Understanding how humans observe and interpret actions is vital for social interaction. Point-light displays (PLDs), which depict actions using only joint movements, are widely used to study this process. Recently, PLAViMoP — an open-access database of 3D PLDs covering everyday actions, fine-motor skills, sports movements, facial expressions, social interactions, and robotic actions — has been introduced to facilitate the use of PLDs. PLAViMoP includes a search engine and metadata for each sequence, including movement type, label, actor sex, and age. In complement to the database, here we present a novel methodology that integrates eye-tracking data into the PLD reference frame, allowing gaze behavior and action kinematics to be jointly analyzed (i.e., in a unified dataset). This combined approach offers new insights into action perception and has broad applications in health, sports, and occupational settings. It also offers a promising tool for continuous psychophysical studies of the perception of biological movement.

3D-ARM-Gaze is a public dataset designed to provide natural arm movements together with visual and gaze information when reaching objects in a wide reachable space from a precisely controlled, comfortably seated posture. Participants were involved in picking and placing objects in various positions and orientations in a virtual environment, whereby a specific procedure maximized the workspace explored while ensuring a consistent seated posture by guiding participants to a predetermined neutral posture via visual feedback from the trunk and shoulders. These experimental settings enabled to capture natural arm movements with high median success rates (>98% objects reached) and minimal compensatory movements. The dataset regroups more than 2.5 million samples recorded from 20 healthy participants performing 14 000 single pick-and-place movements (700 per participant). While initially designed to explore novel prosthesis control strategies based on natural eye-hand and arm coordination, this dataset will also be useful to researchers interested in core sensorimotor control, humanoid robotics, human-robot interactions, as well as for the development and testing of associated solutions in gaze-guided computer vision.

The differentiation between continuous and discrete actions is key for behavioral neuroscience. Although many studies have characterized eye-hand coordination during discrete (e.g., reaching) and continuous (e.g., pursuit tracking) actions, all these studies were conducted separately, using different setups and participants. In addition, how eye-hand coordination might operate at the frontier between discrete and continuous movements remains unexplored. Here we filled these gaps by means of a task that could elicit different movement dynamics. Twenty-eight participants were asked to simultaneously track with their eyes and a joystick a visual target that followed an unpredictable trajectory and whose position was updated at different rates (from 1.5 to 240 Hz). This procedure allowed us to examine actions ranging from discrete point-to-point movements (low refresh rate) to continuous pursuit (high refresh rate). For comparison, we also tested a manual tracking condition with the eyes fixed and a pure eye tracking condition (hand fixed). The results showed an abrupt transition between discrete and continuous hand movements around 3 Hz contrasting with a smooth trade-off between fixations and smooth pursuit. Nevertheless, hand and eye tracking accuracy remained strongly correlated, with each of these depending on whether the other effector was recruited. Moreover, gaze-cursor distance and lag were smaller when eye and hand performed the task conjointly than separately. Altogether, despite some dissimilarities in eye and hand dynamics when transitioning between discrete and continuous movements, our results emphasize that eye-hand coordination continues to smoothly operate and support the notion of synergies across eye movement types.

Simultaneous adaptation to opposite visuomotor perturbations is known to be difficult. It has been shown to be possible only in situations where the two tasks are associated with different contexts, being either a different colored background, a different area of workspace, or a different follow-through movement. However, many of these elements evoke explicit mechanisms that could contribute to storing separate (modular) memories. It remains to be shown whether simultaneous adaptation to multiple perturbations is possible when they are introduced in a fully implicit manner. Here, we sought to test this possibility using a visuomotor perturbation small enough to eliminate explicit awareness. Participants (N = 25) performed center-out reaching movements with a joystick to five targets located 72 degrees apart. Depending on the target, visual feedback of cursor position was either veridical (one target) or could be rotated by +5 or -5 degrees (two targets each). After 300 trials of adaptation (60 to each target), results revealed that participants were able to fully compensate for each of the imposed rotations. Moreover, when veridical visual feedback was restored, participants exhibited after-effects that were consistent with the rotations applied at each target. Questionnaires collected immediately after the experiment confirmed that none of the participants were aware of the perturbations. These results speak for the existence of implicit processes that can smoothly handle small and opposite visual perturbations when these are associated with distinct target locations.

To date, interlimb transfer following visuomotor adaptation has been mainly investigated through discrete reaching movements. Here we explored this issue in the context of continuous manual tracking, a task in which the contribution of online feedback mechanisms is crucial, and in which there is a well-established right (dominant) hand advantage under baseline conditions. We had two objectives (1) to determine whether this preexisting hand asymmetry would persist under visuomotor rotation, (2) to examine interlimb transfer by assessing whether prior experience with the rotation by one hand benefit to the other hand. To address these, 44 right-handed participants were asked to move a joystick and to track a visual target following a rather unpredictable trajectory. Visuomotor adaptation was elicited by introducing a 90° rotation between the joystick motion and the cursor motion. Half of the participants adapted to the rotation first with the right hand, and then with the left, while the other half performed the opposite protocol. As expected during baseline trials, the left hand was less accurate while also exhibiting more variable and exploratory behavior. However, participants exhibited a left hand advantage during first exposure to the rotation. Moreover, interlimb transfer was observed albeit more strongly from the left to the right hand. We suggest that the less effective and more variable/exploratory control strategy of the left hand promoted its adaptation, which incidentally favored transfer from left to right hand. Altogether, this study speaks for further attention to the dominant/non-dominant asymmetry during baseline before examining interlimb transfer of adaptation.

Reaching and manual tracking are two very common tasks for studying human sensorimotor processes. Although these motor tasks rely both on feedforward and feedback processes, emphasis is more on feedforward processes for reaching and feedback processes for tracking. The extent to which feedforward and feedback processes are interrelated when being updated is not settled yet. Here, using reaching and tracking as proxies, we examined the bidirectional relationship between the update of feedforward and feedback processes. Forty right-handed participants were asked to move a joystick so as to either track a target moving rather unpredictably (pursuit tracking) or to make fast pointing movements toward a static target (center-out reaching task). Visuomotor adaptation was elicited by introducing a 45° rotation between the joystick motion and the cursor motion. Half of the participants adapted to rotation first via reaching movements and then with pursuit tracking, whereas the other half performed both tasks in opposite order. Group comparisons revealed a strong asymmetrical transfer of adaptation between tasks. Namely, although nearly complete transfer of adaptation was observed from reaching to tracking, only modest transfer was found from tracking to reaching. A control experiment (n = 10) revealed that making target motion fully predictable did not impact the latter finding. One possible interpretation is that the update of feedforward processes contributes directly to feedback processes, but the update of feedback processes engaged in tracking can be performed in isolation. These results suggest that reaching movements are supported by broader (i.e. more universal) mechanisms than tracking ones.NEW & NOTEWORTHY Reaching and manual tracking are thought to rely differently on feedforward and feedback processes. Here, we show that although nearly complete transfer of visuomotor adaptation occurs from reaching to tracking, only minimal transfer is found from tracking to reaching. Even though the update of feedforward processes (key for reaching) proved directly useful to feedback processes (key for tracking), the strong asymmetrical transfer suggests that feedback control can be updated independently from feedforward adaptation.

When tracking targets moving in various directions with one's eyes, horizontal components of pursuit are more precise than vertical ones. Is this because horizontal target motion is predicted better or because horizontal movements of the eyes are controlled more precisely? When tracking a visual target with the hand, the eyes also track the target. We investigated whether the directional asymmetries that have been found during isolated eye movements are also present during such manual tracking, and if so, whether individual participants' asymmetry in eye movements is accompanied by a similar asymmetry in hand movements. We examined the data of 62 participants who used a joystick to track a visual target with a cursor. The target followed a smooth but unpredictable trajectory in two dimensions. Both the mean gaze-target distance and the mean cursor-target distance were about 20% larger in the vertical direction than in the horizontal direction. Gaze and cursor both followed the target with a slightly longer delay in the vertical than in the horizontal direction, irrespective of the target's trajectory. The delays of gaze and cursor were correlated, as were their errors in tracking the target. Gaze clearly followed the target rather than the cursor, so the asymmetry in both eye and hand movements presumably results from better predictions of the target's horizontal than of its vertical motion. Altogether this study speaks for the presence of anisotropic predictive processes that are shared across effectors.

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.

It is well documented that providing advanced information regarding the spatial location of a target stimulus (i.e., spatial anticipation) or its timing of occurrence (i.e., temporal anticipation) influences reach preparation, reducing RTs. Yet, it remains unknown whether the RT gains attributable to temporal and spatial anticipation are subtended by similar preparatory dynamics. Here, this issue is addressed in humans by investigating EEG beta-band activity during reach preparation. Participants performed a reach RT task in which they initiated a movement as fast as possible toward visual targets following their appearance. Temporal anticipation was manipulated by having the target appear after a constant or variable delay period, whereas spatial anticipation was manipulated by precueing participants about the upcoming target location in advance or not. Results revealed that temporal and spatial anticipation both reduced reach RTs, with no interaction. Interestingly, temporal and spatial anticipation were associated with fundamentally different patterns of beta-band modulations. Temporal anticipation was associated with beta-band desynchronization over contralateral sensorimotor regions specifically around the expected moment of target onset, the magnitude of which was correlated with RT modulations across participants. In contrast, spatial anticipation did not influence sensorimotor activity but rather led to increased beta-band power over bilateral parieto-occipital regions during the entire delay period. These results argue for distinct states of preparation incurred by temporal and spatial anticipation. In particular, sensorimotor beta-band desynchronization may reflect the timely disinhibition of movement-related neuronal ensembles at the expected time of movement initiation, without reflecting its spatial parameters per se.

There is a growing interest in sex differences in human and animal cognition. However, empirical evidences supporting behavioral and neural sex differences in humans remain sparse. Visuomotor behaviors offer a robust and naturalistic empirical framework to seek for the computational mechanisms underlying sex biases in cognition. In a large group of human participants (N=127), we investigated sex differences in a visuo-oculo-manual motor task that consists of tracking with the hand a target moving unpredictably. We report a clear male advantage in hand tracking accuracy. We tested whether men and women employ different gaze strategy or hand movement kinematics. Results show no key difference in these distinct visuomotor components. However, highly consistent differences in eye-hand coordination were evidenced by a larger temporal lag between hand motion and target motion in women. This observation echoes with other studies showing a male advantage in manual reaction time to visual stimuli. We propose that the male advantage for visuomotor tracking does not reside in a more reliable gaze strategy, or in more sophisticated hand movements, but rather in a faster decisional process linking visual information about target motion with forthcoming hand, but not eye, actions.

When coordinating two hands to achieve a common goal, the nervous system has to assign responsibility to each hand. Optimal control theory suggests that this problem is solved by minimizing costs such as the variability of movement and effort. However, the natural tendency to produce similar movements during bimanual tasks has been somewhat ignored by this approach. We consider a task in which participants were asked to track a moving target by means of a single cursor controlled simultaneously by the two hands. Two types of hand-cursor mappings were tested: one in which the cursor position resulted from the average location of two hands (Mean) and one in which horizontal and vertical positions of the cursor were driven separately by each hand (Split). As expected, unimanual tracking performance was better with the dominant hand than with the more variable nondominant hand. More interestingly, instead of exploiting this effect by increasing the use of the dominant hand, the contributions from both hands remained symmetrical during bimanual cooperative tasks. Indeed, for both mappings, and even after 6min of practice, the right and left hands remained strongly correlated, performing similar movements in extrinsic space. Persistence of this bimanual coupling demonstrates that participants prefer to maintain similar movements at the expense of unnecessary movements (in the Split task) and of increased noise from the nondominant hand (in the Mean task). Altogether, the findings suggest that bimanual tracking exploits hand coordination in space rather than minimizing motor costs associated with variability and effort.NEW & NOTEWORTHY When two hands are coordinated to achieve a common goal, optimal control theory proposes that the brain assigns responsibility to each hand by minimizing movement variability and effort. Nevertheless, we show that participants perform bimanual tracking using similar contributions from the dominant and nondominant hands, despite unnecessary movements and a less accurate nondominant hand. Our findings suggest that bimanual tracking exploits hand coordination in space rather than minimizing motor costs associated with variability and effort.

Adapting hand movements to changes in our body or the environment is essential for skilled motor behavior. Although eye movements are known to assist hand movement control, how eye movements might contribute to the adaptation of hand movements remains largely unexplored. To determine to what extent eye movements contribute to visuomotor adaptation of hand tracking, participants were asked to track a visual target that followed an unpredictable trajectory with a cursor using a joystick. During blocks of trials, participants were either allowed to look wherever they liked or required to fixate a cross at the center of the screen. Eye movements were tracked to ensure gaze fixation as well as to examine free gaze behavior. The cursor initially responded normally to the joystick, but after several trials, the direction in which it responded was rotated by 90°. Although fixating the eyes had a detrimental influence on hand tracking performance, participants exhibited a rather similar time course of adaptation to rotated visual feedback in the gaze-fixed and gaze-free conditions. More importantly, there was extensive transfer of adaptation between the gaze-fixed and gaze-free conditions. We conclude that although eye movements are relevant for the online control of hand tracking, they do not play an important role in the visuomotor adaptation of such tracking. These results suggest that participants do not adapt by changing the mapping between eye and hand movements, but rather by changing the mapping between hand movements and the cursor's motion independently of eye movements. NEW & NOTEWORTHY Eye movements assist hand movements in everyday activities, but their contribution to visuomotor adaptation remains largely unknown. We compared adaptation of hand tracking under free gaze and fixed gaze. Although our results confirm that following the target with the eyes increases the accuracy of hand movements, they unexpectedly demonstrate that gaze fixation does not hinder adaptation. These results suggest that eye movements have distinct contributions for online control and visuomotor adaptation of hand movements.

The ability to track a moving target with the hand has been extensively studied, but few studies have characterized gaze behavior during this task. Here we investigate gaze behavior when participants learn a new mapping between hand and cursor motion, such that the cursor represented the position of a virtual mass attached to the grasped handle via a virtual spring. Depending on the experimental condition, haptic feedback consistent with mass-spring dynamics could also be provided. For comparison a simple one-to-one hand-cursor mapping was also tested. We hypothesized that gaze would be drawn, at times, to the cursor in the mass-spring conditions, especially in the absence of haptic feedback. As expected hand tracking performance was less accurate under the spring mapping, but gaze behavior was virtually unaffected by the spring mapping, regardless of whether haptic feedback was provided. Specifically, relative gaze position between target and cursor, rate of saccades, and gain of smooth pursuit were similar under both mappings and both haptic feedback conditions. We conclude that even when participants are exposed to a challenging hand-cursor mapping, gaze is primarily concerned about ongoing target motion suggesting that peripheral vision is sufficient to monitor cursor position and to update hand movement control.

In human gait, alternating flexion and extension of the legs essentially requires the production of extension forces, leg flexion being largely determined by passive forces. Electromyographic (EMG) activity patterns show an opposition between the two phases of gait. In contrast, during the swing phase minor EMG activity of the flexor muscles is observed. Longitudinal displacement of each foot tip, angles of the hip, knee, and ankle, and EMG activity from the major surface muscles of the right leg was recorded. During the stance phase, substantial EMG activity is observed in the extensor muscles. The elastic constraint is derived from the "penguin suit" initially created to make a cosmonaut's extensor muscles work under micro-gravity conditions. The elastic constraint also induced important changes in proprioceptive information. Thus the elastic constraint requires adapting motor commands in a modified sensory context. The kinematics used in condition C was found to minimize the moments generated by the elastic cords.

Skilled motor behavior relies on the ability to control the body and to predict the sensory consequences of this control. Although there is ample evidence that manual dexterity depends on handedness, it remains unclear whether control and prediction are similarly impacted. To address this issue, right-handed human participants performed two tasks with either the right or the left hand. In the first task, participants had to move a cursor with their hand so as to track a target that followed a quasi-random trajectory. This hand-tracking task allowed testing the ability to control the hand along an imposed trajectory. In the second task, participants had to track with their eyes a target that was self-moved through voluntary hand motion. This eye-tracking task allowed testing the ability to predict the visual consequences of hand movements. As expected, results showed that hand tracking was more accurate with the right hand than with the left hand. In contrast, eye tracking was similar in terms of spatial and temporal gaze attributes whether the target was moved by the right or the left hand. Although these results extend previous evidence for different levels of control by the two hands, they show that the ability to predict the visual consequences of self-generated actions does not depend on handedness. We propose that the greater dexterity exhibited by the dominant hand in many motor tasks stems from advantages in control, not in prediction. Finally, these findings support the notion that prediction and control are distinct processes.

Prediction turns motor commands into expected sensory consequences, whereas control turns desired consequences into motor commands. Flanagan and colleagues (2003) have shown that subjects can learn to predict before they can actually learn to control. This observation was interpreted as evidence that the update of prediction precedes control in motor learning. Here we investigated the transfer of learning between two visuomotor tasks both requiring adaptation to a 90° rotation. In the first task participants had to track with their eyes a self-moved target whose displacement was driven by random hand motion (see also Landelle et al., 2016). In the other task participants had also to move the hand but this time they were required to move a cursor so as to track an externally moving target (see also Ogawa & Imamizu, 2013). The first task was designed to test the ability of participants to predict novel visual consequences arising from their hand actions (eye tracking task). The second task was designed to monitor their ability to control a cursor along a desired trajectory (hand tracking task). Our preliminary results suggest an asymmetrical transfer of learning between the two tasks. Namely, although prior experience in the hand tracking task enhanced performance in the eye tracking task, prior experience in the eye tracking task did not improve performance in the hand tracking task. A possible scheme to account for these results is that visuomotor adaptation in our hand tracking task requires both the update of a forward and inverse model (Wolpert & Kawato, 1998), whereas adaptation in our eye tracking task relies solely on the update of a forward model. At a more general level these results emphasize that our ability to predict sensory consequences of hand movements can be improved without necessarily improving our ability to control hand movements. Meeting abstract presented at VSS 2018

The ability to visually track, using smooth pursuit eye movements, moving objects is critical in both perceptual and action tasks. Here, by asking participants to view a moving target or track it with their hand, we tested whether different task demands give rise to different gaze strategies. We hypothesized that during hand tracking, in comparison to eye tracking, the frequency of catch-up saccades would be lower, and the smooth pursuit gain would be greater, because it limits the loss of stable retinal and extra-retinal information due to saccades. In our study participants viewed a visual target that followed a smooth but unpredictable trajectory in a horizontal plane and were instructed to either track the target with their gaze or with a cursor controlled by a manipulandum. Although the mean distance between gaze and target was comparable in both tasks, we found, consistent with our hypothesis, an increase in smooth pursuit gain and a decrease in the frequency of catch-up saccades during hand tracking. We suggest that this difference in gaze behavior arises from different tasks demands. Whereas keeping gaze close to the target is important in both tasks, obtaining stable retinal and extra-retinal information is critical for guiding hand movement.

Current theories suggest that the ability to control the body and to predict its associated sensory consequences is key for skilled motor behavior. It is also suggested that these abilities need to be updated when the mapping between motor commands and sensory consequences is altered. Here we challenge this view by investigating the transfer of adaptation to rotated visual feedback between one task in which human participants had to control a cursor with their hand in order to track a moving target, and another in which they had to predict with their eyes the visual consequences of their hand movement on the cursor. Hand and eye tracking performances were evaluated respectively through cursor-target and eye-cursor distance. Results reveal a striking dissociation: although prior adaptation of hand tracking greatly facilitates eye tracking, the adaptation of eye tracking does not transfer to hand tracking. We conclude that although the update of control is associated with the update of prediction, prediction can be updated independently of control. To account for this pattern of results, we propose that task demands mediate the update of prediction and control. Although a joint update of prediction and control seemed mandatory for success in our hand tracking task, the update of control was only facultative for success in our eye tracking task. More generally, those results promote the view that prediction and control are mediated by separate neural processes and suggest that people can learn to predict movement consequences without necessarily promoting their ability to control these movements.

Transcranial magnetic stimulation (TMS) can interfere with smooth pursuit or with saccades initiated from a fixed position toward a fixed target, but little is known about the effect of TMS on catch-up saccade made to assist smooth pursuit. Here we explored the effect of TMS on catch-up saccades by means of a situation in which the moving target was driven by an external agent, or moved by the participants' hand, a condition known to decrease the occurrence of catch-up saccade. Two sites of stimulation were tested, the vertex and M1 hand area. Compared to conditions with no TMS, we found a consistent modulation of saccadic activity after TMS such that it decreased at 40-100ms, strongly resumed at 100-160ms, and then decreased at 200-300ms. Despite this modulatory effect, the accuracy of catch-up saccade was maintained, and the mean saccadic activity over the 0-300ms period remained unchanged. Those findings are discussed in the context of studies showing that single-pulse TMS can induce widespread effects on neural oscillations as well as perturbations in the latency of saccades during reaction time protocols. At a more general level, despite challenges and interpretational limitations making uncertain the origin of this modulatory effect, our study provides direct evidence that TMS over presumably non-oculomotor regions interferes with the initiation of catch-up saccades, and thus offers methodological considerations for future studies that wish to investigate the underlying neural circuitry of catch-up saccades using TMS.

The ability to track a moving target with the eye is substantially improved when the target is self-moved compared with when it is moved by an external agent. To account for this observation, it has been postulated that the oculomotor system has access to hand efference copy, thereby allowing to predict the motion of the visual target. Along this scheme, we tested the effect of transcranial magnetic stimulation (TMS) over the hand area of the primary motor cortex (M1) when human participants (50% females) are asked to track with their eyes a visual target whose horizontal motion is driven by their grip force. We reasoned that, if the output of M1 is used by the oculomotor system to keep track of the target, on top of inducing short latency disturbance of grip force, single-pulse TMS should also quickly disrupt ongoing eye motion. For comparison purposes, the effect of TMS over M1 was monitored when subjects tracked an externally moved target (while keeping their hand at rest or not). In both cases, results showed no alterations in smooth pursuit, meaning that its velocity was unaffected within the 25–125 ms epoch that followed TMS. Overall, our results imply that the output of M1 has limited contribution in driving the eye motion during our eye-hand coordination task. This study suggests that, if hand motor signals are accessed by the oculomotor system, this is upstream of M1. SIGNIFICANCE STATEMENT The ability to coordinate eye and hand actions is central in everyday activity. However, the neural mechanisms underlying this coordination remain to be clarified. A leading hypothesis is that the oculomotor system has access to hand motor signals. Here we explored this possibility by means of transcranial magnetic stimulation (TMS) over the hand area of the primary motor cortex (M1) when humans tracked with the eyes a visual target that was moved by the hand. As expected, ongoing hand action was perturbed 25–30 ms after TMS, but our results fail to show any disruption of eye motion, smooth pursuit velocity being unaffected. This work suggests that, if hand motor signals are accessed by the oculomotor system, this is upstream of M1.