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Reaches with overlapping stimulus-response spatial relations (propointing) adhere to speed–accuracy relations as defined by Paul Fitts’ index of difficulty equation (IDFitts: in bits of information). This movement principle is attributed to response mediation via the “fast” visuomotor networks of the dorsal visual pathway. It is, however, unclear whether the executive demands of dissociating stimulus-response spatial relations by reaching mirror-symmetrical to a target (antipointing) elicits similar adherence to Fitts’ equation. Here, pro- and antipointing responses were directed to a constant target amplitude with varying target widths to provide IDFitts values of 3.0, 3.5, 4.3, and 6.3 bits. Propointing movement times linearly increased with IDFitts—a result attributed to visually based trajectory corrections. In contrast, antipointing movement times, deceleration times, and endpoint precision did not adhere to Fitts’ equation. These results indicate that antipointing renders a “slow” and offline mode of control mediated by the visuoperceptual networks of the ventral visual pathway.

We used the event-related potential (ERP) methodology to examine differences in neural processing between visually and memory-guided reaches. Consistent with previous findings (e.g., Westwood, Heath, & Roy, 2003), memory-guided reaches undershot veridical target location to a greater extent than their visually guided counterparts. Analysis of the ERP data revealed that memory-guided reaches were associated with reduced potentials over medial-frontal cortex at target presentation and following movement onset. Further, we found that the amplitudes of the potentials over medial-frontal cortex for visually and memory-guided reaches were significantly correlated with the peak accelerations and decelerations of the reaching movements. Our results suggest that memory-guided reaches are mediated by a motor plan that is generated while a target is visible, and then stored in memory until needed—a result counter to recent behavioral theories asserting that memory-guided reaches are planned just before movement onset via a stored, sensory-based target representation.

The authors manipulated the availability of monocular and binocular vision during the constituent planning and control stages of a goal-directed reaching task. Furthermore, trials were completed with or without online limb vision to determine whether monocular- or binocular-derived ego-motion cues influence the integration of visual feedback for online limb corrections. Results showed that the manipulation of visual cues during movement planning did not influence planning times or overall kinematics. During movement execution, however, binocular reaches—and particularly those completed with online limb vision—demonstrated heightened endpoint accuracy and stability, a finding directly linked to the adoption of a feedback-based mode of reaching control (i.e., online control). In contrast, reaches performed with online monocular vision produced increased endpoint error and instability and demonstrated reduced evidence of feedback-based corrections (i.e., offline control). Based on these results, the authors propose that the combination of static (i.e., target location) and dynamic (i.e., the moving limb) binocular cues serve to specifically optimize online reaching control. Moreover, results provide new evidence that differences in the kinematic and endpoint parameters of binocular and monocular reaches reflect differences in the extent to which the aforementioned engage in online and offline modes of movement control.

We investigated whether a representation of a visual target can be stored in memory and used to support the online control of reaching movements. To distinguish between the use of a stored target representation for movement planning versus online control, we employed a novel movement environment in which participants could not fully plan their action in advance of movement initiation; that is, the spatial mapping between the movement of a computer mouse and the on-screen movement of a cursor was randomly varied from trial to trial. As such, participants were required to use online control to reach the target position. Reaches were examined in full-vision and three memory-dependent conditions (0, 2, and 5 s of delay). Absolute constant error did not accumulate between full-vision and brief delay trials (i.e., the 0-s delay), suggesting a stored representation of the visual target can be used for online control of reaching given a sufficiently brief delay interval. Longer delay trials (2 and 5 s) were less accurate and more variable than brief delay trials; however, the residual accuracy of these memory-dependent actions suggests that the motor system may have access to a stored representation of the visual target for online control processes for upwards of 5 s following target occlusion.

The authors examined if previously reported anatomical asymmetries between the upper (uVF) and lower visual fields (lVF) influence the preparation and control of visually and memory-guided reaching movements. To manipulate visual field, participants maintained their visual gaze on a cue position presented above or below the location of a target object, thus resulting in reaches completed in respective uVF and lVF of peripersonal. In Experiment 1, participants performed reaches to four targets with indices of difficulty ranging from 3.1 to 5.1 bits under five visualmemory conditions: full vision and memory-guided conditions entailing 0, 2, 5, and 10 s of delay. In Experiment 2, participants reached to the vertex of Müller-Lyer figures in 3 visual-memory conditions: full vision, and memory-guided conditions entailing 0, and 2 s of delay. In accord with duplex theories of vision (e.g., Milner & Goodale, 1992), it was hypothesized that the introduction of a visual delay and/or the introduction of context-dependent illusory structure would differentially bias the efficiency and effectiveness of uVF and lVF reaches. Although data displayed mixed supported for the existence of an lVF advantage for movement execution, neither the introduction of delay nor contextual illusions succeeded in differentiating visual fields. Thus, performance advantages for movements made in the lower visual field do not appear associated with preferential connections to parietal (i.e., dorsal-action) and temporal (i.e., ventral-perception) architectures.

The present investigation sought to examine the nature of the visual information supporting online movement corrections. Participants were instructed to maintain gaze on the veridical endpoint of a neutral Müller-Lyer (ML) configuration in advance and during reaches performed with and without continuous limb vision. At movement onset, the stimulus array remained either the same (i.e., the neutral ML figure) or was perturbed to a fins-in or fins-out ML configuration. We reasoned that our illusion-based paradigm would provide a novel basis to examine the nature of the visual information supporting online movement corrections without the intrusion of putative biased ocular/manual motor interactions. Early reaching kinematics were refractory to the illusion-based perturbation; however, later kinematics were influenced in a direction consistent with the well-documented perceptual effects of the ML illusion. This illusory bias was present irrespective of the presence or absence of limb vision and the corollary extent reaches were controlled online. These results counter the view that metrical visual information specified in an egocentric frame of reference supports online movement corrections (e.g., Glover, 2004). Instead, the present results suggest online movement control is subserved by visual input specified via interacting egocentric and allocentric reference frames.

This investigation tested the proposal that a “highly accurate” and temporally unstable stored target representation is available to the motor system for the online control of memory-guided reaches. Participants reached to a target that was: (a) visible during the response, (b) extinguished at movement onset, and (c) occluded for 0, 500, 1500 and 2,500 ms in advance of response cueing. Additionally, trials were performed with (i.e., limb visible) and without (i.e., limb occluded) vision of the reaching limb. Results showed that limb occluded trials undershot the target location in each target condition, and were characterized by a primarily offline mode of control. In contrast, limb visible trials showed a consistent level of endpoint accuracy for each target condition and elicited more online reaching corrections than limb occluded trials. It is therefore proposed that a reasonably accurate and temporally stable stored target representation can be combined with vision of the moving limb for the online control of memory-guided reaches.

We investigated whether a representation of a visual target can be stored in memory and used to support the online control of reaching movements. To distinguish between the use of a stored target representation for movement planning versus online control, we employed a novel movement environment in which participants could not fully plan their action in advance of movement initiation; that is, the spatial mapping between the movement of a computer mouse and the on-screen movement of a cursor was randomly varied from trial to trial. As such, participants were required to use online control to reach the target position. Reaches were examined in full-vision and three memory-dependent conditions (0, 2, and 5 s of delay). Absolute constant error did not accumulate between full-vision and brief delay trials (i.e., the 0-s delay), suggesting a stored representation of the visual target can be used for online control of reaching given a sufficiently brief delay interval. Longer delay trials (2 and 5 s) were less accurate and more variable than brief delay trials; however, the residual accuracy of these memory-dependent actions suggests that the motor system may have access to a stored representation of the visual target for online control processes for upwards of 5 s following target occlusion.

The goal of the present investigation was to explore the putative contributions of feedforward- and feedback-based processes in the control of memory-guided reaching movements. Participants (N = 4) completed an extensive number of reaching movements (2700) to 3 midline targets (20, 30, 40 cm) in 6 visual conditions: full-vision, open-loop, and four memory-guided conditions (0, 200, 400, and 600 ms of delay). To infer limb control, we used a regression technique to examine the within-trial correspondence between the spatial position of the limb at peak acceleration, peak velocity, peak deceleration, and the ultimate movement endpoint. A high degree of within-trial correspondence would suggest that the final position of the limb was largely specified prior to movement onset and not adjusted during the action (i.e., feedforward control); conversely, a low degree of within-trial correspondence would suggest that movements were modified during the reaching trajectory (i.e., feedback control). Full-vision reaches were found to be more accurate and less variable than open-loop and memory-guided reaches. Moreover, full-vision reaches demonstrated only modest within-trial correspondence between the spatial position of the limb at each kinematic marker and the ultimate movement endpoint, suggesting that reaching accuracy was achieved by adjusting the limb trajectory throughout the course of the action. Open-loop and memory-guided movements exhibited strong within-trial correspondence between final limb position and the position of the limb at peak velocity and peak deceleration. This strong correspondence indicates that the final position of the limb was largely determined by processes that occurred before the reach was initiated; errors in the planning process were not corrected during the course of the action. Thus, and contrary to our previous findings in a video-based aiming task, it appears that stored target information is not extensively (if at all) used to modify the trajectory of reaching movements to remembered targets in peripersonal space.