Effect of visuomotor-map uncertainty on visuomotor adaptation

Vision and proprioception contribute to generating hand movement. If a conflict between the visual and proprioceptive feedback of hand position is given, reaching movement is disturbed initially but recovers after training. Although previous studies have predominantly investigated the adaptive change in the motor output, it is unclear whether the contributions of visual and proprioceptive feedback controls to the reaching movement are modified by visuomotor adaptation. To investigate this, we focused on the change in proprioceptive feedback control associated with visuomotor adaptation. After the adaptation to gradually introduce visuomotor rotation, the hand reached the shifted position of the visual target to move the cursor to the visual target correctly. When the cursor feedback was occasionally eliminated (probe trial), the end point of the hand movement was biased in the visual-target direction, while the movement was initiated in the adapted direction, suggesting the incomplete adaptation of proprioceptive feedback control. Moreover, after the learning of uncertain visuomotor rotation, in which the rotation angle was randomly fluctuated on a trial-by-trial basis, the end-point bias in the probe trial increased, but the initial movement direction was not affected, suggesting a reduction in the adaptation level of proprioceptive feedback control. These results suggest that the change in the relative contribution of visual and proprioceptive feedback controls to the reaching movement in response to the visuomotor-map uncertainty is involved in visuomotor adaptation, whereas feedforward control might adapt in a manner different from that of the feedback control.     

The role of proprioception and attention in a visuomotor adaptation task

The role of proprioception in the control and adaptation of visuomotor relationships is still unclear. We have studied a deafferented subject, IW, and control subjects in a task in which they used single joint elbow extension to move to a visual target, with visual feedback of the terminal position provided by a cursor displayed in the plane of their movements. We report the differences in movement accuracy between the deafferented subject and controls in the normal task and when challenged with a cognitive load, counting backwards. All subjects were less accurate when counting; this was a small effect for the controls (<10% change) but much greater for the deafferented subject (>60% change). We also examined changes in movement kinematics when the instructed amplitude was altered via a changed gain between final arm position and presentation of the feedback cursor. The deafferented subject maintained temporal movement parameters stable and altered amplitude by scaling force (i.e. changed peak velocity), whereas the controls scaled both movement velocity and duration. Finally, we compared the subjects' adaptation of movement amplitude after a period of exposure to the changed visuomotor gain. The deafferented subject was able to adapt, but his adaptation was severely impaired by the counting task. These results suggest that proprioception is not an absolute requirement for adaptation to occur. Instead, proprioception has a more subtle role to play in the adjustment to visuomotor perturbations. It has an important role in the control of reaching movements, while in the absence of proprioception, attention appears necessary to monitor movements.     

Scaling of the metrics of visually-guided arm movements during motor learning in primates

Summary Hand trajectory, tangential velocity and acceleration, time and distance until peak velocity and reaction time were analyzed during the process of learning a skilled, visually-guided arm movement. Primates were trained to move a cursor with a manipulandum from a start box to target boxes displayed on a horizontal video screen during control conditions and when the relationship (gain) between the cursor and manipulandum was altered. The animals adapted to the altered feedback over 100–200 trials. A subsequent testing phase with randomly interspersed trials using the control gain demonstrated that the animals had modified their movements appropriately for the novel gain. Examination of the kinematics revealed that in adapting to a novel gain, primates scaled movement amplitude, tangential velocity, acceleration, and duration appropriately for the distance the hand needed to travel. Yet time to peak velocity was kept constant. Reaction time also remained unchanged for three of the four animals. Movements were performed in two phases, the first from movement onset to peak velocity and the second from peak velocity until the end of the movement. During the first phase the shape of the trajectory and velocity profile were stereotypic and without evidence of any corrections, consistent with this phase being essentially open loop. However, corrections occurred in the second phase and we propose visual feedback was used to correct for the difference in hand/cursor position. Learning appeared to involve utilizing the errors from previous trials to modify the early feedforward phase of subsequent trials. Peak tangential velocity, total movement duration and distance reached at peak tangential velocity all scaled linearly with the total movement distance required at each gain. Based on regression analyses, for none of these variables were the changes in learning completely adequate to compensate for total distance required. However, distance to peak velocity scaled with peak velocity in relation to the control gain. The results show that non-human primates adopt a consistent strategy when learning to scale a multi-joint movement. The metrics of the movement scaled yet the time to peak velocity remained constant, suggesting independent control of time and amplitude. Keeping time to peak velocity constant as well as the scaling of peak velocity with distance to peak velocity are viewed as ways to simplify the learning process.     

Real-time error detection but not error correction drives automatic visuomotor adaptation

We investigated the role of visual feedback of task performance in visuomotor adaptation. Participants produced novel two degrees of freedom movements (elbow flexion–extension, forearm pronation–supination) to move a cursor towards visual targets. Following trials with no rotation, participants were exposed to a 60° visuomotor rotation, before returning to the non-rotated condition. A colour cue on each trial permitted identification of the rotated/non-rotated contexts. Participants could not see their arm but received continuous and concurrent visual feedback (CF) of a cursor representing limb position or post-trial visual feedback (PF) representing the movement trajectory. Separate groups of participants who received CF were instructed that online modifications of their movements either were, or were not, permissible as a means of improving performance. Feedforward-mediated performance improvements occurred for both CF and PF groups in the rotated environment. Furthermore, for CF participants this adaptation occurred regardless of whether feedback modifications of motor commands were permissible. Upon re-exposure to the non-rotated environment participants in the CF, but not PF, groups exhibited post-training aftereffects, manifested as greater angular deviations from a straight initial trajectory, with respect to the pre-rotation trials. Accordingly, the nature of the performance improvements that occurred was dependent upon the timing of the visual feedback of task performance. Continuous visual feedback of task performance during task execution appears critical in realising automatic visuomotor adaptation through a recalibration of the visuomotor mapping that transforms visual inputs into appropriate motor commands.     

The effect of target modality on visual and proprioceptive contributions to the control of movement distance

The goal of this study was to determine whether the sensory nature of a target influences the roles of vision and proprioception in the planning of movement distance. Two groups of subjects made rapid, elbow extension movements, either toward a visual target or toward the index fingertip of the unseen opposite hand. Visual feedback of the reaching index fingertip was only available before movement onset. Using a virtual reality display, we randomly introduced a discrepancy between actual and virtual (cursor) fingertip location. When subjects reached toward the visual target, movement distance varied with changes in visual information about initial hand position. For the proprioceptive target, movement distance varied mostly with changes in proprioceptive information about initial position. The effect of target modality was already present at the time of peak acceleration, indicating that this effect include feedforward processes. Our results suggest that the relative contributions of vision and proprioception to motor planning can change, depending on the modality in which task relevant information is represented.     

Allocation of attention for dissociated visual and motor goals

In daily life, selecting an object visually is closely intertwined with processing that object as a potential goal for action. Since visual and motor goals are typically identical, it remains unknown whether attention is primarily allocated to a visual target, a motor goal, or both. Here, we dissociated visual and motor goals using a visuomotor adaptation paradigm, in which participants reached toward a visual target using a computer mouse or a stylus pen, while the direction of the cursor was rotated 45° counter-clockwise from the direction of the hand movement. Thus, as visuomotor adaptation was accomplished, the visual target was dissociated from the movement goal. Then, we measured the locus of attention using an attention-demanding rapid serial visual presentation (RSVP) task, in which participants detected a pre-defined visual stimulus among the successive visual stimuli presented on either the visual target, the motor goal, or a neutral control location. We demonstrated that before visuomotor adaptation, participants performed better when the RSVP stream was presented at the visual target than at other locations. However, once visual and motor goals were dissociated following visuomotor adaptation, performance at the visual and motor goals was equated and better than performance at the control location. Therefore, we concluded that attentional resources are allocated both to visual target and motor goals during goal-directed reaching movements.     

Differential influence of vision and proprioception on control of movement distance

The purpose of this study was to investigate the contribution of proprioceptive and visual information about initial limb position in controlling the distance of rapid, single-joint reaching movements. Using a virtual reality environment, we systematically changed the relationship between actual and visually displayed hand position as subjects’ positioned a cursor within a start circle. No visual feedback was given during the movement. Subjects reached two visual targets (115 and 125° elbow angle) from four start locations (90, 95, 100, and 105° elbow angle) under four mismatch conditions (0, 5, 10, or 15°). A 2×4×4 ANOVA enabled us to ask whether the subjects controlled the movement distance in accord with the virtual, or the actual hand location. Our results indicate that the movement distance was mainly controlled according to the virtual start location. Whereas distance modification was most extensive for the closer target, analysis of acceleration profiles revealed that, regardless of target position, visual information about start location determined the initial peak in tangential hand acceleration. Peak acceleration scaled with peak velocity and movement distance, a phenomenon termed “pulse-height” control. In contrast, proprioceptive information about actual hand location determined the duration of acceleration, which also scaled with peak velocity and movement distance, a phenomenon termed “pulse-width” control. Because pulse-height and pulse-width mechanisms reflect movement planning and sensory-based corrective processes, respectively, our current findings indicate that vision is used primarily for planning movement distance, while proprioception is used primarily for online corrections during rapid, unseen movements toward visual targets.     

On-line corrections for visuomotor errors

This study was designed to determine how visual feedback mediates error corrections during reaching. We used visuomotor rotations to dissociate a cursor, representing finger position, from the actual finger location. We then extinguished cursor feedback at different distances from the start location to determine whether corrections were based on error extrapolation from prior cursor information. Results indicated that correction amplitude varied with the extent of cursor feedback. A second experiment tested specific aspects of error information that might mediate corrections to visuomotor rotations: rotation angle, distance between the finger and cursor positions and the duration of cursor exposure. Results showed that corrections did not depend on the amplitude of the rotation angle or the amount of time the cursor was shown. Instead, participants corrected for the cursor–finger distance, at the point where cursor feedback was last-seen. These findings suggest that within-trial corrections and inter-trial adaptation might employ different mechanisms.     

The role of visual reafferents during a pointing movement: comparative study between open-loop and closed-loop performances in monkeys before and after unilateral electrolytic lesion of the sustantia nigra

Summary In order to elucidate the compensatory role of visual feedback during movement, two experiments were designed to compare the motor performances of Papio papio baboons depending on whether the animals were able to visually control the limb trajectory (visual closed-loop condition) or not (visual open-loop condition). The visuomotor task used consisted of making trained pointing movements towards a stationary target. In experiment A, the baboons were successively presented with these two experimental conditions. The abolition of visual control was found to cause no change in either reaction time (RT) or movement time (MT), but brought about extensive pointing errors. It was also associated with a conspicuous increase in the mean velocity and the mean length of the trajectories. In experiment B, two groups of baboons were used. The monkeys in the first group were required to perform under closed loop conditions. The second group performed the pointing movement under open loop conditions. Once criterion was reached by each animal, a unilateral electrolytic lesion of the substantia nigra (SN) was performed. A comparison between the post operative performances of the animals in the two groups showed that suppression of visual cues resulted in a lengthening of the RT and a slowing of the movement speed. Moreover when visual feedback was lacking, the amplitude of the movement decreased and the finger fell short of the target. During the last post operative period, suppression of visual feedback brought about a more rapid return of RTs to their preoperative level and a more durable slowing of movement speed than with normal vision. The discussion deals with the role of visual feed-back in the control of movement preparation and execution, and with the change in mode of motor control caused by lesion of the SN. Partial exclusion of the SN might bring about a shift from the feedforward to a feedback mode relying more heavily on visual cues.     

Evidence for an eye-centered spherical representation of the visuomotor map

During visually guided movement, visual coordinates of target location must be transformed into coordinates appropriate for movement. To investigate the representation of this visuomotor coordinate transformation, we examined changes in pointing behavior induced by a local visuomotor remapping. The visual feedback of finger position was limited to one location within the workspace, at which a discrepancy was introduced between the actual and visually perceived finger position. This remapping induced a change in pointing that extended over the entire workspace and was best captured by a spherical coordinate system centered near the eyes.     

Limb position drift: implications for control of posture and movement

In the absence of visual feedback, subject reports of hand location tend to drift over time. Such drift has been attributed to a gradual reduction in the usefulness of proprioception to signal limb position. If this account is correct, drift should degrade the accuracy of movement distance and direction over a series of movements made without visual feedback. To test this hypothesis, we asked participants to perform six series of 75 repetitive movements from a visible start location to a visible target, in time with a regular, audible tone. Fingertip position feedback was given by a cursor during the first five trials in the series. Feedback was then removed, and participants were to continue on pace for the next 70 trials. Movements were made in two directions (30 degrees and 120 degrees ) from each of three start locations (initial shoulder angles of 30 degrees, 40 degrees, 50 degrees, and initial elbow angles of 90 degrees ). Over the 70 trials, the start location of each movement drifted, on average, 8 cm away from the initial start location. This drift varied systematically with movement direction, indicating that drift is related to movement production. However, despite these dramatic changes in hand position and joint configuration, movement distance and direction remained relatively constant. Inverse dynamics analysis revealed that movement preservation was accompanied by substantial modification of joint muscle torque. These results suggest that proprioception continues to be a reliable source of limb position information after prolonged time without vision, but that this information is used differently for maintaining limb position and for specifying movement trajectory.     

Differences in visuomotor control between the upper and lower visual fields

Danckert and Goodale [Exp Brain Res 137:303-308 (2001)] have shown that increases in movement time as target size decreased were greater when movements were performed in the lower compared with upper visual field. On this basis, they suggested that visual feedback processing was more effective in the lower visual field. However, despite the greater influence of target size on movement time for the lower compared to upper visual field, there were no differences in accuracy between visual fields for movements to the smallest targets. In the present study, we investigated whether superior performance would be observed in the lower visual field when movement times were constrained. Analysis of the variability in distance travelled at key kinematic markers (e.g. peak acceleration, peak velocity, and peak negative acceleration) revealed that limb trajectories were more consistent in the lower compared to upper visual field at the late stages of the movement. Also, squared correlation coefficients between the distance travelled at peak velocity and the distance at the end of the movement were smaller for movements performed in the lower visual field. These results imply that superior performance in the lower visual field was due to better utilization of visual feedback during movement execution.     

Influence of disturbances on the control of PC-mouse,goal-directed arm movements

This study concerns the influence of visuomotor rotating disturbance on motion dynamics and brain activity. It involves using a PC-mouse and introducing a predefined bias angle between the direction of motion of the mouse pointer and that of the screen cursor. Subjects were asked to execute three different tasks, designed to study the effect of visuomotor rotation on direction control, extent control or the two together. During each task, mouse movement, screen cursor movement and electroencephalograph (EEG) signals were recorded. An algorithm was used to detect and discard EEG signals contaminated by artifacts. Movement performance indexes and brain activity are used to evaluate motion control, tracking ability, learning and control. The results suggest the direction control is planned before the movement and controlled by an adaptive control while extent control is controlled by a real-time feedback. The measurements also confirm that increased motion and/or brain activity occur for bias angles in the ranges ±(90–120°) for both direction and extension controls. After-effects when changing the angle of visual rotation have been seen to be proportional to the variation in the adaptation angle.     

Visuomotor adaptation and generalization with repeated and varied training

Many studies have shown that reaching movements to visual targets can rapidly adapt to altered visual feedback of hand motion (i.e., visuomotor rotation) and generalize to new target directions. This generalization is thought to reflect the acquisition of a neural representation of the novel visuomotor environment that is localized to the particular trained direction. In these studies, participants perform movements to a small number of target locations repeatedly. However, it is unclear whether adaptation and generalization are comparable when target locations are constantly varied and participants reach to visual targets one time only. Here, we compared performance for reaches to a 30° counter-clockwise visuomotor rotation to four targets, spaced 90° apart across four areas of workspace 18 times each (repeated practice (RP)) with one time only reaching movements to 72 targets, spaced 5° apart (varied practice (VP)). For both training groups, participants performed 18 reaches to radial targets (either at the repeated or varied location) in a specific area of the workspace (i.e., one of four quadrants) before reaching in the adjacent workspace. We found that the RP group adapted more completely compared to the VP group. Conversely, the VP group generalized to new target directions more completely when reaching without cursor feedback compared to the RP group. This suggests that RP and VP follow a mainly common pattern of adaptation and generalization represented in the brain, with benefits of faster adaptation with RP and more complete generalization with VP.     

The effects of aging on the asymmetry of inter-limb transfer in a visuomotor task

The direction of the asymmetry of inter-limb transfer has been suggested to identify the specialization of each hemisphere when performing a motor task. In an earlier study, we showed that trajectory information is only transferred from the right to the left hand, while final movement outcome-associated parameters transferred in both directions when right-hand-dominant individuals perform a motor task with visual distorted feedback. In the current study, we try to replicate this finding in young adults and test whether the asymmetry of inter-limb transfer in visuomotor task reduces in older adults, suggesting that hemispheric lateralization reduces with age. Young and older adults (all right-hand-dominant) performed a multidirectional point-to-point drawing task in which the visual feedback was rotated and the gain was increased. Half of the participants in each age group trained with the right hand and the other half trained with the left hand. Performances of both hands with non-distorted and distorted visual feedback were collected from all participants before and after the training session. The results showed that the pattern of inter-limb transfer was similar between young and older adults, i.e., inter-limb transfer is asymmetric for initial direction and symmetric for movement time and trajectory length. The results suggest that older adults retain the specialized functions of the non-dominant (right) hemisphere allowing them to program movement direction of a graphic aiming task when visual feedback is distorted.     

The role of the cross-sensory error signal in visuomotor adaptation

Reaching to targets with misaligned visual feedback of the hand leads to changes in proprioceptive estimates of hand position and reach aftereffects. In such tasks, subjects are able to make use of two error signals: the discrepancy between the desired and actual movement, known as the sensorimotor error signal, and the discrepancy between visual and proprioceptive estimates of hand position, which we refer to as the cross-sensory error signal. We have recently shown that mere exposure to a sensory discrepancy in the absence of goal-directed movement (i.e. no sensorimotor error signal) is sufficient to produce similar changes in felt hand position and reach aftereffects. Here, we sought to determine the extent that this cross-sensory error signal can contribute to proprioceptive recalibration and movement aftereffects by manipulating the magnitude of this signal in the absence of volitional aiming movements. Subjects pushed their hand out along a robot-generated linear path that was gradually rotated clockwise relative to the path of a cursor. On all trials, subjects viewed a cursor that headed directly towards a remembered target while their hand moved out synchronously. After exposure to a 30° rotated hand-cursor distortion, subjects recalibrated their sense of felt hand position and adapted their reaches. However, no additional increases in recalibration or aftereffects were observed following further increases in the cross-sensory error signal (e.g. up to 70°). This is in contrast to our previous study where subjects freely reached to targets with misaligned visual hand position feedback, hence experiencing both sensorimotor and cross-sensory errors, and the distortion magnitude systematically predicted increases in proprioceptive recalibration and reach aftereffects. Given these findings, we suggest that the cross-sensory error signal results in changes to felt hand position which drive partial reach aftereffects, while larger aftereffects that are produced after visuomotor adaptation (and that vary with the size of distortion) are related to the sensorimotor error signal.     

Changes in motor cortical activity during visuomotor adaptation

We examined neuronal activity in three motor cortical areas while a rhesus monkey adapted to novel visuomotor transforms. The monkey moved a joystick that controlled a cursor on a video screen. Each trial began with the joystick centered. Next, the cursor appeared in one of eight positions, arranged in a circle around a target stimulus at the center of the screen. To receive reinforcement, the monkey moved the joystick so that the cursor contacted the target continuously for 1s. The video monitor provided continuous visual feedback of both cursor and target position. With those elements of the task constant, we modified the transform between joystick movement and that of the cursor at the beginning of a block of trials. Neuronal activity was studied as the monkey adapted to these novel joystick-cursor transforms. Some novel tasks included spatial transforms such as single-axis inversions, asymmetric double-axis inversions and angular deviations (also known as rotations). Other tasks involved changes in the spatiotemporal pattern and magnitude of joystick movement. As the monkey adapted to various visuomotor tasks, 209 task-related neurons (selected for stable background activity) showed significant changes in their task-related activity: 88 neurons in the primary motor cortex (M1), 32 in the supplementary motor cortex (M2), and 89 in the caudal part of the dorsal premotor cortex (PMdc). Slightly more than half of the sample in each area showed significant changes in the magnitude of activity modulation during adaptation, with the number of increases approximately equaling the number of decreases. These data support the prediction that changes in task-related neuronal activity can be observed in M1 during motor adaptation, but fail to support the hypothesis that M1 and PMdc differ in this regard. When viewed in population averages, motor cortex continued to change its activity for at least dozens of trials after performance reached a plateau. This slow, apparently continuing change in the pattern and magnitude of task-related activity may reflect the initial phases of consolidating the motor memory for preparing and executing visuomotor skills.     

Target-, limb-, and context-dependent neural activity in the cingulate and supplementary motor areas of the monkey

Very little is known about the role of the cingulate motor area (CMA) in visually guided reaching compared to other cortical motor areas. To investigate the hierarchical role of the caudal CMA (CMAc) during reaching we recorded the activity of neurons in CMAc in comparison to the supplementary motor area proper (SMA) while a monkey performed an instructed delay task that required it to position a cursor over visual targets on a computer screen using two-dimensional (2D) joystick movements. The direction of the monkeys arm movement was dissociated from the direction of the visual target by periodically reversing the relationship between the direction of movement of the joystick and that of the cursor. Neurons that responded maximally with a particular limb movement direction regardless of target location were classified as limb-dependent, whereas neurons that responded maximally to a particular target direction regardless of the direction of limb movement were classified as target-dependent. Neurons whose activity was directional in one of the two visuomotor mapping conditions and non-directional or inactive in the other were categorized as context-dependent. Limb-dependent activity was observed more frequently than target-dependent activity in both CMAc and SMA proper during both the delay period (preparatory activity; CMAc, 17%; SMA, 31%) and during movement execution (CMAc, 49%, SMA, 48%). A modest percentage of neurons with preparatory activity were target-dependent in both CMAc (11%) and SMA proper (8%) and a similar percentage of neurons in both areas demonstrated target-dependent, movement activity (CMAc, 8%; SMA, 10%). The surprising finding was that a very large percentage of neurons in both areas displayed context-dependent activity either during the preparatory (CMAc, 72%; SMA, 61%) or movement (CMAc, 43%, SMA 42%) epochs of the task. These results show that neural activity in both CMAc and SMA can directly represent movement direction in either limb-centered or target-centered coordinates. The presence of target-dependent activity in CMAc, as well as SMA, suggests that both are involved in the transformation of visual target information into appropriate motor commands. Target-dependent activity has been found in the putamen, SMA, CMAc, dorsal and ventral premotor cortex, as well as primary motor cortex. This indicates that the visuomotor transformations required for visually guided reaching are carried out by a distributed network of interconnected motor areas. The large proportion of neurons with context-dependent activity suggests, however, that while both CMAc and SMA may play a role in the visuomotor transformation of target information into movement parameters, their activity is not solely coding parameters of movement, since their involvement in this process is highly condition-dependent.     

Rhythmic movements are larger and faster but with the same frequency on removal of visual feedback

The brain controls rhythmic movement through neural circuits combining visual information with proprioceptive information from the limbs. Although rhythmic movements are fundamental to everyday activities the specific details of the responsible control mechanisms remain elusive. We tested 39 young adults who performed flexion/extension movements of the forearm. We provided them with explicit knowledge of the amplitude and the speed of their movements, whereas frequency information was only implicitly available. In a series of 3 experiments, we demonstrate a tighter control of frequency compared with amplitude or speed. We found that in the absence of visual feedback, movements had larger amplitude and higher peak speed while maintaining the same frequency as when visual feedback was available; this was the case even when participants were aware of performing overly large and fast movements. Finally, when participants were asked to modulate continuously movement frequency, but not amplitude, we found the local coefficient of variability of movement frequency to be lower than that of amplitude. We suggest that a misperception of the generated amplitude in the absence of visual feedback, coupled with a highly accurate perception of generated frequency, leads to the performance of larger and faster movements with the same frequency when visual feedback is not available. Relatively low local coefficient of variability of frequency in a task that calls for continuous change in movement frequency suggests that we tend to operate at a constant frequency at the expense of variation in amplitude and peak speed.     

Speed-accuracy trade-off in the performance of pointing movements in different directions in two-dimensional space

Nine healthy subjects performed 2D pointing movements using a joystick that controlled a screen cursor. Continuous visual feedback was provided until movement completion. Three variables were systematically manipulated: (1) target distance, (2) target size and (3) target direction. A four-way factorial ANOVA was used to analyze the effects of these fixed factors and of the random factor of subject on several movement parameters. Movement time increased with increasing distance and decreasing target size and as predicted from Fitts' law. The target direction did not affect movement time. In contrast the direction, distance and size of the target significantly affected the movement time until the first zero crossing on the speed record reflecting the time to bring the arm into the vicinity of the target. Movements on the lateral axis of the horizontal plane (horizontal movements) resulted in a decrease in initial movement time compared to movements on the anterior axis of the horizontal plane (vertical movements). A significant effect of target distance and direction but not target size was observed for the magnitude of maximum acceleration, maximum speed and maximum deceleration. Horizontal movements had a larger maximum acceleration, speed and deceleration. Furthermore the maximum speed and deceleration occurred earlier in time for these horizontal movements. Finally the number of secondary peaks on the speed record increased with decreasing target size and was not affected by the target distance or target direction. In conclusion our results indicate that different movement parameters are affected by target distance, size and direction. The crucial distinction was between parameters affected by target size and direction. These parameters did not overlap. Target direction affects the first part of movement execution while target size affects the final part of movement execution. Thus a clear segmentation of movement execution in two phases is supported by these results. The implications of these results for theoretical models of speed-accuracy trade-off are discussed.