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The Influence of Target Perturbation on Manual Aiming Asymmetries in Right-Handers
THE INFLUENCE OF TARGET PERTURBATION ON MANUAL AIMING ASYMMETRIES IN RIGHT-BANDERS* Digby Elliott!, James Lyons 1, Romeo Chua 2 , David Goodman 2 and Richard G. Carson 3 CDepartment of Kinesiology, McMaster University, Hamilton, Ontario, Canada; 2 School of Kinesiology, Simon Fraser University, Burnaby, British Columbia, Canada; 3 Department of Human Movement Studies, University of Queensland, Brisbane, Australia)
ABSTRACT
Ten right-handed subjects performed 100 target-aiming movements with each hand. These movements were directed toward a small target on the midline. On 60% of the trials, the target remained stationary. On other randomly placed trials, the tlclrget "jumped" to a location 3 em to the right (20%) or left (20%) of its original position when the cursor had travelled 6.5 em. Although no hand differences were evident in the control condition, the right hand acquired the new target location more quickly than the left hand when the target was perturbed in either direction. Kinematic data revealed that this advantage was not due to initiating an adjustment to the initial movement more rapidly, but rather less time decelerating the corrective movement. Movement adjustments on perturbed trials were implemented more rapidly in left space than right space independent of the hand doing the aiming. These asymmetries may reflect the differential role of the two cerebral hemispheres in the control of goal-directed movements.
INTRODUCTION
R.S. Woodworth (1899) examined manual asymmetries in a one-dimensional aiming task in which subjects made reciprocal sliding movements to the beat of a metronome. In one condition subjects made these movements with full visual information (i.e., eyes open), while in another situation they were required to close their eyes. In the eyes open condition, right hand movements were more accurate than movements with the left hand, except when the movements were made very slowly. In the eyes closed situation, movements of the right hand were more precise regardless of speed. Woodworth proposed two possible explanations for this right hand advantage. In what today might be termed a motor programming explanation, he suggested that the "seat of this superiority of the right hand is probably in the motor centers" (Woodworth, 1899, p. 34). Alternatively he proposed that the difference could be due to kinesthetic feedback utilization. Specifically, since "the right hand gives better results also when the eyes are closed, it would seem that the muscle, joint and skin sensations from the right arm are probably more delicate than those from the left" (Woodworth, * This research was presented at the June 1994 Conference of the North American Society for the Psychology of Sport and Physical Activity in Clearwater Beach, Florida, U.S.A.
Cortex, (1995) 31, 685-697
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1899, p. 34). Interestingly (almost a century later) there is still controversy regarding the feedback versus programming explanation of manual aiming asymmetries. One of the most explicit statements regarding manual asymmetry, and the differential abilities of the hemispheres to utilize feedback was made by Flowers (1975, p. 39) who proposed that "the essential dexterity difference between the preferred and non-preferred hands is in the sensory or feedback control of movements rather than in the motor function per se" (his emphasis). This suggestion was based on a between task comparison of Fitts' manual aiming and rhythmic finger-tapping. Essentially Flowers (1975) found that preferred hand advantages were more pronounced for aiming than tapping, and that hand differences in aiming increased with the accuracy demands of the aiming task. The assumption of course was that aiming to a small target requires a greater need for feedback utilization, and that finger-tapping is ballistic and preprogrammed. Todor and Doane (1978) extended Flowers' findings by demonstrating that for a given index of difficulty (see Fitts, 1954), manual asymmetries were more dependent on the width of the target than movement amplitude 1• Once again, hand differences were attributed to the feedback processing demands of acquiring a small target, specifically the visual feedback processing demands. Roy (1983) also postulated that right hand manual aiming advantages were the result of the right hand system's proficiency at using feedback. Rather than manipulating target size and movement amplitude, Roy (1983) varied the instructions, emphasizing speed on one set of trials, and accuracy on another. Although the right hand outperformed the left hand in both conditions (i.e., faster and more accurate), the right hand advantage was more pronounced for the instruction set emphasizing speed. Presumably the increased temporal constraints of the instructional set, allowed the "system most proficient at processing feedback regarding the relative positions of the pencil and the target(s)" to "experience an increased advantage" (Roy, 1983, p. 276). Annett, Annett, Hudson et al. (1979) attempted to gain some understanding of the processes underlying manual asymmetry by filming subjects performing a peg-board task in which they manipulated movement amplitude and target tolerance. Like many of the studies discussed already, they found more pronounced preferred hand advantages for movement time when the target tolerances were small. In contrast to Flowers' (1975) suggestions, their film of peg placement indicated that the nonpreferred hand exhibited greater programming noise. This extra noise made it necessary for the nonpreferred hand to either make a greater number of corrections while in the target area or miss peg placement (Annett et al., 1979). In order to extend Annett et al.'s work, Todor and Cisneros (1985) mounted an accelerometer on a stylus to obtain more detailed kinematic data for a discrete Fitts' aiming task. In line with Flowers' feedback processing hypothesis, Todor
1
2 X movement amplitude)] Index of difficulty= [ Log2 ( . • target wtdth
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and Cisneros found that longer movement times for the left hand were primarily associated with the time spent in the latter portions of the movement when feedback-based adjustments are presumably being made (Carlton, 1981). This was consistent with the idea that in right-banders the left hand system is less efficient at processing visual feedback and/or less able to program fine adjustments to the movement based on vision. However, their findings are also compatible with the notion that greater programming noise will require time consuming adjustments late in the movement. Rather than assuming that vision is important for particular types of movements, Roy and Elliott (1986, 1989) manipulated vision in order to determine its influence on manual asymmetry. In an initial experiment (Roy and Elliott, 1986), subjects used a range of movement times to hit a small illuminated diode. In one condition, they were allowed full vision of their limb and the stylus during the movement, while in another condition the room lights were extinguished upon movement initiation, and remained off until the aiming movement was complete. Although aiming accuracy deteriorated less with increased speed for the right hand than the left hand, hand differences did not depend on the availability of visual feedback (see also Carson, Goodman, Chua et al., 1993; Roy, Kalbfleisch and Elliott, 1994; Roy and Elliott, 1989). Thus while visual feedback about the relative position of the moving limb and target is important, it does not appear to mediate manual asymmetries. Following Annett et al. (1979) then, preferred hand advantages in manual aiming may be related to the differential ability of the hand-hemisphere systems to select and specify appropriate muscular forces. Specifically, it was suggested that in right-banders the left hemisphere/right hand system is less variable in its motor output (Roy and Elliott, 1986, 1989). This open-loop explanation of aiming ::isymmetries stems primarily from Schmidt and colleagues' impulse variability model of the speed-accuracy relationship (Schmidt, Zelaznik, Hawkins et al., 1979). The basic tenet is that, for a given movement, specific force values must be selected, and programmed. Errors in force specification will result in trial to trial target overshooting and undershooting, or variable error in the direction of the movement. Thus the ability of a hand-hemisphere system to select and produce the appropriate muscular forces should predict end-point variability. Another characteristic of the impulse variability model (Schmidt et al., 1979) is that the variability in specifying a particular force, and therefore variable error, will increase with the absolute magnitude of the required force. In terms of manual asymmetries if the left hand system has greater difficulty specifying the forces required for a movement, then its disadvantage in terms of spatial error should be greatest for movements in which large force values are required. This idea was compatible with Roy and Elliott's (1986) finding that hand differences in movement error were most pronounced for rapid movements regardless of whether or not visual feedback was available. It is also consistent with numerous studies which indicate that hand differences in favour of the right hand increase with index of difficulty (e.g., Todor and Doane, 1978). Moreover, this explanation of manual asymmetries in aiming is similar to proposals regarding hand differences in other types of tasks such as rapid finger
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tapping (e.g., Peters, 1980; Todor and Smiley, 1985) and throwing (Calvin, 1983). Roy and Elliott (1989) examined the impulse variability account of manual asymmetry by manipulating visual feedback as well as the force requirements of the movement in the same experiment. As expected, increases in movement amplitude and decreases in movement time resulted in greater end-point variability regardless of whether or not visual information about the ongoing movement was available. Moreover, left hand aiming was more variable than right hand aiming. Contrary to the impulse variability explanation of manual asymmetries however, there were no hand by movement time or hand by movement amplitude interactions, indicating that hand differences in variable error are independent of the absolute force requirements of the movement. Carson, Elliott, Goodman et al. (1993a) came to the same conclusion based on two studies in which the force requirements of aiming movements were manipulated more directly by adding mass to the limb. Moreover in spite of the fact that the right hand exhibited superior performance regardless of the force requirements of the movement, the advantage was not reflected in kinematic measures of impulse variability such as variability in peak velocity and time to peak velocity. Although kinematic studies have failed to find hand differences in variables sensitive to trial to trial force production (Carson et al., 1993a, 1993b; Roy et al., 1994), these studies have focused on variability in the initial impulse. Perhaps hand differences may be the result of asymmetries in the ability to program and execute the small corrective movements that occur near the target (e.g., Meyer, Abrams, Kornblum et al., 1988). Presumably, these corrective movements could be based on proprioceptive feedback and visual feedback when it is available, as well as efference (Chua and Elliott, 1993). The purpose of this study was to examine the ability of the two hand hemisphere systems to rapidly adjust an already prepared movement in order to hit a target. We employed a target perturbation paradigm (e.g., Paulignan, MacKenzie, Marteniuk et al., 1991) to create a situation in which adjustments to the initial movement impulses would be necessary. Specifically, subjects performed aiming movements to a target directly in front of them, and on some trials the target shifted to the right (20%) or the left (20%) when the subject had travelled half the distance toward the original target position. By examining the resultant movement kinematics as well as kinematics in the direction of the visual perturbation, we were able to determine how quickly and how precisely subjects were able to make these adjustments with the two hands. We expected more rapid and precise adjustments when subjects were aiming with their right hand. MATERIALS AND METHODS
Subjects The subjects were 5 female and 5 male kinesiology students from McMaster University. All participants were right-handed as determined by a modified version of the Edinburgh
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Handedness Inventory (Bryden, 1977). Specifically, they all indicated a right hand or strong right hand preference for writing, throwing, drawing, using scissors and using a toothbrush.
Apparatus Subjects faced a computer monitor (AMA VGA colour monitor, model SC-431VS) located 65 em in front of the subject and raised 16 em from the table surface in order to bring it closer to eye level. A 58.5 em X 44.5 em graphics tablet (Summagraphics SummaSketch II™ professional MMII 1812) was placed directly between the subject and the monitor, so that the centre of the tablet was at the subject's midline. The subject held a computer mouse (SummaSketch™ 4-button mouse) with the hand specified by trial order in such a way that the tip of the index finger rested at the anterior end of the mouse. The location of the mouse on the tablet, and thus the location of the index finger, was translated into the coordinates of a cursor on the monitor such that a 1 mm displacement of the mouse resulted in a I mm displacement of the cursor on the screen. This cursor appeared as a solid blue circle 3 mm in diamter. The output signal from the graphics tablet was sent to a computer (AMA325 386 computer) and was sampled at a rate of 139.08 Hz. In order to occlude vision of the moving limb, a black plastic screen was placed over the tablet in such a way to shield the limb from view while allowing free movement.
Procedure The subject was seated facing the graphics tablet and monitor, close enough to the table so that the ensuing reaching movements did not necessitate full extension of the arm. Each trial began with the appearance of a home circle. This 8 mm diameter red circle, with a central opening of 4 mm, served as the starting position for each trial. Following the appearance of the home circle, the cursor appeared on the screen and the subject was instructed to move the mouse such that the cursor was positioned in the centre of the home circle. Three seconds after the appearance of the cursor, a circular target appeared in the upper region of the monitor display. This target was represented by a solid pink disc, 8 mm in diameter, the centre of which was located 130 mm from, and aligned with, the centre of the home circle. The subject was free to initiate movement at anytime within one second of the target's appearance, but was instructed to move as quickly and accurately as possible while trying to ensure that the cursor be in contact with the target at movement end. At the end of each trial, in all conditions, a feedback display was provided that showed the home circle, the target, and the position of the cursor at both the time of the target's appearance and at the end of the movement. Each subject participated in a single experimental session consisting of 4 blocks of 50 trials. Subjects were required to switch hands at the end of each block so that 100 trials were performed with each hand. Regardless of the hand being used, the mouse and home position were at the midline. Starting order was counterbalanced so that half of the subjects began the first block with their right hand and half began with their left. On 40 percent of the 200 total trials (i.e., 20 trials in each block of 50), the target would perturb 13.2Y (3 em) from it's central position to either the left or right of midline. The order of these perturbations was determined randomly and the perturbation was initiated once the subject had moved the cursor half the distance to the target. The subject had full vision of both the cursor and target for the duration of the movement. At the start of each session, the task was demonstrated to the subject and instructions were given. The subject then performed one block of 20 practice trials. Within this practice block, the target remained in the central position for 12 trials, was perturbed to the left on 4 trials and was perturbed to the right on 4 trials. The order of this target manipulation was determined randomly.
Data Reduction The displacement data for each trial were filtered using a second order dual pass Butterworth filter with a low pass cutoff frequency of 6.0 Hz. Instantaneous velocity was calculated by differentiating displacement data using a two point central finite difference algorithm.
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An interactive program (Chua and Elliott, 1993) was used to identify specific critical points in the X-axis and resultant displacement and velocity profiles for each trial. The beginning of a movement was identified as the moment at which the instantaneous velocity exceeded 1 mm/s. The end of the movement was considered as point at which velocity fell below 1.0 mm/s, and then remained below that threshold for a minimum of 10 sampling frames (i.e., 72 ms). Movement time and time to peak velocity were calculated by determining the number of frames between the beginning of the movement, and the end of the movement and peak velocity, respectively divided by the sampling frequency. Movement errors were identified when the distance between the centre of the target and the outer edge of the cursor was greater than 4 mm (i.e., the radius of the target). In addition to movement time, error, and resultant velocity, we were interested in the time required for subjects to adjust to a target perturbation. To this end, we examined displacement along the X-axis which was the primary dimension of the perturbation. Since on control trials, subjects exhibited different amounts of movement along the X-axis, we adopted a within-subject criterion for determining a 'significant displacement' in the direction of the target perturbation. Specifically, for each control trial and for each subject, we determined a maximum absolute displacement in X. We then calculated a single mean and standard deviation for these maximum displacements based on the I 20 control trials. For each subject, a significant deviation in the direction of the perturbation was considered the first point after target perturbation at which displacement in X was equal to or greater than the mean maximum displacement plus one standard deviation. 'Time to adjust' to the perturbation was calculated by subtracting the frame number at which the perturbation occurred from the frame number at which the first significant deviation occurred, and dividing by the sampling rate (139.08 Hz). While the rules we developed for determining 'time to adjust' values were based on statistical rather than biological criteria, it is interesting that in pilot work, 'time to adjust' values were very close to conservative estimates of visual processing time (e.g., Keele and Posner, 1968; cf. Carlton, 1992). RESULTS
Sixty percent of all trials were control trials in which the target remained stationary. Initial within-subject t-tests were conducted on these control data in order to identify any performance or kinematic differences between the two hands. Our measures of performance were movement time, the within-subject standard deviation of movement time, and the proportion of trials in which the end position of the cursor was not within the boundary of the target (i.e., movement errors). Our kinematic measures included peak resultant velocity, and time to peak velocity, as well as the within-subject standard deviation of these two variables. We also examined the proportion of the total movement time that subjects spent prior to peak velocity in order to examine the overall temporal symmetry of the profile. Since on the perturbed trials, the target could move to either the right or left, these data were analyzed using a 2 hand by 2 side of space repeated measures analysis of variance. Once again, our measures of overall performance were movement time and the within-subject standard deviation of movement time, as well as the proportion of trials with errors. We also examined resultant peak velocity, time to peak velocity and their within-subject standard deviations as well as the proportion of time to peak velocity. One of our most important measures in this study was what we have termed 'time to adjust'. As described earlier, this is the time between the perturbation and significant deviation from a control trajectory in the direction of the perturbed target (i.e., X-axis). Other indices of how subjects responded to the perturbation include the time between
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TABLE I
Mean Peak Velocity (PV), Time to Peak Velocity (TPV), Percentage Time to Peak Velocity (% TPV) and the Within-Subject Standard Deviation of Peak Velocity (SD-PV) and Time to Peak Velocity (SD-TPV) for Control Trials as a Function of Hand Hand
Dependent variable
Left
Right
PV (mm/s) TPV (ms) % TPV SD-PV (mm/s) SD-TPV (ms)
419 248 30.0 77.6 56.6
433 239 29.8 75.6 58.0
the perturbation and peak velocity in the X-axis, as well as time between the perturbation and the end of the movement. This latter variable provides an indication of how quickly subjects were able to complete the new movement requirements. Control Trials The movement time analyses revealed a slight, but nonreliable advantage for the right hand (833 ms) over the left hand (859 ms), t = 1.58, d.f. = 9, p = .078 (one-tailed). While these movement times may appear long for the index of difficulty employed in this study (i.e., 5 bits), they are consistent with other studies employing this type of indirect stimulus-response mapping (e.g., Chua and Elliott, 1993). The analysis of within-subject variability in movement time yielded similar results (right hand SO= 170 ms, left hand SO= 175 m). The difference between the two hands in the proportion of trials with errors again was in the expected direction (right hand=.101, left hand=.138), but not significant, t=1.41, d.f.=9, p=.10 (one tailed) 2 • The kinematic results are reported in Table I. When performing with the right hand and the left hand, subjects achieved similar peak velocities at similar times after movement initiation (p> .10). For both the right hand and the left hand approximately 30% of the movement time occurred prior to peak velocity. This type of skewed velocity profile is typical when subjects are aiming at medium to high index of difficulty targets (Chua and Elliott, 1993). In addition to average performance, we examined within-subject consistency in peak velocity and time to peak velocity. The within-subject standard deviations for these two variables were again similar for the two hands (p>.10). Perturbed Trials These data were examined using a 2 hand by 2 side of space repeated measures analysis of variance. The movement time analysis yielded a main effect for hand (F=5.4; d.f.=1, 9; p<.05) with the right hand (1058 ms) 2 Analyses of movement time and all other performance and kinematic variables were also done with error trials excluded. These analyses yielded almost identical results.
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Mean Movement Time (MT), Within-Subject Standard Deviation of Movement Time (SD-MT), and Number of Errors on Perturbed Trials as a Function of Hand and Side of Space
Dependent variable MT (ms) SD-MT (ms) # of errors
Left hand
Right hand
Left space
Right space
Left space
Right space
1092 194 2.3
1131
1061 183
1055
213 2.5
1.9
173 1.8
outperforming the left hand (1112 ms). As well, the within-subject variability of movement time analysis revealed that subjects were more variable with their left hand (204 ms) than their right hand (178 ms) (F= 4.95; d.f. = 1, 9; p = .05). There was no influence of hand nor direction of the perturbation on the number of errors (p> .10, see Table II). The analyses of the kinematic data on the perturbed trials failed to reveal any differences between the hands in peak resultant velocity or time to peak velocity (p> .1 0). Since there was also no reliable difference between the hands in time after peak velocity (right hand=816 ms, left hand=854 ms, p>.lO), the movement time effect appears to be a function of both temporal intervals. Thus, the proportion of time to peak velocity was similar for the two hands (right hand= .231, left hand= .235), and more skewed than the velocity profiles on the control trials. Although there was no impact of hand, the direction of the perturbation had a reliable impact on peak velocity (F = 6.67; d.f. = 1, 9; p< .05) and time to peak velocity (F = 6.03; d.f. = 1, 9; p<.05). Subjects achieved higher peak velocities when moving to targets perturbed to the left (427 mm/s) than targets perturbed to the right (420 mm/s). As well, they achieved these peak velocities earlier in the movement (left space= 245 ms, right space= 255 ms). At first these results were puzzling, since, on average, peak velocity was achieved 37 ms prior to target perturbation. An examination of the within-subject time to peak velocity distributions however indicated that when the target was perturbed toward right space, subjects sometimes exhibited a second (late) peak in the velocity profile that was marginally larger than the first peak. These rather small effects for space on peak velocity (w 2 = .0006) and time to peak velocity (w 2 = .009) appear to be due to these aberrant trials (see Table III) 3 . Certainly, it is not surprising that the perturbation had so little effect on these early kinematic markers, since the subject was already half the distance to the target before its position was altered. . Along with mean performance, we also examined within-subject variability in peak velocity and time to peak velocity. In these analyses, neither hand nor the direction of the perturbation had an impact (p> .1 0). One of the most important variables in this study was 'time to adjust'. As mentioned earlier, this is the time between the target perturbation and a 3 Although hand did not have a reliable impact on peak velocity or time to peak velocity, it accounted for more than 4 times (peak velocity) and 2.5 times (time to peak velocity) the variance of side of space.
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Manual asymmetries TABLE Ill
Mean Peak Resultant Velocity (PV), Time to Peak Resultant Velocity (TPV), Percentage Time to Peak Resultant Velocity (% TPV) and the Within-Subject Standard Deviations of Peak Resultant Velocity (SD-PV) and Time to Peak Resultant Velocity (SD-TPV) on Perturbed Trials as a Function of Hand and Side of Space
Dependent variable PV (mm/s) TPV (ms) % TPV SD-PV (mm/s) SD-TPV (ms)
Left hand
Right hand
Left space
Right space
Left space
Right space
421 254 23,5 73.9 66.8
413 262 23.4 72.7 76.8
434 237 22.7 77.0 51.8
428 248 23.6 78.1 74.3
significant displacement in the direction of the perturbation. Surprisingly in this analysis, we failed to find any impact of hand, but did find a significant advantage when targets were perturbed to the left (241 ms) as opposed to the right (264 ms) (F= 8.75; d.f, = 1, 9; p<.05). If it is assumed that subjects fixate the initial target location, this advantage may be related ro right hemisphere/ left visual field superiority in the spatial decision-making important for movement adjustment (e.g., Kimura, 1969). Alternatively, it could reflect the attentional alerting properties of the right cerebral hemisphere (e.g,, Heilman and Valenstein, 1979), TABLE IV
Mean Time to Adjust (TAd), Time Between the Perturbation and Movement Completion (P-MC), Time Between the Perturbation and Peak Velocity in the X-axis (P-PV), and the Within-Subject Standard Deviations in P-MC (SD-PMC) as a Function of Hand and Side of Space
Dependent variable TAd (ms) P-MC (ms) P-PV (ms) SD-PMC (ms)
Left hand
Right hand
Left space
Right space
Left space
Right space
240 809 249 181
275 837 277 204
241 793 231 164
253 778 271 160
Although hand had no impact on 'time to adjust', analyses of post-pertur bation performance revealed that the hands were not behaving in the same way. Specifically, the time between the target perturbation and the completion of the movement was longer for the left hand (823 ms) than the right hand (786 ms) (F=5.21; d.f.=1, 9; p<.05), The left hand (within-subject SD=l92 ms) was also more variable than the right hand (within-subject SD= 162 ms) (F=6.37; d.f. = 1, 9; p<.05). This right hand advantage occurs in spite of the fact that the right hand did not achieve peak velocity in the X-axis any more quickly than the left hand following a perturbation (p> .1 0). Along with the 'time to adjust' findings, this pattern of result indicates that the right hand movement time advantage on perturbed trials is not due to rapidly initiating a corrective movement, but rather to completing the decelerative phase of the corrective movement more quickly.
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Speed-Accuracy Analysis In order to determine if there was any within-subject relation between move ment time and the presence of an error, biserial correlation coefficients were calculated for each subject, for each condition. These coefficients were con verted to z-scores, and used as data to compare the two hands (control tials), as well as the two sides of space (perturbed trials). While overall, subjects were slightly more accurate when they moved slowly (grand means: control z = - .301, perturbed z = - .161), there were no reliable differences between experimental conditions (p> .1 0).
DISCUSSION
The purpose of this study was to determine if the superiority of the right hand/left hemisphere system in manual aiming stems from an ability of that system to rapidly adjust any discrepancy between an initial and a required movement trajectory. We induced subjects to make rapid adjustments by per turbing, a stationary target, toward either the right or left hemispace. In order to facilitate the manipulation of target position, we employed a two dimensional aiming task in which subjects slid a mouse on a graphics tablet in order to move a cursor toward targets on a computer monitor. Elsewhere, we (Maraj, Roy, Elliott et al., 1994) have shown that this type of indirect stimulus response mapping tends to diminish the right hand advantage which is extreme ly robust in a more traditional aiming situation (e.g., Fitts and Peterson, 1964). This was again evident in our control data. Specifically when the target re mained stationary, there was a slight, but nonsignificant, movement time and accuracy advantage for the right hand. Moreover, the kinematic profiles for the two hands were similar both in terms of form and consistency. These findings are consistent with other work using a similar task, and suggest that right hand advantages in movement execution may be diminished in aiming tasks that re quire spatial translation, and therefore greater right hemisphere involvement (El liott, Roy, Goodman et al., 1993). While manual asymmetries may not be as robust for simple aiming tasks in which spatial mapping is indirect, we have also shown that asymmetries ree merge when the response requirements of the movement become more complex (Roy, Winchester, Elliott et al., 1993). This is precisely what occurred in this study. Specifically, movement time differences in favour of the right hand were evident in the perturbation conditions regardless of whether the target was moved to the right or the left. As well, subjects' movement times were more consistent when they were aiming with the right hand. Contrary to our expectations, the right hand performance superiority was not due to the time required to initially adjust to the target perturbation. Rather once the adjustment was initiated, subjects decelerated and achieved the new target position more rapidly when aiming with the right hand. While this decelerative portion of the movement has been shown to be important for visual feedback utilization (e.g., Carlton, 1981; Chua and Elliott, 1993), previous work from
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our laboratory suggests that visual feedback processing per se is not a deter minant of manual asymmetry (Carson et al., 1993b; Roy and Elliott, 1986, 1989). Perhaps the advantage of the right hand system is related to its ability to pre cisely specify the small corrective impulses necessary during the decelerative portion of the movement. Presumably for a rapidly organized movement, such as a movement toward a perturbed target, these adjustment impulses are of crit ical importance. The efficiency with which adjustments to the motion of the hand can be implemented may also be constrained by the functional organization of the limb. For example, there is evidence to suggest that the preferred and non-preferred limbs are discriminated by the degree of phase locking, and the damping and stiffness of their constituent joints. When subjects are required to repetitively produce cursive alphabetic characters and signatures (Newell and van Emmerik, 1989), or circles (van Emmerik and Newell, 1990), correlations of the linear displacements of the wrist, elbow and shoulder are significantly higher for movements of the non-preferred limb. Furthermore, when the limbs are me chanically perturbed, compensation in the non-dominant limb is equivalent ac ross all degrees of freedom, in contrast to the more local adjustment which is characteristic of the dominant limb (van Emmerik, 1991). The performance su periority of the right hand in adjusting to target perturbations, that we observed in the present experiment, may thus reflect a functional organization of the en tire limb which enables flexibility in switching between postures, or between patterns of coordination (cf. Carson, 1993). Although there were no hand differences in the time it took to adjust to the perturbation, and begin moving toward the new target position, the 'time to adjust' was shorter for both hands when the target movement was in left as opposed to right space. This advantage in left space regardless of hand may reflect a right hemisphere propensity for determining target position (Kimura, 1969), an attribute that may be particularly important in an aiming task such as ours in which the spatial mapping is indirect. Bracewell, Husain and Stein (1990) have shown that right-handed subjects are more consistent and more accurate in producing saccades to the remembered position of visual targets when those targets appeared in the left as opposed to the right visual field. They suggested that the right hemisphere may play a special role in perceptual or ganization. It is conceivable that the shorter "time to adjust" for targets in left space (and presumably the left visual field) in the current study is an expression of this right hemisphere advantage. Why right hemisphere involvement in de termining the spatial course of the movements is reflected in a side of space as opposed to a hand effect is not clear (cf. Elliott et al., 1993). Perhaps, the right hand motor control superiority in timing the muscular forces necessary for movement adjustment counteract any left hand advantage related to spatial lo calization. The direct access of targets in left space (i.e., left field, if subjects are fixating the initial target position at the time of perturbation) to the right cerebral hemisphere, however facilitates performance with both hands. From this study and other recent work in our laboratory, it appears that in right-handers both cerebral hemispheres play a role in the preparation and con trol of goal-directed aiming movements. The right cerebral hemisphere appears
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to play a more important role in localizing the target in space, and perhaps some of the initial aspects of movement organization such as determining the direction of movement. The more extensive this type of information processing, the greater the relative importance of the right cerebral hemisphere (Chua, Car son, Goodman et al., 1992; Elliott, 1991; Elliott et al., 1993; MacNeilage, Stud dert-Kennedy and Lindblom, 1987). The special capabilities of the left cerebral hemisphere are probably more related to specifying the magnitude, and timing of accelerative and decelerative muscular forces. When the precision requirements of the actual movement are greater, such as when the index of difficulty is high or in a target perturbation situation, more exact force values will be required, particularly in the vicinity of the target, and left hemisphere pre-eminence will be maximal. Thus, hand and side of space (or field) advantages can be expected to change with the specific task requirements, which reflect the relative importance of right and left hemisphere capabilities. Acknowledgement. This research was funded by the Natural Sciences and Engineering Research Council of Canada.
REFERENCES ANNETT, J., ANNETT, M., HUDSON, P.T.W., and TURNER, A. The control of movement in the preferred and non-preferred hands. Quarterly Journal of Experimental Psychology, 31: 641-652, 1979. BRACEWELL, R.M., HuSAIN, M., and STEIN, J.F. Specialization of the right hemisphere for visuomotor control. Neuropsychologia, 28: 763-775, 1990. BRYDEN, M.P. Measuring handedness with questionnaires. Neuropsychologia, 15: 617-624, 1977. CALVIN, W.H. A stone's thrown and its launch window: Timing precision and its implications for language and hominod brains. Journal of Theoretical Biology, 104: 121-135, 1983. CARLTON, L.G. Visual information: The control of aiming movements. Quarterly Journal of Experi mental Psychology, 33A: 87-93, 1981. CARLTON, L.G. Visual processing time and the control of movement. In L. Protean and D. Elliott (Eds.), Vision and Motor Control. Amsterdam: North-Holland, 1992, pp. 3-31. CARSON, R.G. Manual asymmetries: Old problems and new directions. Human Movement Science, 12: 479-506, 1993. CARSON, R.G., ELLIOTT, D., GooDMAN, D., THYER, L., CHUA, R., and RoY, E.A. The role of impulse variability in manual aiming asymmetries. Psychological Research, 55: 291-298, 1993a. CARSON, R.G., GOODMAN, D., CHUA, R., and ELLIOTT, D. Asymmetries in the regulation of visually guided aiming. Journal of Motor Behavior, 25: 21-32, 1993b. CHUA, R., CARSON, R.G., GooDMAN, D., and ELLIOTT, D. Asymmetries in the spatial localization of transformed targets. Brain and Cognition, 20: 227-235, 1992. CHUA, R., and ELLIOTT, D. Visual regulation of manual aiming. Human Movement Science, 12: 365 401, 1993. ELLIOTT, D. Human handedness reconsidered. Behavioral and Brain Sciences, 14: 341-342, 1991. ELLIOTT, D., RoY, E.A., GOODMAN, D., CARSON, R.G., CHUA, R., and MARAJ, B.K.V. Asymmetries in the preparation and control of manual aiming movements. Canadian Journal of Experimental Psychology, 47: 570-589, 1993. FITTS, P.M. The information capacity of the human motor system in controlling the amplitude of move ment. Journal of Experimental Psychology, 47: 381-391, 1954. FITTS, P.M., and PETERSON, J.R. Information capacity of discrete motor responses. Journal of Exper imental Psychology, 67: 103-112, 1964. FLOWERS, K. Handedness and controlled movement. British Journal of Psychology, 66: 39-52, 1975. HEILMAN, K.M., and V ALENSTEIN, E. Mechanisms underlying hemispatial neglect. Annals of Neurol ogy, 5: 166-170, 1979. KEELE, S.W., and PoSNER, M.I. Processing of visual feedback in rapid movements. Journal of Ex perimental Psychology, 70: 155-158, 1968.
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KIMURA, D. Spatial localization in the left and right visual fields. Canadian Journal of Psychology, 23: 445-458, 1969. MACNE!LAGE, P.F., STUDDERT-KENNEDY, M.G., and LINDBLOM, B. Primate handedness reconsidered. Behavioral and Brain Sciences, 10: 247-303, 1987. MARAJ, B.K.V., RoY, E.A., ELLIOTT, D., and LYONS, J. The influence of spatial mapping on manual aiming asymmetries. Paper presented at the North American Society for the Psychology of Sport and Physical Activity Conference, Clearwater Beach, Florida, June, 1994. MEYER, D.E., ABRAMS, R.A., KORNBLUM, S., WRIGHT, C.E., and SMITH, J.E.K. Optimality in human motor performance: Ideal control of rapid aimed movements. Psychological Review, 95: 340-370, 1988. NEWELL, K.M., and VAN EMMERIK, R.E.A. The acquisition of coordination: Preliminary analysis of learning to write. Human Movement Science, 8: 17-32, 1989. PAULIGNAN, Y., MACKENZIE, C.L., MARTENIUK, R.G., and JEANNEROD, M. Selective perturbation of visual input during prehension movements. In the effects of changing object position. Experimental Brain Research, 83: 502-512, 1991. PETERS, M. Why the preferred hand taps more quickly than the nonpreferred hand: Three experiments on handedness. Canadian Journal of Psychology, 34: 62-71, 1980. ROY, E.A. Manual performance asymmetries and motor control processes: Subject-generated changes and response parameters. Human Movement Science, 2: 271-277, 1983. ROY, E.A., and ELLIOTT, D. Manual asymmetries in visually directed aiming. Canadian Journal of Psychology, 40: 109-121, 1986. RoY, E.A., and ELLIOTT, D. Manual asymmetries in aimed movements. Quarterly Journal of Exper imental Psychology, 41A: 501-516, 1989. RoY, E.A., KALBFLEISCH, L., and ELLIOTT, D. Kinematic analysis of manual asymmetries in visual aiming movements. Brain and Cognition, 24: 289-295, 1994. RoY, E.A., WINCHESTER, T., ELLIOTT, D., and CARNAHAN, H. (1983) Spatial variability and manual asymmetries in pointing movements. Paper presented at the Canadian Society for Psychomotor Learning and Sport Psychology Conference, Montreal, October, 1993. SCHMIDT, R.A., ZELAZNIK, H.N., HAWKINS, B., FRANK, J.S., and QUINN, J.T. Motor output variability: A theory for the accuracy of rapid motor acts. Phychological Review, 86: 415-451, 1979. ToDOR, J.l., and DoANE, T. Handedness and hemispheric asymmetry in the control of movements. Journal of Motor Behavior, 10: 295-300, 1978. ToDOR, J.l., and SMILEY, A. Manual asymmetries in motor control. In E.A. Roy (Ed.), Neuropsy chological Studies of Apraxia and Related Disorders. Amsterdam: North-Holland, 1985, pp. 309 344. vAN EMMERIK, R.E.A. Multijoint stiffness and coupling dynamics in the acquisition of coordination. Paper presented at the North American Society for the Psychology of Sport and Physical Activity Conference, Asilomar, California, June 1991. VAN EMMERIK, R.E.A., and NEWELL, K.M. The influence of task and organismic constraints on in tralimb and pen-point kinematics in a drawing task. Acta Psychologica, 73: 171-190. WooDWORTH, R.S. The accuracy of voluntary movement. Psychological Review, 3 (Supplement 2), 1899. Digby Elliott, Department of Kinesiology. McMaster University, Hamilton, Ontario,
L8S
4Kl. Canada.
ABSTRACT
Ten right-handed subjects performed 100 target-aiming movements with each hand. These movements were directed toward a small target on the midline. On 60% of the trials, the target remained stationary. On other randomly placed trials, the tlclrget "jumped" to a location 3 em to the right (20%) or left (20%) of its original position when the cursor had travelled 6.5 em. Although no hand differences were evident in the control condition, the right hand acquired the new target location more quickly than the left hand when the target was perturbed in either direction. Kinematic data revealed that this advantage was not due to initiating an adjustment to the initial movement more rapidly, but rather less time decelerating the corrective movement. Movement adjustments on perturbed trials were implemented more rapidly in left space than right space independent of the hand doing the aiming. These asymmetries may reflect the differential role of the two cerebral hemispheres in the control of goal-directed movements.
INTRODUCTION
R.S. Woodworth (1899) examined manual asymmetries in a one-dimensional aiming task in which subjects made reciprocal sliding movements to the beat of a metronome. In one condition subjects made these movements with full visual information (i.e., eyes open), while in another situation they were required to close their eyes. In the eyes open condition, right hand movements were more accurate than movements with the left hand, except when the movements were made very slowly. In the eyes closed situation, movements of the right hand were more precise regardless of speed. Woodworth proposed two possible explanations for this right hand advantage. In what today might be termed a motor programming explanation, he suggested that the "seat of this superiority of the right hand is probably in the motor centers" (Woodworth, 1899, p. 34). Alternatively he proposed that the difference could be due to kinesthetic feedback utilization. Specifically, since "the right hand gives better results also when the eyes are closed, it would seem that the muscle, joint and skin sensations from the right arm are probably more delicate than those from the left" (Woodworth, * This research was presented at the June 1994 Conference of the North American Society for the Psychology of Sport and Physical Activity in Clearwater Beach, Florida, U.S.A.
Cortex, (1995) 31, 685-697
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1899, p. 34). Interestingly (almost a century later) there is still controversy regarding the feedback versus programming explanation of manual aiming asymmetries. One of the most explicit statements regarding manual asymmetry, and the differential abilities of the hemispheres to utilize feedback was made by Flowers (1975, p. 39) who proposed that "the essential dexterity difference between the preferred and non-preferred hands is in the sensory or feedback control of movements rather than in the motor function per se" (his emphasis). This suggestion was based on a between task comparison of Fitts' manual aiming and rhythmic finger-tapping. Essentially Flowers (1975) found that preferred hand advantages were more pronounced for aiming than tapping, and that hand differences in aiming increased with the accuracy demands of the aiming task. The assumption of course was that aiming to a small target requires a greater need for feedback utilization, and that finger-tapping is ballistic and preprogrammed. Todor and Doane (1978) extended Flowers' findings by demonstrating that for a given index of difficulty (see Fitts, 1954), manual asymmetries were more dependent on the width of the target than movement amplitude 1• Once again, hand differences were attributed to the feedback processing demands of acquiring a small target, specifically the visual feedback processing demands. Roy (1983) also postulated that right hand manual aiming advantages were the result of the right hand system's proficiency at using feedback. Rather than manipulating target size and movement amplitude, Roy (1983) varied the instructions, emphasizing speed on one set of trials, and accuracy on another. Although the right hand outperformed the left hand in both conditions (i.e., faster and more accurate), the right hand advantage was more pronounced for the instruction set emphasizing speed. Presumably the increased temporal constraints of the instructional set, allowed the "system most proficient at processing feedback regarding the relative positions of the pencil and the target(s)" to "experience an increased advantage" (Roy, 1983, p. 276). Annett, Annett, Hudson et al. (1979) attempted to gain some understanding of the processes underlying manual asymmetry by filming subjects performing a peg-board task in which they manipulated movement amplitude and target tolerance. Like many of the studies discussed already, they found more pronounced preferred hand advantages for movement time when the target tolerances were small. In contrast to Flowers' (1975) suggestions, their film of peg placement indicated that the nonpreferred hand exhibited greater programming noise. This extra noise made it necessary for the nonpreferred hand to either make a greater number of corrections while in the target area or miss peg placement (Annett et al., 1979). In order to extend Annett et al.'s work, Todor and Cisneros (1985) mounted an accelerometer on a stylus to obtain more detailed kinematic data for a discrete Fitts' aiming task. In line with Flowers' feedback processing hypothesis, Todor
1
2 X movement amplitude)] Index of difficulty= [ Log2 ( . • target wtdth
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and Cisneros found that longer movement times for the left hand were primarily associated with the time spent in the latter portions of the movement when feedback-based adjustments are presumably being made (Carlton, 1981). This was consistent with the idea that in right-banders the left hand system is less efficient at processing visual feedback and/or less able to program fine adjustments to the movement based on vision. However, their findings are also compatible with the notion that greater programming noise will require time consuming adjustments late in the movement. Rather than assuming that vision is important for particular types of movements, Roy and Elliott (1986, 1989) manipulated vision in order to determine its influence on manual asymmetry. In an initial experiment (Roy and Elliott, 1986), subjects used a range of movement times to hit a small illuminated diode. In one condition, they were allowed full vision of their limb and the stylus during the movement, while in another condition the room lights were extinguished upon movement initiation, and remained off until the aiming movement was complete. Although aiming accuracy deteriorated less with increased speed for the right hand than the left hand, hand differences did not depend on the availability of visual feedback (see also Carson, Goodman, Chua et al., 1993; Roy, Kalbfleisch and Elliott, 1994; Roy and Elliott, 1989). Thus while visual feedback about the relative position of the moving limb and target is important, it does not appear to mediate manual asymmetries. Following Annett et al. (1979) then, preferred hand advantages in manual aiming may be related to the differential ability of the hand-hemisphere systems to select and specify appropriate muscular forces. Specifically, it was suggested that in right-banders the left hemisphere/right hand system is less variable in its motor output (Roy and Elliott, 1986, 1989). This open-loop explanation of aiming ::isymmetries stems primarily from Schmidt and colleagues' impulse variability model of the speed-accuracy relationship (Schmidt, Zelaznik, Hawkins et al., 1979). The basic tenet is that, for a given movement, specific force values must be selected, and programmed. Errors in force specification will result in trial to trial target overshooting and undershooting, or variable error in the direction of the movement. Thus the ability of a hand-hemisphere system to select and produce the appropriate muscular forces should predict end-point variability. Another characteristic of the impulse variability model (Schmidt et al., 1979) is that the variability in specifying a particular force, and therefore variable error, will increase with the absolute magnitude of the required force. In terms of manual asymmetries if the left hand system has greater difficulty specifying the forces required for a movement, then its disadvantage in terms of spatial error should be greatest for movements in which large force values are required. This idea was compatible with Roy and Elliott's (1986) finding that hand differences in movement error were most pronounced for rapid movements regardless of whether or not visual feedback was available. It is also consistent with numerous studies which indicate that hand differences in favour of the right hand increase with index of difficulty (e.g., Todor and Doane, 1978). Moreover, this explanation of manual asymmetries in aiming is similar to proposals regarding hand differences in other types of tasks such as rapid finger
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tapping (e.g., Peters, 1980; Todor and Smiley, 1985) and throwing (Calvin, 1983). Roy and Elliott (1989) examined the impulse variability account of manual asymmetry by manipulating visual feedback as well as the force requirements of the movement in the same experiment. As expected, increases in movement amplitude and decreases in movement time resulted in greater end-point variability regardless of whether or not visual information about the ongoing movement was available. Moreover, left hand aiming was more variable than right hand aiming. Contrary to the impulse variability explanation of manual asymmetries however, there were no hand by movement time or hand by movement amplitude interactions, indicating that hand differences in variable error are independent of the absolute force requirements of the movement. Carson, Elliott, Goodman et al. (1993a) came to the same conclusion based on two studies in which the force requirements of aiming movements were manipulated more directly by adding mass to the limb. Moreover in spite of the fact that the right hand exhibited superior performance regardless of the force requirements of the movement, the advantage was not reflected in kinematic measures of impulse variability such as variability in peak velocity and time to peak velocity. Although kinematic studies have failed to find hand differences in variables sensitive to trial to trial force production (Carson et al., 1993a, 1993b; Roy et al., 1994), these studies have focused on variability in the initial impulse. Perhaps hand differences may be the result of asymmetries in the ability to program and execute the small corrective movements that occur near the target (e.g., Meyer, Abrams, Kornblum et al., 1988). Presumably, these corrective movements could be based on proprioceptive feedback and visual feedback when it is available, as well as efference (Chua and Elliott, 1993). The purpose of this study was to examine the ability of the two hand hemisphere systems to rapidly adjust an already prepared movement in order to hit a target. We employed a target perturbation paradigm (e.g., Paulignan, MacKenzie, Marteniuk et al., 1991) to create a situation in which adjustments to the initial movement impulses would be necessary. Specifically, subjects performed aiming movements to a target directly in front of them, and on some trials the target shifted to the right (20%) or the left (20%) when the subject had travelled half the distance toward the original target position. By examining the resultant movement kinematics as well as kinematics in the direction of the visual perturbation, we were able to determine how quickly and how precisely subjects were able to make these adjustments with the two hands. We expected more rapid and precise adjustments when subjects were aiming with their right hand. MATERIALS AND METHODS
Subjects The subjects were 5 female and 5 male kinesiology students from McMaster University. All participants were right-handed as determined by a modified version of the Edinburgh
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Handedness Inventory (Bryden, 1977). Specifically, they all indicated a right hand or strong right hand preference for writing, throwing, drawing, using scissors and using a toothbrush.
Apparatus Subjects faced a computer monitor (AMA VGA colour monitor, model SC-431VS) located 65 em in front of the subject and raised 16 em from the table surface in order to bring it closer to eye level. A 58.5 em X 44.5 em graphics tablet (Summagraphics SummaSketch II™ professional MMII 1812) was placed directly between the subject and the monitor, so that the centre of the tablet was at the subject's midline. The subject held a computer mouse (SummaSketch™ 4-button mouse) with the hand specified by trial order in such a way that the tip of the index finger rested at the anterior end of the mouse. The location of the mouse on the tablet, and thus the location of the index finger, was translated into the coordinates of a cursor on the monitor such that a 1 mm displacement of the mouse resulted in a I mm displacement of the cursor on the screen. This cursor appeared as a solid blue circle 3 mm in diamter. The output signal from the graphics tablet was sent to a computer (AMA325 386 computer) and was sampled at a rate of 139.08 Hz. In order to occlude vision of the moving limb, a black plastic screen was placed over the tablet in such a way to shield the limb from view while allowing free movement.
Procedure The subject was seated facing the graphics tablet and monitor, close enough to the table so that the ensuing reaching movements did not necessitate full extension of the arm. Each trial began with the appearance of a home circle. This 8 mm diameter red circle, with a central opening of 4 mm, served as the starting position for each trial. Following the appearance of the home circle, the cursor appeared on the screen and the subject was instructed to move the mouse such that the cursor was positioned in the centre of the home circle. Three seconds after the appearance of the cursor, a circular target appeared in the upper region of the monitor display. This target was represented by a solid pink disc, 8 mm in diameter, the centre of which was located 130 mm from, and aligned with, the centre of the home circle. The subject was free to initiate movement at anytime within one second of the target's appearance, but was instructed to move as quickly and accurately as possible while trying to ensure that the cursor be in contact with the target at movement end. At the end of each trial, in all conditions, a feedback display was provided that showed the home circle, the target, and the position of the cursor at both the time of the target's appearance and at the end of the movement. Each subject participated in a single experimental session consisting of 4 blocks of 50 trials. Subjects were required to switch hands at the end of each block so that 100 trials were performed with each hand. Regardless of the hand being used, the mouse and home position were at the midline. Starting order was counterbalanced so that half of the subjects began the first block with their right hand and half began with their left. On 40 percent of the 200 total trials (i.e., 20 trials in each block of 50), the target would perturb 13.2Y (3 em) from it's central position to either the left or right of midline. The order of these perturbations was determined randomly and the perturbation was initiated once the subject had moved the cursor half the distance to the target. The subject had full vision of both the cursor and target for the duration of the movement. At the start of each session, the task was demonstrated to the subject and instructions were given. The subject then performed one block of 20 practice trials. Within this practice block, the target remained in the central position for 12 trials, was perturbed to the left on 4 trials and was perturbed to the right on 4 trials. The order of this target manipulation was determined randomly.
Data Reduction The displacement data for each trial were filtered using a second order dual pass Butterworth filter with a low pass cutoff frequency of 6.0 Hz. Instantaneous velocity was calculated by differentiating displacement data using a two point central finite difference algorithm.
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An interactive program (Chua and Elliott, 1993) was used to identify specific critical points in the X-axis and resultant displacement and velocity profiles for each trial. The beginning of a movement was identified as the moment at which the instantaneous velocity exceeded 1 mm/s. The end of the movement was considered as point at which velocity fell below 1.0 mm/s, and then remained below that threshold for a minimum of 10 sampling frames (i.e., 72 ms). Movement time and time to peak velocity were calculated by determining the number of frames between the beginning of the movement, and the end of the movement and peak velocity, respectively divided by the sampling frequency. Movement errors were identified when the distance between the centre of the target and the outer edge of the cursor was greater than 4 mm (i.e., the radius of the target). In addition to movement time, error, and resultant velocity, we were interested in the time required for subjects to adjust to a target perturbation. To this end, we examined displacement along the X-axis which was the primary dimension of the perturbation. Since on control trials, subjects exhibited different amounts of movement along the X-axis, we adopted a within-subject criterion for determining a 'significant displacement' in the direction of the target perturbation. Specifically, for each control trial and for each subject, we determined a maximum absolute displacement in X. We then calculated a single mean and standard deviation for these maximum displacements based on the I 20 control trials. For each subject, a significant deviation in the direction of the perturbation was considered the first point after target perturbation at which displacement in X was equal to or greater than the mean maximum displacement plus one standard deviation. 'Time to adjust' to the perturbation was calculated by subtracting the frame number at which the perturbation occurred from the frame number at which the first significant deviation occurred, and dividing by the sampling rate (139.08 Hz). While the rules we developed for determining 'time to adjust' values were based on statistical rather than biological criteria, it is interesting that in pilot work, 'time to adjust' values were very close to conservative estimates of visual processing time (e.g., Keele and Posner, 1968; cf. Carlton, 1992). RESULTS
Sixty percent of all trials were control trials in which the target remained stationary. Initial within-subject t-tests were conducted on these control data in order to identify any performance or kinematic differences between the two hands. Our measures of performance were movement time, the within-subject standard deviation of movement time, and the proportion of trials in which the end position of the cursor was not within the boundary of the target (i.e., movement errors). Our kinematic measures included peak resultant velocity, and time to peak velocity, as well as the within-subject standard deviation of these two variables. We also examined the proportion of the total movement time that subjects spent prior to peak velocity in order to examine the overall temporal symmetry of the profile. Since on the perturbed trials, the target could move to either the right or left, these data were analyzed using a 2 hand by 2 side of space repeated measures analysis of variance. Once again, our measures of overall performance were movement time and the within-subject standard deviation of movement time, as well as the proportion of trials with errors. We also examined resultant peak velocity, time to peak velocity and their within-subject standard deviations as well as the proportion of time to peak velocity. One of our most important measures in this study was what we have termed 'time to adjust'. As described earlier, this is the time between the perturbation and significant deviation from a control trajectory in the direction of the perturbed target (i.e., X-axis). Other indices of how subjects responded to the perturbation include the time between
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TABLE I
Mean Peak Velocity (PV), Time to Peak Velocity (TPV), Percentage Time to Peak Velocity (% TPV) and the Within-Subject Standard Deviation of Peak Velocity (SD-PV) and Time to Peak Velocity (SD-TPV) for Control Trials as a Function of Hand Hand
Dependent variable
Left
Right
PV (mm/s) TPV (ms) % TPV SD-PV (mm/s) SD-TPV (ms)
419 248 30.0 77.6 56.6
433 239 29.8 75.6 58.0
the perturbation and peak velocity in the X-axis, as well as time between the perturbation and the end of the movement. This latter variable provides an indication of how quickly subjects were able to complete the new movement requirements. Control Trials The movement time analyses revealed a slight, but nonreliable advantage for the right hand (833 ms) over the left hand (859 ms), t = 1.58, d.f. = 9, p = .078 (one-tailed). While these movement times may appear long for the index of difficulty employed in this study (i.e., 5 bits), they are consistent with other studies employing this type of indirect stimulus-response mapping (e.g., Chua and Elliott, 1993). The analysis of within-subject variability in movement time yielded similar results (right hand SO= 170 ms, left hand SO= 175 m). The difference between the two hands in the proportion of trials with errors again was in the expected direction (right hand=.101, left hand=.138), but not significant, t=1.41, d.f.=9, p=.10 (one tailed) 2 • The kinematic results are reported in Table I. When performing with the right hand and the left hand, subjects achieved similar peak velocities at similar times after movement initiation (p> .10). For both the right hand and the left hand approximately 30% of the movement time occurred prior to peak velocity. This type of skewed velocity profile is typical when subjects are aiming at medium to high index of difficulty targets (Chua and Elliott, 1993). In addition to average performance, we examined within-subject consistency in peak velocity and time to peak velocity. The within-subject standard deviations for these two variables were again similar for the two hands (p>.10). Perturbed Trials These data were examined using a 2 hand by 2 side of space repeated measures analysis of variance. The movement time analysis yielded a main effect for hand (F=5.4; d.f.=1, 9; p<.05) with the right hand (1058 ms) 2 Analyses of movement time and all other performance and kinematic variables were also done with error trials excluded. These analyses yielded almost identical results.
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Mean Movement Time (MT), Within-Subject Standard Deviation of Movement Time (SD-MT), and Number of Errors on Perturbed Trials as a Function of Hand and Side of Space
Dependent variable MT (ms) SD-MT (ms) # of errors
Left hand
Right hand
Left space
Right space
Left space
Right space
1092 194 2.3
1131
1061 183
1055
213 2.5
1.9
173 1.8
outperforming the left hand (1112 ms). As well, the within-subject variability of movement time analysis revealed that subjects were more variable with their left hand (204 ms) than their right hand (178 ms) (F= 4.95; d.f. = 1, 9; p = .05). There was no influence of hand nor direction of the perturbation on the number of errors (p> .10, see Table II). The analyses of the kinematic data on the perturbed trials failed to reveal any differences between the hands in peak resultant velocity or time to peak velocity (p> .1 0). Since there was also no reliable difference between the hands in time after peak velocity (right hand=816 ms, left hand=854 ms, p>.lO), the movement time effect appears to be a function of both temporal intervals. Thus, the proportion of time to peak velocity was similar for the two hands (right hand= .231, left hand= .235), and more skewed than the velocity profiles on the control trials. Although there was no impact of hand, the direction of the perturbation had a reliable impact on peak velocity (F = 6.67; d.f. = 1, 9; p< .05) and time to peak velocity (F = 6.03; d.f. = 1, 9; p<.05). Subjects achieved higher peak velocities when moving to targets perturbed to the left (427 mm/s) than targets perturbed to the right (420 mm/s). As well, they achieved these peak velocities earlier in the movement (left space= 245 ms, right space= 255 ms). At first these results were puzzling, since, on average, peak velocity was achieved 37 ms prior to target perturbation. An examination of the within-subject time to peak velocity distributions however indicated that when the target was perturbed toward right space, subjects sometimes exhibited a second (late) peak in the velocity profile that was marginally larger than the first peak. These rather small effects for space on peak velocity (w 2 = .0006) and time to peak velocity (w 2 = .009) appear to be due to these aberrant trials (see Table III) 3 . Certainly, it is not surprising that the perturbation had so little effect on these early kinematic markers, since the subject was already half the distance to the target before its position was altered. . Along with mean performance, we also examined within-subject variability in peak velocity and time to peak velocity. In these analyses, neither hand nor the direction of the perturbation had an impact (p> .1 0). One of the most important variables in this study was 'time to adjust'. As mentioned earlier, this is the time between the target perturbation and a 3 Although hand did not have a reliable impact on peak velocity or time to peak velocity, it accounted for more than 4 times (peak velocity) and 2.5 times (time to peak velocity) the variance of side of space.
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Manual asymmetries TABLE Ill
Mean Peak Resultant Velocity (PV), Time to Peak Resultant Velocity (TPV), Percentage Time to Peak Resultant Velocity (% TPV) and the Within-Subject Standard Deviations of Peak Resultant Velocity (SD-PV) and Time to Peak Resultant Velocity (SD-TPV) on Perturbed Trials as a Function of Hand and Side of Space
Dependent variable PV (mm/s) TPV (ms) % TPV SD-PV (mm/s) SD-TPV (ms)
Left hand
Right hand
Left space
Right space
Left space
Right space
421 254 23,5 73.9 66.8
413 262 23.4 72.7 76.8
434 237 22.7 77.0 51.8
428 248 23.6 78.1 74.3
significant displacement in the direction of the perturbation. Surprisingly in this analysis, we failed to find any impact of hand, but did find a significant advantage when targets were perturbed to the left (241 ms) as opposed to the right (264 ms) (F= 8.75; d.f, = 1, 9; p<.05). If it is assumed that subjects fixate the initial target location, this advantage may be related ro right hemisphere/ left visual field superiority in the spatial decision-making important for movement adjustment (e.g., Kimura, 1969). Alternatively, it could reflect the attentional alerting properties of the right cerebral hemisphere (e.g,, Heilman and Valenstein, 1979), TABLE IV
Mean Time to Adjust (TAd), Time Between the Perturbation and Movement Completion (P-MC), Time Between the Perturbation and Peak Velocity in the X-axis (P-PV), and the Within-Subject Standard Deviations in P-MC (SD-PMC) as a Function of Hand and Side of Space
Dependent variable TAd (ms) P-MC (ms) P-PV (ms) SD-PMC (ms)
Left hand
Right hand
Left space
Right space
Left space
Right space
240 809 249 181
275 837 277 204
241 793 231 164
253 778 271 160
Although hand had no impact on 'time to adjust', analyses of post-pertur bation performance revealed that the hands were not behaving in the same way. Specifically, the time between the target perturbation and the completion of the movement was longer for the left hand (823 ms) than the right hand (786 ms) (F=5.21; d.f.=1, 9; p<.05), The left hand (within-subject SD=l92 ms) was also more variable than the right hand (within-subject SD= 162 ms) (F=6.37; d.f. = 1, 9; p<.05). This right hand advantage occurs in spite of the fact that the right hand did not achieve peak velocity in the X-axis any more quickly than the left hand following a perturbation (p> .1 0). Along with the 'time to adjust' findings, this pattern of result indicates that the right hand movement time advantage on perturbed trials is not due to rapidly initiating a corrective movement, but rather to completing the decelerative phase of the corrective movement more quickly.
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Speed-Accuracy Analysis In order to determine if there was any within-subject relation between move ment time and the presence of an error, biserial correlation coefficients were calculated for each subject, for each condition. These coefficients were con verted to z-scores, and used as data to compare the two hands (control tials), as well as the two sides of space (perturbed trials). While overall, subjects were slightly more accurate when they moved slowly (grand means: control z = - .301, perturbed z = - .161), there were no reliable differences between experimental conditions (p> .1 0).
DISCUSSION
The purpose of this study was to determine if the superiority of the right hand/left hemisphere system in manual aiming stems from an ability of that system to rapidly adjust any discrepancy between an initial and a required movement trajectory. We induced subjects to make rapid adjustments by per turbing, a stationary target, toward either the right or left hemispace. In order to facilitate the manipulation of target position, we employed a two dimensional aiming task in which subjects slid a mouse on a graphics tablet in order to move a cursor toward targets on a computer monitor. Elsewhere, we (Maraj, Roy, Elliott et al., 1994) have shown that this type of indirect stimulus response mapping tends to diminish the right hand advantage which is extreme ly robust in a more traditional aiming situation (e.g., Fitts and Peterson, 1964). This was again evident in our control data. Specifically when the target re mained stationary, there was a slight, but nonsignificant, movement time and accuracy advantage for the right hand. Moreover, the kinematic profiles for the two hands were similar both in terms of form and consistency. These findings are consistent with other work using a similar task, and suggest that right hand advantages in movement execution may be diminished in aiming tasks that re quire spatial translation, and therefore greater right hemisphere involvement (El liott, Roy, Goodman et al., 1993). While manual asymmetries may not be as robust for simple aiming tasks in which spatial mapping is indirect, we have also shown that asymmetries ree merge when the response requirements of the movement become more complex (Roy, Winchester, Elliott et al., 1993). This is precisely what occurred in this study. Specifically, movement time differences in favour of the right hand were evident in the perturbation conditions regardless of whether the target was moved to the right or the left. As well, subjects' movement times were more consistent when they were aiming with the right hand. Contrary to our expectations, the right hand performance superiority was not due to the time required to initially adjust to the target perturbation. Rather once the adjustment was initiated, subjects decelerated and achieved the new target position more rapidly when aiming with the right hand. While this decelerative portion of the movement has been shown to be important for visual feedback utilization (e.g., Carlton, 1981; Chua and Elliott, 1993), previous work from
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our laboratory suggests that visual feedback processing per se is not a deter minant of manual asymmetry (Carson et al., 1993b; Roy and Elliott, 1986, 1989). Perhaps the advantage of the right hand system is related to its ability to pre cisely specify the small corrective impulses necessary during the decelerative portion of the movement. Presumably for a rapidly organized movement, such as a movement toward a perturbed target, these adjustment impulses are of crit ical importance. The efficiency with which adjustments to the motion of the hand can be implemented may also be constrained by the functional organization of the limb. For example, there is evidence to suggest that the preferred and non-preferred limbs are discriminated by the degree of phase locking, and the damping and stiffness of their constituent joints. When subjects are required to repetitively produce cursive alphabetic characters and signatures (Newell and van Emmerik, 1989), or circles (van Emmerik and Newell, 1990), correlations of the linear displacements of the wrist, elbow and shoulder are significantly higher for movements of the non-preferred limb. Furthermore, when the limbs are me chanically perturbed, compensation in the non-dominant limb is equivalent ac ross all degrees of freedom, in contrast to the more local adjustment which is characteristic of the dominant limb (van Emmerik, 1991). The performance su periority of the right hand in adjusting to target perturbations, that we observed in the present experiment, may thus reflect a functional organization of the en tire limb which enables flexibility in switching between postures, or between patterns of coordination (cf. Carson, 1993). Although there were no hand differences in the time it took to adjust to the perturbation, and begin moving toward the new target position, the 'time to adjust' was shorter for both hands when the target movement was in left as opposed to right space. This advantage in left space regardless of hand may reflect a right hemisphere propensity for determining target position (Kimura, 1969), an attribute that may be particularly important in an aiming task such as ours in which the spatial mapping is indirect. Bracewell, Husain and Stein (1990) have shown that right-handed subjects are more consistent and more accurate in producing saccades to the remembered position of visual targets when those targets appeared in the left as opposed to the right visual field. They suggested that the right hemisphere may play a special role in perceptual or ganization. It is conceivable that the shorter "time to adjust" for targets in left space (and presumably the left visual field) in the current study is an expression of this right hemisphere advantage. Why right hemisphere involvement in de termining the spatial course of the movements is reflected in a side of space as opposed to a hand effect is not clear (cf. Elliott et al., 1993). Perhaps, the right hand motor control superiority in timing the muscular forces necessary for movement adjustment counteract any left hand advantage related to spatial lo calization. The direct access of targets in left space (i.e., left field, if subjects are fixating the initial target position at the time of perturbation) to the right cerebral hemisphere, however facilitates performance with both hands. From this study and other recent work in our laboratory, it appears that in right-handers both cerebral hemispheres play a role in the preparation and con trol of goal-directed aiming movements. The right cerebral hemisphere appears
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to play a more important role in localizing the target in space, and perhaps some of the initial aspects of movement organization such as determining the direction of movement. The more extensive this type of information processing, the greater the relative importance of the right cerebral hemisphere (Chua, Car son, Goodman et al., 1992; Elliott, 1991; Elliott et al., 1993; MacNeilage, Stud dert-Kennedy and Lindblom, 1987). The special capabilities of the left cerebral hemisphere are probably more related to specifying the magnitude, and timing of accelerative and decelerative muscular forces. When the precision requirements of the actual movement are greater, such as when the index of difficulty is high or in a target perturbation situation, more exact force values will be required, particularly in the vicinity of the target, and left hemisphere pre-eminence will be maximal. Thus, hand and side of space (or field) advantages can be expected to change with the specific task requirements, which reflect the relative importance of right and left hemisphere capabilities. Acknowledgement. This research was funded by the Natural Sciences and Engineering Research Council of Canada.
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KIMURA, D. Spatial localization in the left and right visual fields. Canadian Journal of Psychology, 23: 445-458, 1969. MACNE!LAGE, P.F., STUDDERT-KENNEDY, M.G., and LINDBLOM, B. Primate handedness reconsidered. Behavioral and Brain Sciences, 10: 247-303, 1987. MARAJ, B.K.V., RoY, E.A., ELLIOTT, D., and LYONS, J. The influence of spatial mapping on manual aiming asymmetries. Paper presented at the North American Society for the Psychology of Sport and Physical Activity Conference, Clearwater Beach, Florida, June, 1994. MEYER, D.E., ABRAMS, R.A., KORNBLUM, S., WRIGHT, C.E., and SMITH, J.E.K. Optimality in human motor performance: Ideal control of rapid aimed movements. Psychological Review, 95: 340-370, 1988. NEWELL, K.M., and VAN EMMERIK, R.E.A. The acquisition of coordination: Preliminary analysis of learning to write. Human Movement Science, 8: 17-32, 1989. PAULIGNAN, Y., MACKENZIE, C.L., MARTENIUK, R.G., and JEANNEROD, M. Selective perturbation of visual input during prehension movements. In the effects of changing object position. Experimental Brain Research, 83: 502-512, 1991. PETERS, M. Why the preferred hand taps more quickly than the nonpreferred hand: Three experiments on handedness. Canadian Journal of Psychology, 34: 62-71, 1980. ROY, E.A. Manual performance asymmetries and motor control processes: Subject-generated changes and response parameters. Human Movement Science, 2: 271-277, 1983. ROY, E.A., and ELLIOTT, D. Manual asymmetries in visually directed aiming. Canadian Journal of Psychology, 40: 109-121, 1986. RoY, E.A., and ELLIOTT, D. Manual asymmetries in aimed movements. Quarterly Journal of Exper imental Psychology, 41A: 501-516, 1989. RoY, E.A., KALBFLEISCH, L., and ELLIOTT, D. Kinematic analysis of manual asymmetries in visual aiming movements. Brain and Cognition, 24: 289-295, 1994. RoY, E.A., WINCHESTER, T., ELLIOTT, D., and CARNAHAN, H. (1983) Spatial variability and manual asymmetries in pointing movements. Paper presented at the Canadian Society for Psychomotor Learning and Sport Psychology Conference, Montreal, October, 1993. SCHMIDT, R.A., ZELAZNIK, H.N., HAWKINS, B., FRANK, J.S., and QUINN, J.T. Motor output variability: A theory for the accuracy of rapid motor acts. Phychological Review, 86: 415-451, 1979. ToDOR, J.l., and DoANE, T. Handedness and hemispheric asymmetry in the control of movements. Journal of Motor Behavior, 10: 295-300, 1978. ToDOR, J.l., and SMILEY, A. Manual asymmetries in motor control. In E.A. Roy (Ed.), Neuropsy chological Studies of Apraxia and Related Disorders. Amsterdam: North-Holland, 1985, pp. 309 344. vAN EMMERIK, R.E.A. Multijoint stiffness and coupling dynamics in the acquisition of coordination. Paper presented at the North American Society for the Psychology of Sport and Physical Activity Conference, Asilomar, California, June 1991. VAN EMMERIK, R.E.A., and NEWELL, K.M. The influence of task and organismic constraints on in tralimb and pen-point kinematics in a drawing task. Acta Psychologica, 73: 171-190. WooDWORTH, R.S. The accuracy of voluntary movement. Psychological Review, 3 (Supplement 2), 1899. Digby Elliott, Department of Kinesiology. McMaster University, Hamilton, Ontario,
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