. Here, with the use of a target-directed reaching task, we show that in this situation, the brain specifies a competing action for each new, sequentially presented potential target and that recently formed action plans can be revisited and updated so as to conform with separate, more newly developed, plans. These findings indicate that the brain forms labile motor plans for sequentially arising target options that can be flexibly restructured to accommodate new motor plans.

Reach Trajectories Characterize Tactile Localization for Sensorimotor Decision Making

Spatial target information for movement planning appears to be coded in a gaze-centered reference frame. In touch, however, location is initially coded with reference to the skin. Therefore, the tactile spatial location must be derived by integrating skin location and posture. It has been suggested that this recoding is impaired when the limb is placed in the opposite hemispace, for example, by limb crossing. Here, human participants reached toward visual and tactile targets located at uncrossed and crossed feet in a sensorimotor decision task. We characterized stimulus recoding by analyzing the timing and spatial profile of hand reaches. For tactile targets at crossed feet, skin-based information implicates the incorrect side, and only recoded information points to the correct location. Participants initiated straight reaches and redirected the hand toward a target presented in midflight. Trajectories to visual targets were unaffected by foot crossing. In contrast, trajectories to tactile targets were redirected later with crossed than uncrossed feet. Reaches to crossed feet usually continued straight until they were directed toward the correct tactile target and were not biased toward the skin-based target location. Occasional, far deflections toward the incorrect target were most likely when this target was implicated by trial history. These results are inconsistent with the suggestion that spatial transformations in touch are impaired by limb crossing, but are consistent with tactile location being recoded rapidly and efficiently, followed by integration of skin-based and external information to specify the reach target. This process may be implemented in a bounded integrator framework.

SIGNIFICANCE STATEMENT

How do you touch yourself, for instance, to scratch an itch? The place you need to reach is defined by a sensation on the skin, but our bodies are flexible, so this skin location could be anywhere in 3D space. The movement toward the tactile sensation must therefore be specified by merging skin location and body posture. By investigating human hand reach trajectories toward tactile stimuli on the feet, we provide experimental evidence that this transformation process is quick and efficient, and that its output is integrated with the original skin location in a fashion consistent with bounded integrator decision-making frameworks.

Dynamic Integration of Value Information into a Common Probability Currency as a Theory for Flexible Decision Making

Decisions involve two fundamental problems, selecting goals and generating actions to pursue those goals. While simple decisions involve choosing a goal and pursuing it, humans evolved to survive in hostile dynamic environments where goal availability and value can change with time and previous actions, entangling goal decisions with action selection. Recent studies suggest the brain generates concurrent action-plans for competing goals, using online information to bias the competition until a single goal is pursued. This creates a challenging problem of integrating information across diverse types, including both the dynamic value of the goal and the costs of action. We model the computations underlying dynamic decision-making with disparate value types, using the probability of getting the highest pay-off with the least effort as a common currency that supports goal competition. This framework predicts many aspects of decision behavior that have eluded a common explanation.

Action plan co-optimization reveals the parallel encoding of competing reach movements

Several influential cognitive theories propose that in situations affording more than one possible target of action, we prepare multiple competing movements before selecting one. Here we provide direct evidence for this provocative but largely untested idea and demonstrate why preparing multiple movements is computationally advantageous. Using a reaching task in which movements are initiated after one of two potential targets is cued, we show that the movement generated for the cued target borrows components of the movement that would have been required for the other, competing target. This interaction can only arise if multiple potential movements are fully specified in advance and we demonstrate that it reduces the time required to launch a given action plan. Our findings suggest that this co-optimization of motor plans is highly automatic and largely occurs outside conscious awareness.

Several prominent cognitive theories propose that in situations affording more than one action strategy, the brain prepares multiple competing movements prior to selecting one. Here the authors provide direct experimental evidence for this provocative but largely untested notion.

A biologically plausible computational theory for value integration and action selection in decisions with competing alternatives

Decision making is a vital component of human and animal behavior that involves selecting between alternative options and generating actions to implement the choices. Although decisions can be as simple as choosing a goal and then pursuing it, humans and animals usually have to make decisions in dynamic environments where the value and the availability of an option change unpredictably with time and previous actions. A predator chasing multiple prey exemplifies how goals can dynamically change and compete during ongoing actions. Classical psychological theories posit that decision making takes place within frontal areas and is a separate process from perception and action. However, recent findings argue for additional mechanisms and suggest the decisions between actions often emerge through a continuous competition within the same brain regions that plan and guide action execution. According to these findings, the sensorimotor system generates concurrent action-plans for competing goals and uses online information to bias the competition until a single goal is pursued. This information is diverse, relating to both the dynamic value of the goal and the cost of acting, creating a challenging problem in integrating information across these diverse variables in real time. We introduce a computational framework for dynamically integrating value information from disparate sources in decision tasks with competing actions. We evaluated the framework in a series of oculomotor and reaching decision tasks and found that it captures many features of choice/motor behavior, as well as its neural underpinnings that previously have eluded a common explanation.

In high-pressure situations, such as driving on a highway or flying a plane, people have limited time to select between competing options while acting. Each option is usually accompanied with reward benefits (e.g., avoid traffic) and action costs (e.g., fuel consumption) that characterize the value of the option. The value and the availability of an option can change dynamically even during ongoing actions which compounds the decision-making challenge. How the brain dynamically integrates value information from disparate sources and selects between competing options is still poorly understood. In the current study, we present a neurodynamical framework to show how a distributed brain network can solve the problem of value integration and action selection in decisions with competing alternatives. It combines dynamic neural field theory with stochastic optimal control theory, and includes circuitry for perception, expected reward, effort cost and decision-making. It provides a principled way to explain both the neural and the behavioral findings from a series of visuomotor decision tasks in human and animal studies. For instance, the model shows how the competitive interactions between populations of neurons within and between sensorimotor regions can result in “spatial-averaging” movements, and how decision-variables influence neural activity and choice behavior.

Three-dimensional reach trajectories as a probe of real-time decision-making between multiple competing targets

Though several features of cognitive processing can be inferred from the discrete measurement [e.g., reaction time (RT), accuracy, etc.] of participants' conscious reports (e.g., verbal or key-press responses), it is becoming increasingly clear that a much richer understanding of these features can be captured from continuous measures of rapid, largely non-conscious behaviors like hand or eye movements. Here, using new experimental data, we describe in detail both the approach and analyses implemented in some of our previous studies that have used rapid reaching movements under cases of target uncertainty in order to probe the features, constraints and dynamics of stimulus-related processing in the brain. This work, as well as that of others, shows that when individuals are simultaneously presented with multiple potential targets—only one of which will be cued after reach onset—they produce initial reach trajectories that are spatially biased in accordance with the probabilistic distribution of targets. Such “spatial averaging” effects are consistent with observations from neurophysiological studies showing that neuronal populations in sensorimotor brain structures represent multiple target choices in parallel and they compete for selection. These effects also confirm and help extend computational models aimed at understanding the underlying mechanisms that support action-target selection. We suggest that the use of this simple, yet powerful behavioral paradigm for providing a “real-time” visualization of ongoing cognitive processes occurring at the neural level offers great promise for studying processes related to a wide range of psychological phenomena, such as decision-making and the representation of objects.

Embodied effects of conceptual knowledge continuously perturb the hand in flight

Attending to a manipulable object evokes a mental representation of hand actions associated with the object's form and function. In one view, these representations are sufficiently abstract that their competing influence on an unrelated action is confined to the planning stages of movement and does not affect its on-line control. Alternatively, an object may evoke action representations that affect the entire trajectory of an unrelated grasping action. We developed a new methodology to statistically analyze the forward motion and rotation of the hand and fingers under different task conditions. Using this novel approach, we established that a grasping action executed after seeing a photograph of an object is systematically perturbed even into the late stages of its trajectory by the competing influence of the grasping posture associated with the object. Our results show that embodied effects of conceptual knowledge continuously modulate the hand in flight.

Connecting the Dots

The perceptual system parses complex scenes into discrete objects. Parsing is also required for planning visually guided movements when more than one potential target is present. To examine whether visual perception and motor planning use the same or different parsing strategies, we used the connectedness illusion, in which observers typically report seeing fewer targets if pairs of targets are connected by short lines. We found that despite this illusion, when observers are asked to make speeded reaches toward targets in such displays, their reaches are unaffected by the presence of the connecting lines. Instead, their movement plans, as revealed by their movement trajectories, are influenced by the number of potential targets irrespective of whether connecting lines are present or not. This suggests that scene parsing for perception depends on mechanisms that are distinct from those that allow observers to plan rapid and efficient target-directed movements in situations with multiple potential targets.

Simultaneous encoding of the direction and orientation of potential targets during reach planning: evidence of multiple competing reach plans

Reaches performed in many natural situations involve selecting a specific target from a number of alternatives. Recent studies show that before reaching, multiple potential reach targets are encoded in brain regions involved in action control and that, when people are required to initiate the reach before the target is specified, initial hand direction is biased by the spatial distribution of potential targets. These findings have led to the suggestion that the brain, during planning, simultaneously prepares multiple reaches to potential targets. In addition to hand direction, reach planning often involves specifying other parameters such as wrist orientation. For example, when posting a letter in a mail slot, both the location and orientation of the slot must be encoded to control hand direction and orientation. Therefore, if the brain prepares multiple reaches to potential targets and if these targets require the specification of hand direction and orientation, then both of these variables should be biased by the spatial distribution of potential targets. To test this prediction, we examined a task in which participants moved a hand-held rectangular tool toward multiple rectangular targets of varying location and orientation, one of which was selected, with equal probability as the actual target after movement initiation. We found that initial hand direction and orientation were biased by the spatial distributions of potential target locations and orientations, respectively. This result is consistent with the idea that the brain, in cases of target uncertainty, simultaneously plans fully specified reaching movements to all potential targets.