We explore the visual world through saccadic eye movements, but saccades also present a challenge to visual processing by shifting externally stable objects from one retinal location to another. The brain could solve this problem in two ways: by overwriting preceding input and starting afresh with each fixation or by maintaining a representation of presaccadic visual features in working memory and updating it with new information from the remapped location. Crucially, when multiple objects are present in a scene the planning of eye movements profoundly affects the precision of their working memory representations, transferring limited memory resources from fixation toward the saccade target. Here we show that when humans make saccades, it results in an update of not just the precision of representations but also their contents. When multiple item colors are shifted imperceptibly during a saccade the perceived colors are found to fall between presaccadic and postsaccadic values, with the weight given to each input varying continuously with item location, and fixed relative to saccade parameters. Increasing sensory uncertainty, by adding color noise, biases updating toward the more reliable input, which is consistent with an optimal integration of presaccadic working memory with a postsaccadic updating signal. We recover this update signal and show it to be tightly focused on the vicinity of the saccade target. These results reveal how the nervous system accumulates detailed visual information from multiple views of the same object or scene.

To study the strategy in responding to target displacements during fast goal-directed arm movements, we examined how quickly corrections are initiated and how vigorously they are executed. We perturbed the target position at various moments before and after movement initiation. Corrections to perturbations before the movement started were initiated with the same latency as corrections to perturbations during the movement. Subjects also responded as quickly to a second perturbation during the same reach, even if the perturbations were only separated by 60 ms. The magnitude of the correction was minimized with respect to the time remaining until the end of the movement. We conclude that despite being executed after a fixed latency, these fast corrections are not stereotyped responses but are suited to the circumstances.

Recent studies suggested that the control of hand movements in catching involves continuous visionbased adjustments. More insight into these adjustments may be gained by examining the effects of occluding different parts of the ball trajectory. Here, we examined the effects of such occlusion on lateral hand movements when catching balls approaching from different directions, with the occlusion conditions presented in blocks or in randomized order. The analyses showed that late occlusion only had an effect during the blocked presentation, and early occlusion only during the randomized presentation. During the randomized presentation movement biases were more leftward if the preceding trial was an early occlusion trial. The effect of early occlusion during the randomized presentation suggests that the observed leftward movement bias relates to the rightward visual acceleration inherent to the ball trajectories used, while its absence during the blocked presentation seems to reflect trial-by-trial adaptations in the visuomotor gain, reminiscent of dynamic gain control in the smooth pursuit system. The movement biases during the late occlusion block were interpreted in terms of an incomplete motion extrapolation-a reduction of the velocity gaincaused by the fact that participants never saw the to-beextrapolated part of the ball trajectory. These results underscore that continuous movement adjustments for catching do not only depend on visual information, but also on visuomotor adaptations based on non-visual information.

We can adjust an ongoing movement to a change in the target's position with a latency of about 100 ms, about half of the time that is needed to start a new movement in response to the same change in target position (reaction time). In this opinion paper, we discuss factors that could explain the difference in latency between initiating and adjusting a movement in response to target displacements. We consider the latency to be the sum of the durations of various stages in information processing. Many of these stages are identical for adjusting and initiating a movement; however, for movement initiation, it is essential to detect that something has changed to respond, whereas adjustments to movements can be based on updated position information without detecting that the position has changed. This explanation for the shorter latency for movement adjustments also explains why we can respond to changes that we do not detect.

The brain rapidly adapts reaching movements to changing circumstances by using visual feedback about errors. Providing reward in addition to error feedback facilitates the adaptation but the underlying mechanism is unknown. Here, we investigate whether the proportion of trials rewarded (the ‘reward abundance’) influences how much participants adapt to their errors. We used a 3D multi-target pointing task in which reward alone is insufficient for motor adaptation. Participants (N = 423) performed the pointing task with feedback based on a shifted hand-position. On a proportion of trials we gave them rewarding feedback that their hand hit the target. Half of the participants only received this reward feedback. The other half also received feedback about endpoint errors. In different groups, we varied the proportion of trials that was rewarded. As expected, participants who received feedback about their errors did adapt, but participants who only received reward-feedback did not. Critically, participants who received abundant rewards adapted less to their errors than participants who received less reward. Thus, reward abundance negatively influences how much participants learn from their errors. Probably participants used a mechanism that relied more on the reward feedback when the reward was abundant. Because participants could not adapt to the reward, this interfered with adaptation to errors.

When studying online movement adjustments, one of the interesting parameters is their latency. We set out to compare three different methods of determining the latency: the threshold, confidence interval, and extrapolation methods. We simulated sets of movements with different movement times and amplitudes of movement adjustments, all with the same known latency. We applied the three different methods in order to determine when the position, velocity, and acceleration of the adjusted movements started to deviate from the values for unperturbed movements. We did so both for averaged data and for the data of individual trials. We evaluated the methods on the basis of their accuracy and precision, and according to whether the latency was influenced by the intensity of the movement adjustment. The extrapolation method applied to average acceleration data gave the most reliable estimates of latency, according to these criteria.

Faster movements are typically more variable - a speed-accuracy tradeoff known as Fitts' law. Are movements that are initiated faster also more variable? Neurophysiological work has associated larger neural variability during motor preparation with longer reaction time (RT) and larger movement variability, implying that movement variability decreases with increasing RT. Here, we recorded over 30000 reaching movements in eleven human participants who moved to visually-cued targets. Half of the visual cues was accompanied by a beep to evoke a wide RT range in each participant. Results show that initial reach variability decreases with increasing RT, for voluntarily produced RTs up to ~300 ms, while other kinematic aspects and endpoint accuracy remained unaffected. We conclude that movement preparation time determines initial movement variability. We suggest that the chosen movement preparation time reflects a trade-off between movement initiation and precision.

It has been suggested that movements are planned in terms of direction and distance. If so, online adjustments to changes in the direction and distance of the movements may also differ. The authors therefore investigated whether fast online movement adjustments are the same for perturbations of the direction and of the distance. While subjects made fast pointing movements, the authors perturbed either target direction or distance or both shortly after movement initiation. Both kinds of perturbations resulted in accurate online adjustments. The latency and intensity of corrections for distance and direction perturbations were quite similar. This suggests that there might be one mechanism controlling both distance and direction perturbations.