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The effects of a pre-movement delay on the kinematics of prehension in middle childhood
Human Movement Science 23 (2004) 771–784 www.elsevier.com/locate/humov
The effects of a pre-movement delay on the kinematics of prehension in middle childhood Mark F. Bradshaw a, Simon J. Watt a,b,*, Kathleen M. Elliott a, Patricia M. Riddell c a
Department of Psychology, School of Human Sciences, University of Surrey, Guildford GU2 5XH, UK b School of Psychology, University of Wales, Bangor Gwynedd LL57 2AS, UK c School of Psychology, University of Reading, Reading RG6 6AL, UK Available online 11 September 2004
Abstract The present study examined the effects of a pre-movement delay on the kinematics of prehension in middle childhood. Twenty-five children between the ages of 5 and 11 years made visually open-loop reaches to two different sized objects at two different distances along the midline. Reaches took place either (i) immediately, or (ii) 2 s after the occlusion of the stimulus. In all age groups, reaches following the pre-movement delay were characterised by longer movement durations, lower peak velocities, larger peak grip apertures and longer time spent in the final slow phase of the movement. This pattern of results suggests that the representations that control the transport and grasp component are affected similarly by delay, and is consistent with the results previously reported for adults. Such representations therefore appear to develop before the age of 5. 2004 Elsevier B.V. All rights reserved. PsycINFO classification: 2323; 2330; 2820 Keywords: Prehension; Pre-response delay; Reaching; Grasping; Motor development
*
Corresponding author. Tel.: +44 0 1248 388252; fax: +44 0 1248 382599. E-mail address: [email protected] (S.J. Watt).
0167-9457/$ - see front matter 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.humov.2004.07.003
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1. Introduction We reach for and pick up objects any number of times during the day. The apparent simplicity of this routine behaviour, however, masks the enormous complexity of the problem faced by the perceptual-motor system. Visual information is vital and can be used in two ways: (i) to specify the necessary object properties in order to pre-plan the transport and grasp components of the movement, and (ii) to monitor performance ‘‘on-line’’, as the reach progresses, in order to make fine adjustments when the arm, hand and/or object are visible (Jeannerod, 1988; Piaget, 1952). On-line visual feedback plays an important role in reaching, particularly in the latter stages of the movement as the hand closes on the object (e.g., Berthier, Clifton, Gullapalli, McCall, & Robin, 1996; Churchill, Hopkins, Ro¨nnqvist, & Vogt, 2000; Connolly & Goodale, 1999; Gentilucci, Toni, Chieffi, & Pavesi, 1994; Goodale, Pe´llison, & Prablanc, 1986; Paillard, 1982; Saunders & Knill, 2003; Smyth, Katamba, & Peacock, 2004). It is clear, however, that efficient reaching also depends on an internal representation of space, and the objects within it, acquired prior to movement onset (e.g., Bradshaw & Graham, 1998; Bradshaw & Watt, 2002; Elliott & Madalena, 1987; Thomson, 1983). The existence of such a representation can be demonstrated by a simple experiment at oneÕs desk – seeing an object and then reaching for it with your eyes closed shows that objects can easily be grasped in the absence of visual feedback, and suggests that this representation of objects in space may persist for some period of time when visual access to the world is denied. Indeed, although prehensile movements are affected reliably by removing visual feedback (e.g., longer deceleration times and larger maximum grip apertures) movements made under visually open-loop conditions remain generally similar to those executed under normal viewing: the principal kinematic markers such as peak wrist velocity and grip aperture continue to scale with object properties in the normal way (Connolly & Goodale, 1999; Gentilucci et al., 1994; Jakobson & Goodale, 1991; Jeannerod, 1984) and the gradual posturing of the fingers to the shape of the object throughout the reach is unaffected by lack of vision (Winges, Weber, & Santello, 2003). In this paper we investigate the nature and development of this underlying representation for the control of prehension by examining visually open-loop prehensile movements in children aged 5–11 years. Which properties of objects must be represented in order to successfully complete a prehensile movement? We need to recover and represent information that can be used to transport the hand to the correct location (extrinsic information) and preconfigure the fingers to form a grasp in accordance with the target objectÕs size, shape and weight (intrinsic information; Jeannerod, 1984; Jeannerod, 1988). The division between extrinsic/intrinsic information is useful as it maps on to the division between the relatively independent, although temporally coupled, components of a prehensile movement: the transport component and the grasp component (Gentilucci & Rizzolatti, 1990; Jeannerod, 1984; Sakata & Taira, 1994). Experiments in primates suggest that dissociable neural systems in the premotor cortex underlie the control of the
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transport and grasp components (Gentilucci et al., 1988; Sakata & Taira, 1994; Sakata, Taira, Mine, & Murata, 1992). Also, Gallese and colleagues have shown that reversible inactivation of regions of the anterior intraparietal area produces deficits in pre-shaping of the grasp while leaving reaching unaffected (Gallese, Murata, Kaseda, Niki, & Sakata, 1994; see also Fogassi et al., 2001). Whether both intrinsic and extrinsic object properties are represented similarly by the visuo-motor system through middle childhood is a particular focus of the present paper. One way to investigate the nature of any visual representation involved in motor control in humans is to introduce a delay between the presentation of the visual information and the initiation of the movement. With adults such a paradigm has been used to investigate the representations underlying both pointing (Bradshaw & Watt, 2002; Elliott & Madalena, 1987; Heath et al., 2004; Westwood et al., 2003) and natural prehension tasks (Bradshaw & Watt, 2002; Hu, Eagleson, & Goodale, 1999). For example, Bradshaw and Watt (2002) found that after a delay of 2 s the accuracy of pointing to a remembered location, which requires extrinsic information, decreased whereas the variability of the movements remained constant. This pattern of results indicates that a representation of space is involved in the control of pointing (i.e., reliability was invariant with delay) but it is systematically distorted by the introduction of a pre-movement delay (accuracy decreased with delay). Moreover, in a further Ôperceptual-matchingÕ condition they found that both accuracy and variance were unaffected by pre-response delays of up to 4 s. The introduction of a temporal delay has also been found to have a significant effect on the kinematics of prehensile movements in adults. For example, Hu et al. (1999) found that reaches to different objects placed at a fixed distance from the observer and performed following a 5 s delay had significantly longer movement durations, reached peak velocity earlier (although peak velocity itself was not significantly affected) and consisted of significantly larger peak grip apertures. Bradshaw and Watt (2002) asked subjects to grasp objects of varying sizes at varying distances after delays of 1, 2 and 4 s and found that a 2 s delay was enough to affect significantly both the transport and grasp components of prehensile movements. They found that reaches executed following a delay consisted of lower peak velocities and larger peak grip apertures. Taken together the results from adult subjects indicate that a spatial representation for perceptual-motor control exists, and that it appears to be separate from conventional perceptual representations. These empirical results are consistent with the theoretical view advanced by Milner and Goodale (1995) of separable systems for perception and action (see Section 4) and demonstrate that temporal delay can be a useful tool for exploring the nature of visual representations. The majority of research into such representations in children has focused on infancy. It has been shown that infants of about 16 weeks old can reach for objects in both the light and in the dark (Clifton, Muir, Ashmead, & Clarkson, 1993) and in both conditions show a movement pattern related to object size. The fact that the movement patterns were also related to object size in the dark conditions suggests that some of form of mental representation of the previously encountered objects
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must have been available. Similarly, McCarty, Clifton, Ashmead, Lee, and Goubet (2001) found that 7-month old infants oriented their hands appropriately when grasping a rod, presented at different orientations, even when vision of the rod was occluded prior to movement onset (i.e., the presence of a pre-movement delay). The maintenance of veridical information about the visual world, in a form suitable for motor-control, may, however, be rather transient in children. Graham, Bradshaw, and Davis (1998) investigated the effect of a range of pre-response delays on the accuracy of pointing to locations in 3-D space by children aged between 6 and 10 years. They found that a delay of only 1 s significantly affected accuracy. In this paper we investigated the effect of delay on the ‘‘reaching-to-grasp’’ (i.e., prehensile) movements of children between the ages of 5 and 11 years. Prehension is a more complex task than those featured in the foregoing discussion as both extrinsic and intrinsic information about the object to be grasped must be maintained in a suitable form when vision is occluded. This therefore allows us to investigate the kinds of complex representations used in real world tasks. Middle childhood is also an interesting period in the development of reaching movements, throughout which the use of representations for the control of action may change and be refined. Although by the age of 2 childrenÕs reaches begin to exhibit smooth, bell-shaped velocity profiles characteristic of adult reaches (Konczak & Dichgans, 1997) the use of visual information in visuo-motor control continues to develop through middle childhood (e.g., Kuhtz-Buschbeck et al., 1998; KuhtzBuschbeck, Stolze, Johnk, Boczek-Funcke, & Illert, 1998; Pryde, Roy, & Campbell, 1998; Watt, Bradshaw, Clarke, & Elliott, 2003). In particular, the use of visual feedback to monitor and correct movements does not follow a straightforward progression from ‘‘childlike’’ reaches through to reaches that resemble those of adults. Instead, childrenÕs reliance on feedback appears to vary non-monotonically with age. At age 5–6 their reaches have been found to be essentially ‘‘ballistic’’ (i.e., they are unaffected by removal of feedback) and by age 10 they respond to the lack of feedback in a similar way to adults (see above). However, at age 7–8, they are most disrupted by the loss of visual feedback (Hay, Bard, Fleury, & Teasdale, 1991; Smyth et al., 2004). This has been interpreted as a kind of over-reliance on feedback in this age group, and as representing a transitional stage between child- and adult-style reaching (Smyth et al., 2004; von Hofsten & Ro¨sblad, 1988; see also Bard, Hay, & Fleury, 1990; Pellizzer & Hauert, 1996). In this study we examine whether the putative representation used by adults to complete open-loop or memory guided reaching is sufficiently mature in children aged 5–11 years to maintain information suitable to control natural prehensile movements. This also allows us to examine whether the representation underlying the planning of prehensile movements continues to develop in this age range during which childrenÕs use of visual feedback is changing. Moreover, by using a natural prehension task we will be able to assess whether a pre-movement delay affects differentially the control of the transport and grasp components. That is, whether both extrinsic and intrinsic information about the object-to-be-grasped is similarly retained. To do this, children were required to make visually open-loop reaches, either coincident with the occlusion of vision, or following a 2 s delay.
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2. Method 2.1. Subjects Twenty-five children between the ages of 5 and 11 years participated in the experiment and were allocated to three age groups: 5–6, 7–8 and 10–11 years. The mean ages for the groups were 6 years 2 months, 7 years 11 months and 11 years 2 months respectively. The sample consisted of four boys and 21 girls, with at least one boy in each group. The youngest and oldest group each contained eight children, and the middle group contained nine. All subjects were right handed and had normal or corrected to normal vision. 2.2. Apparatus The children were seated comfortably at a smooth black table approximately 1 m by 1 m. Their eye height was approximately 30 cm above the surface of the table. Visual information available to each subject was controlled using goggles mounted with liquid crystal lenses. The starting hand position was a 2 cm diameter start button, under the chin on the midline. This button was monitored by a microswitch, which controlled the timing of visual occlusion. Three different sized rectangular objects were used. The objects were each 2.5 cm high and 6 cm wide and differed only in their depths (i.e., front-to-back size), which were 2, 3.5 and 5 cm. To take account of differences in hand sizes across the different age groups the youngest and middle age groups reached for the 2 and 3.5 cm objects while the older group reached for the 3.5 and 5 cm objects. (Note this meant there was a common object size across age groups, although it is not necessary for the study since comparisons here are within rather than between age-groups.) The objects were placed along the midline at 15 and 25 cm from the start button. All of the children were able to reach these distances comfortably. In each condition Ôcatch trialsÕ were introduced, in which an object was placed at a random distance, in order to monitor any learning effects of distance/size combinations. ChildrenÕs movements were recorded using a three-camera MacReflex motion analysis system (Qualisys AB) operating at 120 Hz. This system tracked the position of three spherical infra-red reflective markers, attached to the nail of the thumb and forefinger, and the wrist of each subject. Movement recording was initiated by the release of the start button. 2.3. Procedure The children were instructed to make natural reaches and to pick up the objects using a precision grip (i.e., with opposed thumb and forefinger), grasping the objects front-to-back. They completed the task in two conditions: (i) visually open-loop reaching with no delay, and (ii) visually open-loop reaching with a 2 s delay. On each trial subjects initially viewed the stimulus binocularly, for 2 s. Note that this time was chosen arbitrarily and is much longer than is usually taken (<1 s.) if the subject
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controls the time of presentation to movement initiation. In the no-delay condition, they were then signalled to move by an audible ÔbeepÕ, and vision was occluded by the shutters at movement onset. In the delay condition, vision was occluded following the initial view, and the start signal sounded after a further 2 s. Prior to the signal, subjects were required to keep their finger and thumb pressed together and to depress the start button. This ensured that the start position remained constant throughout testing and that the children did not move prior to the signal. Participants completed two repetitions of each object/distance combination in each viewing condition. In addition they completed two catch trials in each viewing condition, in which an object was placed at a random distance between 5 and 25 cm along the midline. Trials were blocked by viewing condition, which was counterbalanced, and within each block, individual trials were randomised. It was essential to keep the number of trials small so that the specific object–distance combinations could not be learned. An average of five to six practice reaches in randomly varied viewing conditions were permitted prior to the experimental trials. All of the children learned the experimental protocol readily. A short break was allowed between blocks if necessary. 2.4. Dependent measures Velocity and acceleration ÔprofilesÕ were calculated from the raw data, and filtered using a zero-phase digital filtering algorithm (see Oppenheim & Schafer, 1989) with a cut-off frequency of 12 Hz. The following dependent measures were derived for each trial: (1) peak velocity of the wrist (along the midline); (2) peak grip aperture (the maximum 3-D distance between thumb and index finger); (3) movement duration; (4) time to peak velocity, as a proportion of movement duration; (5) time to peak grip aperture, as a proportion of movement duration. The time spent in the final Ôslow movement phaseÕ, as the hand makes a final approach to the object, has also been found to be a sensitive to changes in viewing conditions (e.g., Watt & Bradshaw, 2000). Therefore this was also determined for each trial in the present experiment. This was defined as the proportion of the overall movement time spent after the time at which peak wrist deceleration occurred.
3. Results For each subject the mean value of each dependent measure was calculated for each viewing condition by object size by object distance combination. For each dependent measure, these values were then entered into separate four-way (age · viewing condition · object size · object distance) mixed-measure analyses of variance. TukeyÕs honestly significant difference a posteriori tests were performed to determine the locus of any significant effect revealed by the ANOVA. Fig. 1 plots the mean results for the principal dependent measures, for each age group, in both the delay and no-delay conditions (collapsed across object size and distance). Visual inspection of Fig. 1 clearly suggests that both the transport and
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Fig. 1. Graphs of (a) mean peak wrist velocities, (b) peak grip apertures, (c) percentage times in the slow phase, and (d) overall movement durations plotted for each of the age groups. The dark bars indicate the no-delay conditions and the grey bars indicate the 2 s delay conditions. The error bars represent ±1 SEM.
grasp components of subjectsÕ reaches were affected by temporal delay. For each age group, the mean peak wrist velocity of subjectsÕ reaches was, as predicted, slower following the 2 s delay (Fig. 1a). This difference was significant at the one-tailed level (F(1, 22) = 3.36, P < 0.05). Again, as predicted, reaches made in the delay conditions had larger peak grip apertures (Fig. 1b) than in the no-delay conditions (F (1, 22) = 11.89, P < 0.005). An effect of delay was also evident in the time spent in the slow phase of the movement, as the hand made a final approach to the object (Fig. 1c). Subjects spent a longer proportion of the reach in this phase in the delay conditions than in the no-delay conditions (F(1, 22) = 47.06, P < 0.0001). This result was reflected in the overall movement durations (Fig. 1d; see below), which were longer in the delay conditions (F(1, 22) = 28.27, P < 0.0001). There was no significant main effect of age on peak wrist velocity, time in the slow phase or movement duration. However, there was a significant main effect of age on peak grip apertures (F(2, 22) = 28.27, P < 0.0001). TukeyÕs tests revealed that the older children produced significantly larger grip apertures than either the middle or younger children
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(P < 0.01). This is to be expected, however, as the older group reached for a larger object (with larger hands) than the other two age groups. It is important to note that there were no significant age · viewing condition interactions for any of the dependent measures, indicating that the three age groups were similarly affected by the introduction of the delay. The relative timing of the transport component was also affected by the introduction of the 2 s delay. The ANOVA showed that peak wrist velocity occurred earlier, as a proportion of movement duration, in the delay conditions (32%) than in the nodelay conditions (37%; F(1, 22) = 28.07, P < 0.0001). Caution must be exercised in interpreting this result, however. Fig. 2 plots the mean time to peak velocity and to the start of the slow phase (i.e. time to peak deceleration) in milliseconds, rather than as a proportion of movement duration, for each age group in the no-delay and delay conditions. It is evident from Fig. 2 that the actual time at which both peak velocity, and the start of the Ôslow movement phaseÕ occurred, were unaffected by temporal delay. Analyses of variance (employing the same design as above) confirmed that there was no significant main effect of delay on actual time to peak velocity (F(1, 22) = 0.50, P > 0.05) or time to the start of the slow phase (F(1, 22) = 2.92, P > 0.05). The apparent change in the temporal organisation of the movements can therefore be attributed to the increase in time spent in the final slow movement phase. A similar result was found for the grasp component. Peak grip aperture occurred sooner, as a proportion of the movement duration in the delay conditions (53%) than in the no-delay conditions (59%; F(1, 22) = 21.83, P < 0.001). However, the time to peak grip aperture (in milliseconds) was unaffected by delay
Fig. 2. The mean time course of reaches in each viewing condition, for each age group. Time to peak velocity is indicated by the hatched lines, time from peak velocity to peak deceleration is indicated by the dots and time in the slow phase is indicated by the solid shading. The dark bars indicate the no-delay conditions and the grey bars indicate the 2 s delay conditions.
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(F(1, 22) = 1.01, P > 0.05) which suggests that the change in the temporal co-ordination of the grasp, too, resulted from the extended time in the slow phase of the movement in the delay conditions. Under normal viewing conditions, peak wrist velocity increases as a linear function of object distance and peak grip aperture increases as a linear function of object size (Jeannerod, 1984), indicating that these properties are encoded. The extent of this scaling was determined here, to assess whether the transport and grasp components of the childrenÕs reaches corresponded to ÔnormalÕ reaches both in the no-delay and delay conditions. Fig. 3 plots the means of the slopes of the functions relating peak velocity and object distance (Fig. 3a) and peak grip aperture and object size (Fig. 3b) for each condition. Fig. 3a clearly shows that peak wrist velocities increased with object distance in all age groups, both in the delay and no-delay conditions. One-sample t-tests showed that in each case the mean slope differed significantly from zero (P < 0.001), indicating that information about object distance was available for the control of the transport component. Fig. 3a also suggests that there was less scaling overall in the delay conditions, although a two-way (age · viewing condition) ANOVA revealed that the difference in slopes did not quite reach significance (F(1, 22) = 4.01, P = 0.06). There was no effect of age on peak wrist velocity scaling. Fig. 3b shows that in the no-delay conditions, peak grip apertures also scaled with object size in the normal way. Once again, this was confirmed by the results of onesample t-tests (P < 0.001). However, a two-way (age · viewing condition) ANOVA revealed that peak grip apertures scaled significantly less with object size in the delay conditions than in the no-delay conditions (F(1, 22) = 14.05, P < 0.01). Moreover, a one-sample t-test showed that although in the younger age group children continued to scale their grip sizes according to object size following the 2 s delay (P < 0.05), in both the middle and older age group peak grip aperture scaling with object size in the delay conditions did not differ significantly from zero. peak velocity scaling with object distance
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Fig. 3. The degree of scaling of (a) peak wrist velocities, and (b) peak grip apertures with increases in object distance and size, respectively. Dark bars represent the no-delay conditions and grey bars represent the 2 s delay conditions. Error bars represent ±1 SEM.
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4. Discussion The present study was designed to assess the effects of a pre-movement delay on the transport and grasp components of prehensile movements in children between 5 and 11 years. The effect of the delay was evident in all the children tested. Compared to reaches made with no delay, reaches made after a 2 s delay were characterised by longer movement durations, lower peak velocities, larger peak grip apertures and longer time spent in the slow phase. Both transport and grasp were affected which suggests that the representation of both extrinsic and intrinsic object properties are similarly susceptible to the effect of delay. It is important to note that the children showed normal scaling of peak velocity with changes in object distance and scaling of peak grip aperture with changes in object size, indicating that they were executing normal, natural reaches in the experimental setting. One exception to this was the lack of significant scaling of peak grip aperture (although all reaches produced natural velocity and grip-opening profiles) found for the middle and older age groups in the delay conditions. These age groups may be particularly susceptible to the effects of delay in our experimental manipulation as they have been found to be more affected by the demands of open-loop reaching than younger children who are primarily ÔballisticÕ reachers (e.g. Hay et al., 1991). The addition of a memory load may have simply exacerbated this. It is interesting that, although affected by delay, the transport component still scaled reliably with object distance in these age groups. This may indicate a partial dissociation of the effect of delay on transport and grasp which might have become more pronounced if longer delays had been used (see Bradshaw & Watt, 2002). These results fit well with the ‘‘two-visual-systems hypothesis’’ advanced by Milner and Goodale (1995). They advocate that specialised processing pathways evolved to allow us to perceive and represent the world, and to act within it – so-called ‘‘perception’’ and ‘‘action’’ systems – and that these operate under very different temporal constraints. Their theory holds that the perceptual system recovers intrinsic object features and represents them in a relatively stable and enduring form, which is useful in order to perceive a stable world as our eyes and body move. Alternatively, the visuo-motor system must operate in real-time, with no interest in the retention of object related information. This is because the ego-centric positions of objects in the world, which are required to control goal directed actions, constantly change due to both ego- and object-motion. It therefore makes no sense to maintain such information in memory for long periods. Emphasis is instead given to rapid updating of information (Goodale, Jakobson, & Keillor, 1994; Milner & Goodale, 1995). Consistent with this, Bradshaw and Watt (2002) explicitly compared perception and action responses in reproducing remembered locations and found the accuracy of their perceptual response measure to be invariant with delays of up to 4 s whereas the accuracy of their action response declined significantly after just 2 s. The present finding that, in middle childhood, reach parameters are disrupted after only 2 s delay lends further support to the notion that visuo-motor representations operate over a limited time period. Interestingly, single cells in the dorsal pathway have been identified which may be the correlate of the memory for action. Hand manipulation-
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related neurons in the anterior intraparietal sulcus of monkey parietal cortex have been found which are selective for the 3-D shape, and size of objects, suggesting they may represent information for the control of grasping (Sakata & Taira, 1994; Sakata et al., 1992). Many of these have also been found to show sustained activity during the 2 s period following stimulus presentation (Murata, Gallase, Kaseda, & Sakata, 1996). The representation of intrinsic and extrinsic information about objects may help our prehension performance to remain robust and efficient. However, from Milner and GoodaleÕs theoretical viewpoint, it appears reasonable that such memorial representations should persist for only a limited duration. Such a representation appears to be present in some form as early as age 6 months (see Clifton, Rochat, Litovsky, & Perris, 1991) and, on the basis of the present results, seems to be well developed by the age of 5 years. A size–distance scaling explanation is often employed to account for the results of experiments involving changes in reach kinematics such as those reported here (e.g., Servos, Goodale, & Jakobson, 1992). Such an explanation seems unlikely to hold for our data, however. Objects misperceived as nearer (i.e., leading to lower peak velocities) should, according to size–distance scaling, also appear smaller (i.e., leading to smaller peak grip apertures) but we found ‘‘undershoots’’ in the reach were accompanied by larger grip apertures. When the extended time in the slow phase is considered along with peak velocity and peak grip aperture the data seem more consistent with children adopting a Ôconservative strategyÕ under conditions of increasing uncertainty. Reaching less far, opening the grasp wider and approaching the object more slowly provides a larger margin of safety in order to avoid collision with the target object (see also Smyth et al., 2004). Similar changes in performance have been observed in adult subjects when they are required to make speeded reaching responses or when normal closed-loop reaches are compared with conditions in which visual information is impoverished (Jackson, Jones, Newport, & Pritchard, 1997; Jakobson & Goodale, 1991; Watt & Bradshaw, 2000; Wing, Turton, & Fraser, 1986). Precise details of childrenÕs movements during the slow phase (for example, fumbling versus colliding with the objects) could not be determined on the basis of only the kinematic data from the three markers. It remains possible, therefore, that there were subtle differences between the reaches made in each age group that could not be detected. Nonetheless, it is interesting that children as young as 5 years old generally appear to adopt an adaptive ‘‘strategy’’ of slowing down the hand and opening the grasp wider, in order to deal with reduced certainty about object properties. It should be emphasised that such a strategy need not be invoked consciously (and therefore would not need to be learned explicitly), but could be an automatic result of increasing variability in perceptual estimates of object properties, here introduced by the delay which interferes with the representation of intrinsic and extrinsic object information. This outcome may be captured by a slight extension to Harris and WolpertÕs (1998) model of movement control, for example. Their model operates to constrain the end-point variance of eye or arm movements in the presence of signal-dependent ÔneuronalÕ noise in the motor system. If we consider the addition of Ôperceptual noiseÕ as a consequence of delay, then the visuo-motor control system would have to
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further reduce the signal in order to keep end-point variability approximately constant. This would lead to lower peak velocities and, consequently, more time in the slow phase and widening of the grip aperture. Overall, from the data presented here, it appears that the effects of delay on childrenÕs prehensile movements are similar to, although more pronounced than, those observed previously in adults using a similar task and temporal delay (Bradshaw & Watt, 2002; Hu et al., 1999). This suggests that the short duration representations underlying visuo-motor control are developed by the age of 5 years but remain particularly labile in terms of grip aperture formation in middle and older age groups. The short retention interval has been particularly associated with the visuo-motor, or action, system and the observed decline in performance after 2 s may reflect a critical temporal constraint for prehension. Acknowledgements This work was supported by the Wellcome Trust. Thanks to Rob McIntosh for useful discussions concerning this work, and to Terry Thacker for technical assistance. References Bard, C., Hay, L., & Fleury, M. (1990). Timing and accuracy of visually directed movements in children: Control of direction and amplitude components. Journal of Experimental Child Psychology, 50, 102–118. Berthier, N. E., Clifton, R. K., Gullapalli, V., McCall, D. D., & Robin, D. (1996). Visual information and object size in the control of reaching. Journal of Motor Behavior, 28, 187–197. Bradshaw, M. F., & Graham, J. K. (1998). Visual and motor reproduction of remembered locations: The effect of temporal delay. Investigative Ophthalmology and Visual Science, 39, S622. Bradshaw, M. F., & Watt, S. J. (2002). A dissociation of perception and action in normal human observers: The effect of temporal delay. Neuropsychologia, 40, 1766–1778. Churchill, A., Hopkins, B., Ro¨nnqvist, L., & Vogt, S. (2000). Vision of the hand and environmental context in human prehension. Experimental Brain Research, 134, 81–89. Clifton, R. K., Muir, D. W., Ashmead, D. H., & Clarkson, M. G. (1993). Is visually guided reaching in early infancy a myth? Child Development, 64, 1099–1110. Clifton, R. K., Rochat, P., Litovsky, R. Y., & Perris, E. E. (1991). Object representation guides infantsÕ reaching in the dark. Journal of Experimental Psychology: Human Perception and Performance, 17, 323–329. Connolly, J. D., & Goodale, M. A. (1999). The role of visual feedback of hand position in the control of manual prehension. Experimental Brain Research, 125, 281–286. Elliott, D., & Madalena, J. (1987). The influence of pre-movement visual information on manual aiming. The Quarterly Journal of Experimental Psychology, 39A, 541–559. Fogassi, L., Gallese, V., Buccino, G., Craighero, L., Fadiga, L., & Rizzolatti, G. (2001). Cortical mechanism for the visual guidance of hand grasping movements in the monkey – A reversible inactivation study. Brain, 124, 571–586. Gallese, V., Murata, A., Kaseda, M., Niki, N., & Sakata, H. (1994). Deficit of hand preshaping after muscimol injection in monkey parietal cortex. Neuroreport, 5, 1525–1529. Gentilucci, M., Fogassi, L., Luppino, G., Matelli, M., Camarda, R., & Rizzolatti, G. (1988). Functional organization of inferior area 6 in the macaque monkey. 1: Somatotopy and the control of proximal movements. Experimental Brain Research, 71, 475–490.
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Gentilucci, M., & Rizzolatti, G. (1990). Cortical motor control of arm and hand movements. In M. A. Goodale (Ed.), Vision and Action: The Control of Grasping. Norwood: Ablex. Gentilucci, M., Toni, I., Chieffi, S., & Pavesi, G. (1994). The role of proprioception in the control of prehension movements: A kinematic study in a peripherally deafferented patient and in normal subjects. Experimental Brain Research, 99, 483–500. Goodale, M. A., Jakobson, L. S., & Keillor, J. M. (1994). Differences in the visual control of pantomimed and natural grasping movements. Neuropsychologia, 32, 1159–1178. Goodale, M. A., Pe´llison, D., & Prablanc, C. (1986). Large adjustments in visually guided reaching do not depend on vision of the hand or perception of target displacement. Nature, 320, 748–750. Graham, J., Bradshaw, M. F., & Davis, A. (1998). The effect of pre-movement delays on pointing accuracy in middle childhood. Perception, 27, 1379–1389. Harris, C. M., & Wolpert, D. M. (1998). Signal-dependent noise determines motor planning. Nature, 394, 780–784. Hay, L., Bard, C., Fleury, M., & Teasdale, N. (1991). Kinematics of aiming in direction and amplitude: A developmental study. Acta Psychologica, 77, 203–215. Heath, M., Westwood, D. A., & Binsted, G. (2004). The control of memory-guided reaching movements in peripersonal space. Motor Control, 8, 76–106. Hu, Y., Eagleson, R., & Goodale, M. A. (1999). The effects of delay on the kinematics of grasping. Experimental Brain Research, 126, 109–116. Jackson, S. R., Jones, C. A., Newport, R., & Pritchard, C. (1997). A kinematic analysis of goal directed prehension movements executed under binocular, monocular, and memory-guided viewing conditions. Visual Cognition, 4, 113–142. Jakobson, L. S., & Goodale, M. A. (1991). Factors affecting higher-order movement planning: A kinematic analysis of human prehension. Experimental Brain Research, 86, 199–208. Jeannerod, M. (1984). The timing of natural prehension movements. Journal of Motor Behaviour, 16, 235–254. Jeannerod, M. (1988). The neural and behavioural organization of goal-directed movements. Oxford: Clarendon Press. Konczak, J., & Dichgans, J. (1997). The development towards stereotypic arm kinematics during reaching in the first 3 years of life. Experimental Brain Research, 117, 346–354. Kuhtz-Buschbeck, J. P., Stolze, H., Boczek-Funcke, A., Johnk, K., Heinrichs, H., & Illert, M. (1998). Kinematic analysis of prehension movements in children. Behavioural Brain Research, 93, 131–141. Kuhtz-Buschbeck, J. P., Stolze, H., Johnk, K., Boczek-Funcke, A., & Illert, M. (1998). Development of prehension movements in movements in children: A kinematic study. Experimental Brain Research, 122, 424–432. McCarty, M. E., Clifton, R. K., Ashmead, D. H., Lee, P., & Goubet, N. (2001). How infants use vision for grasping objects. Child Development, 72, 973–987. Milner, A. D., & Goodale, M. A. (1995). The visual brain in action. Oxford: Oxford University Press. Murata, A., Gallese, V., Kaseda, M., & Sakata, H. (1996). Parietal neurons related to memory-guided hand manipulation. Journal of Neurophysiology, 75, 2180–2186. Oppenheim, A. V., & Schafer, R. W. (1989). Discrete-time signal processing. Englewood Cliffs: Prentice Hall. Paillard, J. (1982). The contribution of peripheral and central vision to visually guided reaching. In D. J. Ingle, M. A. Goodele, & R. J. W. Mansfield (Eds.), Analysis of visual behavior. Cambridge: MIT Press. Pellizzer, G., & Hauert, C. A. (1996). Visuo-manual aiming movements in 6- to 10-year-old children: Evidence for an asymmetric and asynchronous development of information processes. Brain and Cognition, 30, 175–193. Piaget, J. (1952). The Origins of Intelligence in Children. New York: Norton. Pryde, K. M., Roy, E. A., & Campbell, K. (1998). Prehension in children and adults: The effects of object size. Human Movement Science, 17, 743–752. Sakata, H., & Taira, M. (1994). Parietal control of hand action. Current Opinion in Neurobiology, 4, 847–856.
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Sakata, H., Taira, M., Mine, S., & Murata, A. (1992). Hand-movement-related neurons of the posterior parietal cortex of the monkey: Their role in the visual guidance of hand movements. In R. Caminiti, P. B. Johnson, & Y. Burnod (Eds.), Control of Arm Movement in Space. Berlin: Springer. Saunders, J. A., & Knill, D. C. (2003). Humans use continuous visual feedback from the hand to control fast reaching movements. Experimental Brain Research, 152, 341–352. Servos, P., Goodale, M. A., & Jakobson, L. S. (1992). The role of binocular vision in prehension: A kinematic analysis. Vision Research, 32, 1513–1521. Smyth, M. M., Katamba, J., & Peacock, K. A. (2004). Development of prehension between 5 and 10 years of age: Distance scaling, grip aperture, and sight of the hand. Journal of Motor Behavior, 36, 91–103. Thomson, J. A. (1983). Is continuous visual monitoring necessary in visually guided locomotion? Journal of Experimental Psychology: Human Perception and Performance, 9, 427–443. von Hofsten, C., & Ro¨sblad, B. (1988). The integration of sensory information in the development of precise manual pointing. Neuropsychologia, 26. Watt, S. J., & Bradshaw, M. F. (2000). Binocular cues control the grasp but not the reach in natural prehension movements. Neuropsychologia, 38, 1473–1481. Watt, S. J., Bradshaw, M. F., Clarke, T. J., & Elliott, K. M. (2003). Binocular vision and prehension in middle childhood. Neuropsychologia, 41, 415–420. Westwood, D. A., Heath, M., & Roy, E. A. (2003). No evidence for accurate visuomotor memory: Systematic and variable error in memory-guided reaching. Journal of Motor Behavior, 35, 127–133. Wing, A. M., Turton, A., & Fraser, C. (1986). Grasp size and accuracy of approach in reaching. Journal of Motor Behavior, 18, 245–260. Winges, S. A., Weber, D. J., & Santello, M. (2003). The role of vision on hand preshaping during reach to grasp. Experimental Brain Research, 152, 489–498.
The effects of a pre-movement delay on the kinematics of prehension in middle childhood Mark F. Bradshaw a, Simon J. Watt a,b,*, Kathleen M. Elliott a, Patricia M. Riddell c a
Department of Psychology, School of Human Sciences, University of Surrey, Guildford GU2 5XH, UK b School of Psychology, University of Wales, Bangor Gwynedd LL57 2AS, UK c School of Psychology, University of Reading, Reading RG6 6AL, UK Available online 11 September 2004
Abstract The present study examined the effects of a pre-movement delay on the kinematics of prehension in middle childhood. Twenty-five children between the ages of 5 and 11 years made visually open-loop reaches to two different sized objects at two different distances along the midline. Reaches took place either (i) immediately, or (ii) 2 s after the occlusion of the stimulus. In all age groups, reaches following the pre-movement delay were characterised by longer movement durations, lower peak velocities, larger peak grip apertures and longer time spent in the final slow phase of the movement. This pattern of results suggests that the representations that control the transport and grasp component are affected similarly by delay, and is consistent with the results previously reported for adults. Such representations therefore appear to develop before the age of 5. 2004 Elsevier B.V. All rights reserved. PsycINFO classification: 2323; 2330; 2820 Keywords: Prehension; Pre-response delay; Reaching; Grasping; Motor development
*
Corresponding author. Tel.: +44 0 1248 388252; fax: +44 0 1248 382599. E-mail address: [email protected] (S.J. Watt).
0167-9457/$ - see front matter 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.humov.2004.07.003
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1. Introduction We reach for and pick up objects any number of times during the day. The apparent simplicity of this routine behaviour, however, masks the enormous complexity of the problem faced by the perceptual-motor system. Visual information is vital and can be used in two ways: (i) to specify the necessary object properties in order to pre-plan the transport and grasp components of the movement, and (ii) to monitor performance ‘‘on-line’’, as the reach progresses, in order to make fine adjustments when the arm, hand and/or object are visible (Jeannerod, 1988; Piaget, 1952). On-line visual feedback plays an important role in reaching, particularly in the latter stages of the movement as the hand closes on the object (e.g., Berthier, Clifton, Gullapalli, McCall, & Robin, 1996; Churchill, Hopkins, Ro¨nnqvist, & Vogt, 2000; Connolly & Goodale, 1999; Gentilucci, Toni, Chieffi, & Pavesi, 1994; Goodale, Pe´llison, & Prablanc, 1986; Paillard, 1982; Saunders & Knill, 2003; Smyth, Katamba, & Peacock, 2004). It is clear, however, that efficient reaching also depends on an internal representation of space, and the objects within it, acquired prior to movement onset (e.g., Bradshaw & Graham, 1998; Bradshaw & Watt, 2002; Elliott & Madalena, 1987; Thomson, 1983). The existence of such a representation can be demonstrated by a simple experiment at oneÕs desk – seeing an object and then reaching for it with your eyes closed shows that objects can easily be grasped in the absence of visual feedback, and suggests that this representation of objects in space may persist for some period of time when visual access to the world is denied. Indeed, although prehensile movements are affected reliably by removing visual feedback (e.g., longer deceleration times and larger maximum grip apertures) movements made under visually open-loop conditions remain generally similar to those executed under normal viewing: the principal kinematic markers such as peak wrist velocity and grip aperture continue to scale with object properties in the normal way (Connolly & Goodale, 1999; Gentilucci et al., 1994; Jakobson & Goodale, 1991; Jeannerod, 1984) and the gradual posturing of the fingers to the shape of the object throughout the reach is unaffected by lack of vision (Winges, Weber, & Santello, 2003). In this paper we investigate the nature and development of this underlying representation for the control of prehension by examining visually open-loop prehensile movements in children aged 5–11 years. Which properties of objects must be represented in order to successfully complete a prehensile movement? We need to recover and represent information that can be used to transport the hand to the correct location (extrinsic information) and preconfigure the fingers to form a grasp in accordance with the target objectÕs size, shape and weight (intrinsic information; Jeannerod, 1984; Jeannerod, 1988). The division between extrinsic/intrinsic information is useful as it maps on to the division between the relatively independent, although temporally coupled, components of a prehensile movement: the transport component and the grasp component (Gentilucci & Rizzolatti, 1990; Jeannerod, 1984; Sakata & Taira, 1994). Experiments in primates suggest that dissociable neural systems in the premotor cortex underlie the control of the
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transport and grasp components (Gentilucci et al., 1988; Sakata & Taira, 1994; Sakata, Taira, Mine, & Murata, 1992). Also, Gallese and colleagues have shown that reversible inactivation of regions of the anterior intraparietal area produces deficits in pre-shaping of the grasp while leaving reaching unaffected (Gallese, Murata, Kaseda, Niki, & Sakata, 1994; see also Fogassi et al., 2001). Whether both intrinsic and extrinsic object properties are represented similarly by the visuo-motor system through middle childhood is a particular focus of the present paper. One way to investigate the nature of any visual representation involved in motor control in humans is to introduce a delay between the presentation of the visual information and the initiation of the movement. With adults such a paradigm has been used to investigate the representations underlying both pointing (Bradshaw & Watt, 2002; Elliott & Madalena, 1987; Heath et al., 2004; Westwood et al., 2003) and natural prehension tasks (Bradshaw & Watt, 2002; Hu, Eagleson, & Goodale, 1999). For example, Bradshaw and Watt (2002) found that after a delay of 2 s the accuracy of pointing to a remembered location, which requires extrinsic information, decreased whereas the variability of the movements remained constant. This pattern of results indicates that a representation of space is involved in the control of pointing (i.e., reliability was invariant with delay) but it is systematically distorted by the introduction of a pre-movement delay (accuracy decreased with delay). Moreover, in a further Ôperceptual-matchingÕ condition they found that both accuracy and variance were unaffected by pre-response delays of up to 4 s. The introduction of a temporal delay has also been found to have a significant effect on the kinematics of prehensile movements in adults. For example, Hu et al. (1999) found that reaches to different objects placed at a fixed distance from the observer and performed following a 5 s delay had significantly longer movement durations, reached peak velocity earlier (although peak velocity itself was not significantly affected) and consisted of significantly larger peak grip apertures. Bradshaw and Watt (2002) asked subjects to grasp objects of varying sizes at varying distances after delays of 1, 2 and 4 s and found that a 2 s delay was enough to affect significantly both the transport and grasp components of prehensile movements. They found that reaches executed following a delay consisted of lower peak velocities and larger peak grip apertures. Taken together the results from adult subjects indicate that a spatial representation for perceptual-motor control exists, and that it appears to be separate from conventional perceptual representations. These empirical results are consistent with the theoretical view advanced by Milner and Goodale (1995) of separable systems for perception and action (see Section 4) and demonstrate that temporal delay can be a useful tool for exploring the nature of visual representations. The majority of research into such representations in children has focused on infancy. It has been shown that infants of about 16 weeks old can reach for objects in both the light and in the dark (Clifton, Muir, Ashmead, & Clarkson, 1993) and in both conditions show a movement pattern related to object size. The fact that the movement patterns were also related to object size in the dark conditions suggests that some of form of mental representation of the previously encountered objects
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must have been available. Similarly, McCarty, Clifton, Ashmead, Lee, and Goubet (2001) found that 7-month old infants oriented their hands appropriately when grasping a rod, presented at different orientations, even when vision of the rod was occluded prior to movement onset (i.e., the presence of a pre-movement delay). The maintenance of veridical information about the visual world, in a form suitable for motor-control, may, however, be rather transient in children. Graham, Bradshaw, and Davis (1998) investigated the effect of a range of pre-response delays on the accuracy of pointing to locations in 3-D space by children aged between 6 and 10 years. They found that a delay of only 1 s significantly affected accuracy. In this paper we investigated the effect of delay on the ‘‘reaching-to-grasp’’ (i.e., prehensile) movements of children between the ages of 5 and 11 years. Prehension is a more complex task than those featured in the foregoing discussion as both extrinsic and intrinsic information about the object to be grasped must be maintained in a suitable form when vision is occluded. This therefore allows us to investigate the kinds of complex representations used in real world tasks. Middle childhood is also an interesting period in the development of reaching movements, throughout which the use of representations for the control of action may change and be refined. Although by the age of 2 childrenÕs reaches begin to exhibit smooth, bell-shaped velocity profiles characteristic of adult reaches (Konczak & Dichgans, 1997) the use of visual information in visuo-motor control continues to develop through middle childhood (e.g., Kuhtz-Buschbeck et al., 1998; KuhtzBuschbeck, Stolze, Johnk, Boczek-Funcke, & Illert, 1998; Pryde, Roy, & Campbell, 1998; Watt, Bradshaw, Clarke, & Elliott, 2003). In particular, the use of visual feedback to monitor and correct movements does not follow a straightforward progression from ‘‘childlike’’ reaches through to reaches that resemble those of adults. Instead, childrenÕs reliance on feedback appears to vary non-monotonically with age. At age 5–6 their reaches have been found to be essentially ‘‘ballistic’’ (i.e., they are unaffected by removal of feedback) and by age 10 they respond to the lack of feedback in a similar way to adults (see above). However, at age 7–8, they are most disrupted by the loss of visual feedback (Hay, Bard, Fleury, & Teasdale, 1991; Smyth et al., 2004). This has been interpreted as a kind of over-reliance on feedback in this age group, and as representing a transitional stage between child- and adult-style reaching (Smyth et al., 2004; von Hofsten & Ro¨sblad, 1988; see also Bard, Hay, & Fleury, 1990; Pellizzer & Hauert, 1996). In this study we examine whether the putative representation used by adults to complete open-loop or memory guided reaching is sufficiently mature in children aged 5–11 years to maintain information suitable to control natural prehensile movements. This also allows us to examine whether the representation underlying the planning of prehensile movements continues to develop in this age range during which childrenÕs use of visual feedback is changing. Moreover, by using a natural prehension task we will be able to assess whether a pre-movement delay affects differentially the control of the transport and grasp components. That is, whether both extrinsic and intrinsic information about the object-to-be-grasped is similarly retained. To do this, children were required to make visually open-loop reaches, either coincident with the occlusion of vision, or following a 2 s delay.
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2. Method 2.1. Subjects Twenty-five children between the ages of 5 and 11 years participated in the experiment and were allocated to three age groups: 5–6, 7–8 and 10–11 years. The mean ages for the groups were 6 years 2 months, 7 years 11 months and 11 years 2 months respectively. The sample consisted of four boys and 21 girls, with at least one boy in each group. The youngest and oldest group each contained eight children, and the middle group contained nine. All subjects were right handed and had normal or corrected to normal vision. 2.2. Apparatus The children were seated comfortably at a smooth black table approximately 1 m by 1 m. Their eye height was approximately 30 cm above the surface of the table. Visual information available to each subject was controlled using goggles mounted with liquid crystal lenses. The starting hand position was a 2 cm diameter start button, under the chin on the midline. This button was monitored by a microswitch, which controlled the timing of visual occlusion. Three different sized rectangular objects were used. The objects were each 2.5 cm high and 6 cm wide and differed only in their depths (i.e., front-to-back size), which were 2, 3.5 and 5 cm. To take account of differences in hand sizes across the different age groups the youngest and middle age groups reached for the 2 and 3.5 cm objects while the older group reached for the 3.5 and 5 cm objects. (Note this meant there was a common object size across age groups, although it is not necessary for the study since comparisons here are within rather than between age-groups.) The objects were placed along the midline at 15 and 25 cm from the start button. All of the children were able to reach these distances comfortably. In each condition Ôcatch trialsÕ were introduced, in which an object was placed at a random distance, in order to monitor any learning effects of distance/size combinations. ChildrenÕs movements were recorded using a three-camera MacReflex motion analysis system (Qualisys AB) operating at 120 Hz. This system tracked the position of three spherical infra-red reflective markers, attached to the nail of the thumb and forefinger, and the wrist of each subject. Movement recording was initiated by the release of the start button. 2.3. Procedure The children were instructed to make natural reaches and to pick up the objects using a precision grip (i.e., with opposed thumb and forefinger), grasping the objects front-to-back. They completed the task in two conditions: (i) visually open-loop reaching with no delay, and (ii) visually open-loop reaching with a 2 s delay. On each trial subjects initially viewed the stimulus binocularly, for 2 s. Note that this time was chosen arbitrarily and is much longer than is usually taken (<1 s.) if the subject
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controls the time of presentation to movement initiation. In the no-delay condition, they were then signalled to move by an audible ÔbeepÕ, and vision was occluded by the shutters at movement onset. In the delay condition, vision was occluded following the initial view, and the start signal sounded after a further 2 s. Prior to the signal, subjects were required to keep their finger and thumb pressed together and to depress the start button. This ensured that the start position remained constant throughout testing and that the children did not move prior to the signal. Participants completed two repetitions of each object/distance combination in each viewing condition. In addition they completed two catch trials in each viewing condition, in which an object was placed at a random distance between 5 and 25 cm along the midline. Trials were blocked by viewing condition, which was counterbalanced, and within each block, individual trials were randomised. It was essential to keep the number of trials small so that the specific object–distance combinations could not be learned. An average of five to six practice reaches in randomly varied viewing conditions were permitted prior to the experimental trials. All of the children learned the experimental protocol readily. A short break was allowed between blocks if necessary. 2.4. Dependent measures Velocity and acceleration ÔprofilesÕ were calculated from the raw data, and filtered using a zero-phase digital filtering algorithm (see Oppenheim & Schafer, 1989) with a cut-off frequency of 12 Hz. The following dependent measures were derived for each trial: (1) peak velocity of the wrist (along the midline); (2) peak grip aperture (the maximum 3-D distance between thumb and index finger); (3) movement duration; (4) time to peak velocity, as a proportion of movement duration; (5) time to peak grip aperture, as a proportion of movement duration. The time spent in the final Ôslow movement phaseÕ, as the hand makes a final approach to the object, has also been found to be a sensitive to changes in viewing conditions (e.g., Watt & Bradshaw, 2000). Therefore this was also determined for each trial in the present experiment. This was defined as the proportion of the overall movement time spent after the time at which peak wrist deceleration occurred.
3. Results For each subject the mean value of each dependent measure was calculated for each viewing condition by object size by object distance combination. For each dependent measure, these values were then entered into separate four-way (age · viewing condition · object size · object distance) mixed-measure analyses of variance. TukeyÕs honestly significant difference a posteriori tests were performed to determine the locus of any significant effect revealed by the ANOVA. Fig. 1 plots the mean results for the principal dependent measures, for each age group, in both the delay and no-delay conditions (collapsed across object size and distance). Visual inspection of Fig. 1 clearly suggests that both the transport and
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Peak wrist velocity
Peak grip aperture 110 105
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Fig. 1. Graphs of (a) mean peak wrist velocities, (b) peak grip apertures, (c) percentage times in the slow phase, and (d) overall movement durations plotted for each of the age groups. The dark bars indicate the no-delay conditions and the grey bars indicate the 2 s delay conditions. The error bars represent ±1 SEM.
grasp components of subjectsÕ reaches were affected by temporal delay. For each age group, the mean peak wrist velocity of subjectsÕ reaches was, as predicted, slower following the 2 s delay (Fig. 1a). This difference was significant at the one-tailed level (F(1, 22) = 3.36, P < 0.05). Again, as predicted, reaches made in the delay conditions had larger peak grip apertures (Fig. 1b) than in the no-delay conditions (F (1, 22) = 11.89, P < 0.005). An effect of delay was also evident in the time spent in the slow phase of the movement, as the hand made a final approach to the object (Fig. 1c). Subjects spent a longer proportion of the reach in this phase in the delay conditions than in the no-delay conditions (F(1, 22) = 47.06, P < 0.0001). This result was reflected in the overall movement durations (Fig. 1d; see below), which were longer in the delay conditions (F(1, 22) = 28.27, P < 0.0001). There was no significant main effect of age on peak wrist velocity, time in the slow phase or movement duration. However, there was a significant main effect of age on peak grip apertures (F(2, 22) = 28.27, P < 0.0001). TukeyÕs tests revealed that the older children produced significantly larger grip apertures than either the middle or younger children
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(P < 0.01). This is to be expected, however, as the older group reached for a larger object (with larger hands) than the other two age groups. It is important to note that there were no significant age · viewing condition interactions for any of the dependent measures, indicating that the three age groups were similarly affected by the introduction of the delay. The relative timing of the transport component was also affected by the introduction of the 2 s delay. The ANOVA showed that peak wrist velocity occurred earlier, as a proportion of movement duration, in the delay conditions (32%) than in the nodelay conditions (37%; F(1, 22) = 28.07, P < 0.0001). Caution must be exercised in interpreting this result, however. Fig. 2 plots the mean time to peak velocity and to the start of the slow phase (i.e. time to peak deceleration) in milliseconds, rather than as a proportion of movement duration, for each age group in the no-delay and delay conditions. It is evident from Fig. 2 that the actual time at which both peak velocity, and the start of the Ôslow movement phaseÕ occurred, were unaffected by temporal delay. Analyses of variance (employing the same design as above) confirmed that there was no significant main effect of delay on actual time to peak velocity (F(1, 22) = 0.50, P > 0.05) or time to the start of the slow phase (F(1, 22) = 2.92, P > 0.05). The apparent change in the temporal organisation of the movements can therefore be attributed to the increase in time spent in the final slow movement phase. A similar result was found for the grasp component. Peak grip aperture occurred sooner, as a proportion of the movement duration in the delay conditions (53%) than in the no-delay conditions (59%; F(1, 22) = 21.83, P < 0.001). However, the time to peak grip aperture (in milliseconds) was unaffected by delay
Fig. 2. The mean time course of reaches in each viewing condition, for each age group. Time to peak velocity is indicated by the hatched lines, time from peak velocity to peak deceleration is indicated by the dots and time in the slow phase is indicated by the solid shading. The dark bars indicate the no-delay conditions and the grey bars indicate the 2 s delay conditions.
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(F(1, 22) = 1.01, P > 0.05) which suggests that the change in the temporal co-ordination of the grasp, too, resulted from the extended time in the slow phase of the movement in the delay conditions. Under normal viewing conditions, peak wrist velocity increases as a linear function of object distance and peak grip aperture increases as a linear function of object size (Jeannerod, 1984), indicating that these properties are encoded. The extent of this scaling was determined here, to assess whether the transport and grasp components of the childrenÕs reaches corresponded to ÔnormalÕ reaches both in the no-delay and delay conditions. Fig. 3 plots the means of the slopes of the functions relating peak velocity and object distance (Fig. 3a) and peak grip aperture and object size (Fig. 3b) for each condition. Fig. 3a clearly shows that peak wrist velocities increased with object distance in all age groups, both in the delay and no-delay conditions. One-sample t-tests showed that in each case the mean slope differed significantly from zero (P < 0.001), indicating that information about object distance was available for the control of the transport component. Fig. 3a also suggests that there was less scaling overall in the delay conditions, although a two-way (age · viewing condition) ANOVA revealed that the difference in slopes did not quite reach significance (F(1, 22) = 4.01, P = 0.06). There was no effect of age on peak wrist velocity scaling. Fig. 3b shows that in the no-delay conditions, peak grip apertures also scaled with object size in the normal way. Once again, this was confirmed by the results of onesample t-tests (P < 0.001). However, a two-way (age · viewing condition) ANOVA revealed that peak grip apertures scaled significantly less with object size in the delay conditions than in the no-delay conditions (F(1, 22) = 14.05, P < 0.01). Moreover, a one-sample t-test showed that although in the younger age group children continued to scale their grip sizes according to object size following the 2 s delay (P < 0.05), in both the middle and older age group peak grip aperture scaling with object size in the delay conditions did not differ significantly from zero. peak velocity scaling with object distance
peak grip aperture scaling with object size
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Fig. 3. The degree of scaling of (a) peak wrist velocities, and (b) peak grip apertures with increases in object distance and size, respectively. Dark bars represent the no-delay conditions and grey bars represent the 2 s delay conditions. Error bars represent ±1 SEM.
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4. Discussion The present study was designed to assess the effects of a pre-movement delay on the transport and grasp components of prehensile movements in children between 5 and 11 years. The effect of the delay was evident in all the children tested. Compared to reaches made with no delay, reaches made after a 2 s delay were characterised by longer movement durations, lower peak velocities, larger peak grip apertures and longer time spent in the slow phase. Both transport and grasp were affected which suggests that the representation of both extrinsic and intrinsic object properties are similarly susceptible to the effect of delay. It is important to note that the children showed normal scaling of peak velocity with changes in object distance and scaling of peak grip aperture with changes in object size, indicating that they were executing normal, natural reaches in the experimental setting. One exception to this was the lack of significant scaling of peak grip aperture (although all reaches produced natural velocity and grip-opening profiles) found for the middle and older age groups in the delay conditions. These age groups may be particularly susceptible to the effects of delay in our experimental manipulation as they have been found to be more affected by the demands of open-loop reaching than younger children who are primarily ÔballisticÕ reachers (e.g. Hay et al., 1991). The addition of a memory load may have simply exacerbated this. It is interesting that, although affected by delay, the transport component still scaled reliably with object distance in these age groups. This may indicate a partial dissociation of the effect of delay on transport and grasp which might have become more pronounced if longer delays had been used (see Bradshaw & Watt, 2002). These results fit well with the ‘‘two-visual-systems hypothesis’’ advanced by Milner and Goodale (1995). They advocate that specialised processing pathways evolved to allow us to perceive and represent the world, and to act within it – so-called ‘‘perception’’ and ‘‘action’’ systems – and that these operate under very different temporal constraints. Their theory holds that the perceptual system recovers intrinsic object features and represents them in a relatively stable and enduring form, which is useful in order to perceive a stable world as our eyes and body move. Alternatively, the visuo-motor system must operate in real-time, with no interest in the retention of object related information. This is because the ego-centric positions of objects in the world, which are required to control goal directed actions, constantly change due to both ego- and object-motion. It therefore makes no sense to maintain such information in memory for long periods. Emphasis is instead given to rapid updating of information (Goodale, Jakobson, & Keillor, 1994; Milner & Goodale, 1995). Consistent with this, Bradshaw and Watt (2002) explicitly compared perception and action responses in reproducing remembered locations and found the accuracy of their perceptual response measure to be invariant with delays of up to 4 s whereas the accuracy of their action response declined significantly after just 2 s. The present finding that, in middle childhood, reach parameters are disrupted after only 2 s delay lends further support to the notion that visuo-motor representations operate over a limited time period. Interestingly, single cells in the dorsal pathway have been identified which may be the correlate of the memory for action. Hand manipulation-
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related neurons in the anterior intraparietal sulcus of monkey parietal cortex have been found which are selective for the 3-D shape, and size of objects, suggesting they may represent information for the control of grasping (Sakata & Taira, 1994; Sakata et al., 1992). Many of these have also been found to show sustained activity during the 2 s period following stimulus presentation (Murata, Gallase, Kaseda, & Sakata, 1996). The representation of intrinsic and extrinsic information about objects may help our prehension performance to remain robust and efficient. However, from Milner and GoodaleÕs theoretical viewpoint, it appears reasonable that such memorial representations should persist for only a limited duration. Such a representation appears to be present in some form as early as age 6 months (see Clifton, Rochat, Litovsky, & Perris, 1991) and, on the basis of the present results, seems to be well developed by the age of 5 years. A size–distance scaling explanation is often employed to account for the results of experiments involving changes in reach kinematics such as those reported here (e.g., Servos, Goodale, & Jakobson, 1992). Such an explanation seems unlikely to hold for our data, however. Objects misperceived as nearer (i.e., leading to lower peak velocities) should, according to size–distance scaling, also appear smaller (i.e., leading to smaller peak grip apertures) but we found ‘‘undershoots’’ in the reach were accompanied by larger grip apertures. When the extended time in the slow phase is considered along with peak velocity and peak grip aperture the data seem more consistent with children adopting a Ôconservative strategyÕ under conditions of increasing uncertainty. Reaching less far, opening the grasp wider and approaching the object more slowly provides a larger margin of safety in order to avoid collision with the target object (see also Smyth et al., 2004). Similar changes in performance have been observed in adult subjects when they are required to make speeded reaching responses or when normal closed-loop reaches are compared with conditions in which visual information is impoverished (Jackson, Jones, Newport, & Pritchard, 1997; Jakobson & Goodale, 1991; Watt & Bradshaw, 2000; Wing, Turton, & Fraser, 1986). Precise details of childrenÕs movements during the slow phase (for example, fumbling versus colliding with the objects) could not be determined on the basis of only the kinematic data from the three markers. It remains possible, therefore, that there were subtle differences between the reaches made in each age group that could not be detected. Nonetheless, it is interesting that children as young as 5 years old generally appear to adopt an adaptive ‘‘strategy’’ of slowing down the hand and opening the grasp wider, in order to deal with reduced certainty about object properties. It should be emphasised that such a strategy need not be invoked consciously (and therefore would not need to be learned explicitly), but could be an automatic result of increasing variability in perceptual estimates of object properties, here introduced by the delay which interferes with the representation of intrinsic and extrinsic object information. This outcome may be captured by a slight extension to Harris and WolpertÕs (1998) model of movement control, for example. Their model operates to constrain the end-point variance of eye or arm movements in the presence of signal-dependent ÔneuronalÕ noise in the motor system. If we consider the addition of Ôperceptual noiseÕ as a consequence of delay, then the visuo-motor control system would have to
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further reduce the signal in order to keep end-point variability approximately constant. This would lead to lower peak velocities and, consequently, more time in the slow phase and widening of the grip aperture. Overall, from the data presented here, it appears that the effects of delay on childrenÕs prehensile movements are similar to, although more pronounced than, those observed previously in adults using a similar task and temporal delay (Bradshaw & Watt, 2002; Hu et al., 1999). This suggests that the short duration representations underlying visuo-motor control are developed by the age of 5 years but remain particularly labile in terms of grip aperture formation in middle and older age groups. The short retention interval has been particularly associated with the visuo-motor, or action, system and the observed decline in performance after 2 s may reflect a critical temporal constraint for prehension. Acknowledgements This work was supported by the Wellcome Trust. Thanks to Rob McIntosh for useful discussions concerning this work, and to Terry Thacker for technical assistance. References Bard, C., Hay, L., & Fleury, M. (1990). Timing and accuracy of visually directed movements in children: Control of direction and amplitude components. Journal of Experimental Child Psychology, 50, 102–118. Berthier, N. E., Clifton, R. K., Gullapalli, V., McCall, D. D., & Robin, D. (1996). Visual information and object size in the control of reaching. Journal of Motor Behavior, 28, 187–197. Bradshaw, M. F., & Graham, J. K. (1998). Visual and motor reproduction of remembered locations: The effect of temporal delay. Investigative Ophthalmology and Visual Science, 39, S622. Bradshaw, M. F., & Watt, S. J. (2002). A dissociation of perception and action in normal human observers: The effect of temporal delay. Neuropsychologia, 40, 1766–1778. Churchill, A., Hopkins, B., Ro¨nnqvist, L., & Vogt, S. (2000). Vision of the hand and environmental context in human prehension. Experimental Brain Research, 134, 81–89. Clifton, R. K., Muir, D. W., Ashmead, D. H., & Clarkson, M. G. (1993). Is visually guided reaching in early infancy a myth? Child Development, 64, 1099–1110. Clifton, R. K., Rochat, P., Litovsky, R. Y., & Perris, E. E. (1991). Object representation guides infantsÕ reaching in the dark. Journal of Experimental Psychology: Human Perception and Performance, 17, 323–329. Connolly, J. D., & Goodale, M. A. (1999). The role of visual feedback of hand position in the control of manual prehension. Experimental Brain Research, 125, 281–286. Elliott, D., & Madalena, J. (1987). The influence of pre-movement visual information on manual aiming. The Quarterly Journal of Experimental Psychology, 39A, 541–559. Fogassi, L., Gallese, V., Buccino, G., Craighero, L., Fadiga, L., & Rizzolatti, G. (2001). Cortical mechanism for the visual guidance of hand grasping movements in the monkey – A reversible inactivation study. Brain, 124, 571–586. Gallese, V., Murata, A., Kaseda, M., Niki, N., & Sakata, H. (1994). Deficit of hand preshaping after muscimol injection in monkey parietal cortex. Neuroreport, 5, 1525–1529. Gentilucci, M., Fogassi, L., Luppino, G., Matelli, M., Camarda, R., & Rizzolatti, G. (1988). Functional organization of inferior area 6 in the macaque monkey. 1: Somatotopy and the control of proximal movements. Experimental Brain Research, 71, 475–490.
M.F. Bradshaw et al. / Human Movement Science 23 (2004) 771–784
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Gentilucci, M., & Rizzolatti, G. (1990). Cortical motor control of arm and hand movements. In M. A. Goodale (Ed.), Vision and Action: The Control of Grasping. Norwood: Ablex. Gentilucci, M., Toni, I., Chieffi, S., & Pavesi, G. (1994). The role of proprioception in the control of prehension movements: A kinematic study in a peripherally deafferented patient and in normal subjects. Experimental Brain Research, 99, 483–500. Goodale, M. A., Jakobson, L. S., & Keillor, J. M. (1994). Differences in the visual control of pantomimed and natural grasping movements. Neuropsychologia, 32, 1159–1178. Goodale, M. A., Pe´llison, D., & Prablanc, C. (1986). Large adjustments in visually guided reaching do not depend on vision of the hand or perception of target displacement. Nature, 320, 748–750. Graham, J., Bradshaw, M. F., & Davis, A. (1998). The effect of pre-movement delays on pointing accuracy in middle childhood. Perception, 27, 1379–1389. Harris, C. M., & Wolpert, D. M. (1998). Signal-dependent noise determines motor planning. Nature, 394, 780–784. Hay, L., Bard, C., Fleury, M., & Teasdale, N. (1991). Kinematics of aiming in direction and amplitude: A developmental study. Acta Psychologica, 77, 203–215. Heath, M., Westwood, D. A., & Binsted, G. (2004). The control of memory-guided reaching movements in peripersonal space. Motor Control, 8, 76–106. Hu, Y., Eagleson, R., & Goodale, M. A. (1999). The effects of delay on the kinematics of grasping. Experimental Brain Research, 126, 109–116. Jackson, S. R., Jones, C. A., Newport, R., & Pritchard, C. (1997). A kinematic analysis of goal directed prehension movements executed under binocular, monocular, and memory-guided viewing conditions. Visual Cognition, 4, 113–142. Jakobson, L. S., & Goodale, M. A. (1991). Factors affecting higher-order movement planning: A kinematic analysis of human prehension. Experimental Brain Research, 86, 199–208. Jeannerod, M. (1984). The timing of natural prehension movements. Journal of Motor Behaviour, 16, 235–254. Jeannerod, M. (1988). The neural and behavioural organization of goal-directed movements. Oxford: Clarendon Press. Konczak, J., & Dichgans, J. (1997). The development towards stereotypic arm kinematics during reaching in the first 3 years of life. Experimental Brain Research, 117, 346–354. Kuhtz-Buschbeck, J. P., Stolze, H., Boczek-Funcke, A., Johnk, K., Heinrichs, H., & Illert, M. (1998). Kinematic analysis of prehension movements in children. Behavioural Brain Research, 93, 131–141. Kuhtz-Buschbeck, J. P., Stolze, H., Johnk, K., Boczek-Funcke, A., & Illert, M. (1998). Development of prehension movements in movements in children: A kinematic study. Experimental Brain Research, 122, 424–432. McCarty, M. E., Clifton, R. K., Ashmead, D. H., Lee, P., & Goubet, N. (2001). How infants use vision for grasping objects. Child Development, 72, 973–987. Milner, A. D., & Goodale, M. A. (1995). The visual brain in action. Oxford: Oxford University Press. Murata, A., Gallese, V., Kaseda, M., & Sakata, H. (1996). Parietal neurons related to memory-guided hand manipulation. Journal of Neurophysiology, 75, 2180–2186. Oppenheim, A. V., & Schafer, R. W. (1989). Discrete-time signal processing. Englewood Cliffs: Prentice Hall. Paillard, J. (1982). The contribution of peripheral and central vision to visually guided reaching. In D. J. Ingle, M. A. Goodele, & R. J. W. Mansfield (Eds.), Analysis of visual behavior. Cambridge: MIT Press. Pellizzer, G., & Hauert, C. A. (1996). Visuo-manual aiming movements in 6- to 10-year-old children: Evidence for an asymmetric and asynchronous development of information processes. Brain and Cognition, 30, 175–193. Piaget, J. (1952). The Origins of Intelligence in Children. New York: Norton. Pryde, K. M., Roy, E. A., & Campbell, K. (1998). Prehension in children and adults: The effects of object size. Human Movement Science, 17, 743–752. Sakata, H., & Taira, M. (1994). Parietal control of hand action. Current Opinion in Neurobiology, 4, 847–856.
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M.F. Bradshaw et al. / Human Movement Science 23 (2004) 771–784
Sakata, H., Taira, M., Mine, S., & Murata, A. (1992). Hand-movement-related neurons of the posterior parietal cortex of the monkey: Their role in the visual guidance of hand movements. In R. Caminiti, P. B. Johnson, & Y. Burnod (Eds.), Control of Arm Movement in Space. Berlin: Springer. Saunders, J. A., & Knill, D. C. (2003). Humans use continuous visual feedback from the hand to control fast reaching movements. Experimental Brain Research, 152, 341–352. Servos, P., Goodale, M. A., & Jakobson, L. S. (1992). The role of binocular vision in prehension: A kinematic analysis. Vision Research, 32, 1513–1521. Smyth, M. M., Katamba, J., & Peacock, K. A. (2004). Development of prehension between 5 and 10 years of age: Distance scaling, grip aperture, and sight of the hand. Journal of Motor Behavior, 36, 91–103. Thomson, J. A. (1983). Is continuous visual monitoring necessary in visually guided locomotion? Journal of Experimental Psychology: Human Perception and Performance, 9, 427–443. von Hofsten, C., & Ro¨sblad, B. (1988). The integration of sensory information in the development of precise manual pointing. Neuropsychologia, 26. Watt, S. J., & Bradshaw, M. F. (2000). Binocular cues control the grasp but not the reach in natural prehension movements. Neuropsychologia, 38, 1473–1481. Watt, S. J., Bradshaw, M. F., Clarke, T. J., & Elliott, K. M. (2003). Binocular vision and prehension in middle childhood. Neuropsychologia, 41, 415–420. Westwood, D. A., Heath, M., & Roy, E. A. (2003). No evidence for accurate visuomotor memory: Systematic and variable error in memory-guided reaching. Journal of Motor Behavior, 35, 127–133. Wing, A. M., Turton, A., & Fraser, C. (1986). Grasp size and accuracy of approach in reaching. Journal of Motor Behavior, 18, 245–260. Winges, S. A., Weber, D. J., & Santello, M. (2003). The role of vision on hand preshaping during reach to grasp. Experimental Brain Research, 152, 489–498.