Our ability to interact with the environment hinges on creating a stable visual world despite the continuous changes in retinal input. To achieve visual stability, the brain must distinguish the retinal image shifts caused by eye movements and shifts due to movements of the visual scene. This process appears not to be flawless: during saccades, we often fail to detect whether visual objects remain stable or move, which is called saccadic suppression of displacement (SSD). How does the brain evaluate the memorized information of the presaccadic scene and the actual visual feedback of the postsaccadic visual scene in the computations for visual stability? Using a SSD task, we test how participants localize the presaccadic position of the fixation target, the saccade target or a peripheral non-foveated target that was displaced parallel or orthogonal during a horizontal saccade, and subsequently viewed for three different durations. Results showed different localization errors of the three targets, depending on the viewing time of the postsaccadic stimulus and its spatial separation from the presaccadic location. We modeled the data through a Bayesian causal inference mechanism, in which at the trial level an optimal mixing of two possible strategies, integration vs. separation of the presaccadic memory and the postsaccadic sensory signals, is applied. Fits of this model generally outperformed other plausible decision strategies for producing SSD. Our findings suggest that humans exploit a Bayesian inference process with two causal structures to mediate visual stability.

Movement inhibition is an aspect of executive control that can be studied using the countermanding paradigm, wherein subjects try to cancel an impending movement following presentation of a stop signal. This paradigm permits estimation of the stop-signal reaction time or the time needed to respond to the stop signal. Numerous countermanding studies have examined fast, ballistic movements, such as saccades, even though many movements in daily life are not ballistic and can be stopped at any point during their trajectory. A benefit of studying the control of nonballistic movements is that antagonist muscle recruitment, which serves to actively brake a movement, presumably arises in response to the stop signal. Here, nine human participants (2 female) performed a center-out whole-arm reaching task with a countermanding component, while we recorded the activity of upper-limb muscles contributing to movement generation and braking. The data show a clear response on antagonist muscles to a stop signal, even for movements that have barely begun. As predicted, the timing of such antagonist recruitment relative to the stop signal covaried with conventional estimates of the stop-signal reaction time, both within and across subjects. The timing of antagonist muscle recruitment also attested to a rapid reprioritization of movement inhibition, with antagonist latencies decreasing across sequences consisting of repeated stop trials; such reprioritization also scaled with error magnitude. We conclude that antagonist muscle recruitment arises as a manifestation of a stopping process, providing a novel, accessible, and within-trial measure of the stop-signal reaction time. The countermanding or stop-signal paradigm permits estimation of how quickly subjects cancel an impending movement. Traditionally, this paradigm has been studied using simple movements, such as saccadic eye movements or button presses. Here, by measuring upper limb muscle activity while human subjects countermand whole-arm reaching movements, we show that movement cancellation often involves prominent recruitment of antagonist muscles that serves to actively brake the movement, even on movements that have barely begun. The timing of antagonist muscle recruitment correlates with traditional estimates of movement cancellation. Because they can be detected on a single-trial basis, muscle-based measures may provide a new way of characterizing movement cancellation at an unprecedented within-trial resolution.

We investigated motion extrapolation in object tracking in two experiments. In Experiment 1, we used a multiple-object-tracking task (MOT; three targets, three distractors) combined with a probe detection task to investigate the distribution of attention around a target object. We found anisotropic probe detection rates with increased probe detection at locations where a target is heading. In Experiment 2, we introduced a black line (wall) in the center of the screen and block-wise manipulated the object's motion: either objects bounced realistically against the wall or objects went through the wall. Just before a target coincided with the wall, a probe could appear either along the bounce path or along the straight path. In addition to MOT, we included a single-object-tracking task (SOT; one target, five distractors) to control for attentional load. We found that linear extrapolation is dominant (better probe detection along the straight path than bounce path) regardless of attentional load and the motion condition. Anticipation of bouncing behavior did occur but only when attentional load was low. We conclude that attention is not tightly bound to moving target objects but encompasses the object's current position and the area in front of it. Furthermore, under the present experimental conditions, the visuo-attentional system does not seem to anticipate object bounces in the MOT task.

Every saccadic eye movement that we make changes the image of the world on our retina. Yet, despite these retinal shifts, we still perceive our visual world to be stable. Efference copy from the oculomotor system to the visual system has been suggested to contribute to this stable percept, enabling the brain to anticipate the retinal image shifts by remapping the neural image. A psychophysical phenomenon that has been linked to this predictive remapping is the mislocalization of a stimulus flashed around the time of a saccade. If this mislocalization is initiated by saccade preparation, one should also observe localization errors when a saccade is planned, but abruptly aborted just before its execution. We tested this hypothesis in human subjects using a novel paradigm that combines a flash localization task with a countermanding component that occasionally requires saccade cancellation. Surprisingly, we found no trace of mislocalization, even for saccades cancelled close to the point of no return. This strongly suggests that the actual execution of the saccade is a prerequisite for the typical localization errors, which rejects various models and constrains neural substrates. We conclude that perisaccadic mislocalization is not a direct consequence of saccade preparation, but arises after saccade execution when the flash location is constructed from memory.

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