Different visuomotor processes maturation rates in children support dual visuomotor learning systems

Human Movement Science 46 (2016) 221–228

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Human Movement Science journal homepage: www.elsevier.com/locate/humov

Different visuomotor processes maturation rates in children support dual visuomotor learning systems Rosinna Gómez-Moya a, Rosalinda Díaz b, Juan Fernandez-Ruiz b,⇑ a b

Doctorado en Neuroetologia, Universidad Veracruzana, Xalapa, Veracruz, Mexico Laboratorio de Neuropsicología, Departamento de Fisiología, Facultad de Medicina, Universidad Nacional Autónoma de México, Distrito Federal, Mexico

a r t i c l e

i n f o

Article history: Received 15 May 2015 Revised 11 January 2016 Accepted 12 January 2016

Keywords: Motor development Sensorimotor learning Sensorimotor adaptation Prism adaptation Strategic-based learning Procedural learning

a b s t r a c t Different processes are involved during visuomotor learning, including an error-based procedural and a strategy based cognitive mechanism. Our objective was to analyze if the changes in the adaptation or the aftereffect components of visuomotor learning measured across development, reflected different maturation rates of the aforementioned mechanisms. Ninety-five healthy children aged 4–12 years and a group of young adults participated in a wedge prism and a dove prism throwing task, which laterally displace or horizontally reverse the visual field respectively. The results show that despite the agerelated differences in motor control, all children groups adapted in the error-based wedge prisms condition. However, when removing the prism, small children showed a slower aftereffects extinction rate. On the strategy-based visual reversing task only the older children group reached adult-like levels. These results are consistent with the idea of different mechanisms with asynchronous maturation rates participating during visuomotor learning. Ó 2016 Elsevier B.V. All rights reserved.

1. Introduction Visuomotor learning, the capacity to improve visually guided movements, is a fundamental ability that can be found from infancy on (McDonnell & Abraham, 1979, 1981). A number of conditions affecting the motor system have been analyzed to understand its underlying mechanisms. For example, it has been shown that specific cerebellar lesions result in a profound visuomotor learning disruption in a number of tasks including adaptation to wedge prisms, force perturbations and visuomotor rotations (Block & Bastian, 2012; Fernandez-Ruiz et al., 2007; Martin, Keating, Goodkin, Bastian, & Thach, 1996; Smith & Shadmehr, 2005; Vaca-Palomares et al., 2013; Velazquez-Perez et al., 2009; Weiner, Hallett, & Funkenstein, 1983). In contrast, basal ganglia degeneration does not affect visuomotor learning in those tasks despite having a profound impact on motor behavior (Fernandez-Ruiz et al., 2003; Gutierrez-Garralda et al., 2013; Smith & Shadmehr, 2005). The effect of aging on visuomotor learning has yielded more variable results, with some studies reporting no changes, while others show significant effects (Bock & Schneider, 2002; Fernandez-Ruiz, Hall, Vergara, & Diiaz, 2000; Roller, Cohen, Kimball, & Bloomberg, 2002). This variation has been explained by the differential effect that aging could have in different processes participating during visuomotor learning (Anguera, Reuter-Lorenz, Willingham, & Seidler, 2011; Baugh & Marotta, 2009; Cressman,

⇑ Corresponding author at: Departamento de Fisiología, Facultad de Medicina, Universidad Nacional Autónoma de México, Coyoacán, Distrito Federal C.P. 04510, Mexico. E-mail address: [email protected] (J. Fernandez-Ruiz). http://dx.doi.org/10.1016/j.humov.2016.01.011 0167-9457/Ó 2016 Elsevier B.V. All rights reserved.

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Salomonczyk, & Henriques, 2010; Fernandez-Ruiz et al., 2003; Hegele & Heuer, 2010, 2013; Langan & Seidler, 2011; Lawrence-Dewar, Baugh, & Marotta, 2012). Recent studies designed to explore the processes involved in visuomotor learning suggest that it could be the result of the interaction of at least two mechanisms with unique properties (Shadmehr, Smith, & Krakauer, 2010; Taylor, Krakauer, & Ivry, 2014; Wolpert, Diedrichsen, & Flanagan, 2011). The first one is an explicit strategic system that shows fast learning, requires long reaction times, and is unstable and vulnerable to interruptions (Fernandez-Ruiz, Wong, Armstrong, & Flanagan, 2011; Huberdeau, Krakauer, & Haith, 2015; Lillicrap et al., 2013; Michel, Pisella, Prablanc, Rode, & Rossetti, 2007). The second one is an implicit slow learning procedural mechanism that requires low reaction times and is error-driven (Fernandez-Ruiz & Diaz, 1999; Michel et al., 2007). It has been postulated that the simultaneous expression of these mechanisms result in the characteristic visuomotor learning time-course pattern observed after the introduction of a perturbation. It consists of substantial error reduction in the initial trials, a phase sometimes denominated the initial fast learning phase, followed by decreasingly small reductions in error called the slow learning phase (Fernandez-Ruiz et al., 2011; Huberdeau et al., 2015; Shadmehr et al., 2010). The interaction of these processes also results in differential aftereffects observed after the perturbation withdrawal. The first mechanism has been related to null or smaller aftereffects that tend to decrease rapidly, while the second mechanism has been related to more robust long-lasting aftereffects (Fernandez-Ruiz & Diaz, 1999; Fernandez-Ruiz, Diaz, Aguilar, & Hall-Haro, 2004; Michel et al., 2007). Developmental studies have shown that different abilities fully develop at different postnatal ages (Liu, Luo, Mayer-Kress, & Newell, 2012; Luna, Garver, Urban, Lazar, & Sweeney, 2004; Luna et al., 2001). For example, it has been shown that gross motor skills are in place before the first two years of age, while processing speed, response inhibition, and working memory reach mature adult-level performance at late adolescence (WHO Multicentre Growth Reference Study Group, 2006; Luciana & Nelson, 1998; Luna et al., 2004). Then, it could be possible that the maturation asynchrony of different processes involved in visuomotor learning, like working memory or procedural processes, could result in different behavioral patterns evident during the performance of a learning task (Luna et al., 2004; Meulemans, Van der Linden, & Perruchet, 1998). To test this hypothesis, here we set to evaluate if there are different visuomotor learning and forgetting rates across development. For this purpose we tested four groups of children from the ages of 4–12 years old, and a group of young adults, in two visuomotor tasks known to differentially exploit the strategic control and the procedural mechanisms, i.e. adaptation to reversing dove prisms and adaptation to wedge prisms (Fernandez-Ruiz & Diaz, 1999; Lawrence-Dewar et al., 2012; Lillicrap et al., 2013). 2. Method 2.1. Participants 95 children (46 girls and 49 boys) right-handed, with an age range of 4–12 years from public schools in Mexico City were divided into four groups. Group 1 included 25 children aged 4 and 5 years who attend preschool. Group 2 included 25 children aged 6 and 7 year olds in first and second grade. Group 3 included 25 children aged 8 and 9 years who attend third and fourth grade. Group 4 included 20 children 11 and 12 years old who attend fifth and sixth grade and a group of 20 right-handed adults of 20– 28 years. The participants’ selection was conducted with a non-probability method using convenience sampling. Parents or tutors signed a letter of informed consent approved by the Ethics Committee of the Faculty of Medicine, UNAM, according to the Declaration of Helsinki and later revisions (World Medical Association, 2001). 2.2. Apparatus and procedure Parents were asked to fill out a questionnaire to rule out neurological or psychiatric diagnosis. Our inclusion criteria were an average intellectual performance in the Wechsler Intelligence Scale for preschool and primary-III levels and Wechsler Intelligence for Children-WISC-IV Scale. All children were screened with the Movement Assessment Battery for Children (MABC) (Henderson & Sugden, 2007); a score at or above the 20th percentile was necessary for inclusion. 2.3. General design of experiments The experimental procedure comprised two experiments with a different prism lens each; one used an 18-diopter displacing wedge prism and the other one used a reversing dove prism. Each experiment followed the following three phases (Fernandez-Ruiz & Diaz, 1999): First: A baseline throwing performance was obtained by having the participants throw 26 balls (weight: 10 g) to the target before the prisms were mounted on the window (condition PRE). The position at which the balls made an impact on or around the target was marked immediately after each throw. Second: After donning the prisms (condition PRI), the subjects were instructed to throw 26 more balls with the same arm and in the same way. For the displacement PRI condition participants saw through 18 diopter wedge prisms that produce a deviation of light to the right. For the reversing PRI condition participants saw through right-left reversing prisms (dove

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prisms) that horizontally flip the visual image around the mid-line. The PRI condition belongs to the visual-motor adaptation capacity. Third: During condition POS, the prisms were removed before continuing throwing 26 more balls with the same arm and in the same way as before. The POS condition, called aftereffect, belongs to the movements persistence once removed the prisms, being this a visual-motor learning measurement. The critical feedback difference between the 18-diopter displacing wedge prism and the reversing prism is as follows: Both prisms led to a 30 cm rightward optical displacement, and to overcome that error in both conditions participants have to make 30 cm leftward corrections. However, while the sign direction of the visual error feedback in the wedge prism is congruent with the real sign direction of the correction, the sign correction of the error feedback in the dove prism is reversed. Therefore, to hit the target during the displacement the participants need to throw where their visual feedback is informing them. By contrast, to hit the target during the reversal of the visual field, the participants would still need to throw to the left, which is incongruent to what their reversed visual feedback is informing them (Lillicrap et al., 2013). To adapt to this displacement, the system could use a procedural error-based learning mechanism that does not require the implementation of a cognitive strategy (Fernandez-Ruiz & Diaz, 1999; Michel et al., 2007; Redding & Wallace, 2002). On the other hand, when the visual field is reversed, the feedback is incongruent with the corrective update (Abdelghani, Lillicrap, & Tweed, 2008; Lillicrap et al., 2013). This perturbation flips the visual field from left to right about the midline. In this case the participants must reduce their errors by correcting also in the leftward direction, but since the visual feedback is also reversed, the error feedback is incongruent, which would mistakenly suggest a rightward correction. To adapt to this perturbation participants implement strategic processes (Abdelghani et al., 2008; Gutierrez-Garralda et al., 2013; Lillicrap et al., 2013; Taylor & Ivry, 2012; Vaca-Palomares et al., 2013). 2.4. Data analyzes The location of the impacts was plotted sequentially by trial number (abscissa) versus horizontal displacement (in centimeters) from a vertical line passing through the target center (ordinate). Impacts to the left of the target were plotted as negative values and impacts to the right were plotted as positive values. A number of measures were obtained. The variable error was calculated for each group from the baseline (PRE condition) p P  2 =NÞ. The adaptation magnitude was obtained from the PRI conditions by subthrows using the formula VE ¼ ð ðX i  XÞ tracting the horizontal displacement to the target on the final throw (throw 26) from that on the initial throw. The aftereffect measure was defined as the horizontal distance to the target of the first throw after removing the prism. To analyze the variable error during the baseline throws across age, a one-way ANOVA test for independent samples was done. To compare the adaptation and aftereffect measures between groups, a one-way ANOVA followed by a post hoc Tukey test was performed. The number of subjects adapting to the prisms was calculated using the following criteria: If the error magnitude of the average of the last three throws of condition PRI (PRI-26) was less than the error magnitude of the first throw of the PRI condition (PRI-1) minus the standard deviation of the baseline the participant was considered as an ‘‘adapter”, otherwise the participant was considered as a ‘‘non-adapter” (Lillicrap et al., 2013; Vaca-Palomares et al., 2013). To analyze the proportion of participants adapting to the prisms, the Z-ratio for the significance of the difference between two independent proportions was calculated (Vaca-Palomares et al., 2013). To analyze the adaptation rate across trials between groups a linear mixed model using the maximum likelihood method on the first 10 trials during the PRI condition was performed. This model is adequate to analyze repeated measures obtained from each individual, since random intercepts and random slopes can be assumed in the analysis (Field, 2009). 3. Results 3.1. Visuomotor performance The Fig. 1 shows the significative differences between F(4,110) = 7.248, p = 0.00 groups in the variable error. Tukey’s post hoc analysis indicated that children aged 11 and 12 years old were significant better than children ages 4 and 5 (p < 0.01). No other differences were found between the children groups. A Pearson product-moment correlation coefficient was computed to further analyze the visuomotor performance across age. The results show a negative correlation between the variable error or the consistency in the throwing which decreases with age, in this case the older, the less variable error, r = .774, n = 95, p < .01, with a variable error reduction of 1.01 cm per month across this age range. 3.2. Wedge prisms experiment The panel A of Fig. 2 shows the performance curve of the 26 adaptation shots in each group, suggesting that by the end of the 26 shots all groups reached the same adaptation level. The panel A of Fig. 3 shows the adaptation size without significative differences between groups (F(4,110) = 0.245, p = 0.912).

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Fig. 1. Variable error (cm) per child (gray circles) across age (in months). The line shows the linear regression.

Fig. 2. (A) Time course of the errors during the adaptation phase by group. (B) Linear mixed model results of the first ten adaptation trials (for details see the methods section).

Significative effects regard age were found in the adaptation rate (F(1,144.2) = 5.87, p = .017) and throwing (F(1,1033) = 48.6, p < .001), but did not show significant interactions between age and trial (F(1,1032) = 1.06, p = .303), (see Fig. 2B). The panel B of Fig. 3 showed no significant differences in the first aftereffect trial (F(4,110) = 0.633, p = 0.640) between groups. The panel A of Fig. 4 shows the performance curve of the 26 shots on the aftereffect condition or the throwing once the prisms is removed. The linear mixed model analysis on the aftereffect forgetting rate showed significant trial effects (F(1,112.7) = 8.9, p = .004), but did not show age effects (F(1,115) = 3.2, p = .07), however, the analysis did show a significant interactions between trial and age (F(1,114.5) = 4.12, p = .044). The parameter estimates of this interaction show a significant prediction of the aftereffects forgetting speed (b = .047, t(114.56) = 2.03, p = .044), (Fig. 4B). 3.3. Reversing prism experiment The adaptation magnitude across groups did not result in significant differences between groups (F(4,110) = 0.245, p = 0.912) due to the large variance in the children groups. Previous studies have shown that a proportion of subjects do not adapted within the 26 trials of the adaptation phase (Lillicrap et al., 2013). Fig. 5 shows the proportion of subjects that adapted within each children group in relation to the adult group using the zratio for the significance of the difference between two independent proportions. The analyzes showed significant differences between the children group of 11–12 years old and the children group of 4–5 years (Z = 2.75, p = 0.006), the group 6–7 years (Z = 3.064, p = 0.0022), but not with the group of 8–9 years (Z = 1.878, p = 0.0604) and adult group (Z = 0.663, p = 0.5073). No other differences were found within the children groups.

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Fig. 3. Visuomotor learning in the displacing condition, (A) Adaptation magnitude in each group. (B) Aftereffect magnitude in each group. There were no statistical differences between groups. Bars represent standard errors of the means.

Fig. 4. (A) Time course of the errors during the aftereffect phase by group. (B) Linear mixed model results of the first ten aftereffect trials showing a significant interaction between trial and age, where younger subjects are slower than older ones.

As expected, the analysis of the aftereffects phase in the reversing prism experiment showed no differences between any of the groups. 4. Discussion Here we tested if children ages 4–12 years showed age-dependent visuomotor learning and forgetting rates variations. Our results show that despite expressing significant age-related performance differences in motor control, all the children groups fully adapted to the perturbation introduced by wedge prisms at the same rate as the young adults. This was not the case, however, once the wedge prism perturbation was withdrawn. Significant age-dependent differences emerged during the extinction of the aftereffect, with younger children showing slower forgetting rates than older ones. The results from the reversing prism task, which favors the implementation of strategies, showed that only a small percentage of the younger children reduced the error. In contrast, the oldest group almost reached the same percentage of successful individuals as the adult group. In the following discussion we argue that combined results from both prisms tasks could be explained by the asynchronous maturation rate of different visuomotor learning mechanisms.

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Fig. 5. Percent of subjects that could adapt during the prism reversing task. Z-ratio shows significant differences between older children and adults with the young children.

4.1. Motor control development The results show an increased accuracy in the motor control performance across age, as has been reported before (Yan, Thomas, Stelmach, & Thomas, 2000). Together with the lack of adaptation differences among the children groups, these results support the idea that different mechanisms are involved in visuomotor control and visuomotor learning. This hypothesis has been suggested by a number of studies on different patient populations that, despite having motor control deficits, show normal visuomotor learning rates (Fernandez-Ruiz et al., 2003; Gutierrez-Garralda et al., 2013; Vaca-Palomares et al., 2013). 4.2. Visuomotor learning and forgetting The results showed no significant group differences in the adaptation magnitude or adaptation rates. Although possible adaptation rates differences could have been obscured by the large throwing variability shown especially by the younger groups, these results support that visuomotor learning capabilities are implemented early in life, as has been shown by previous prism adaptation studies with infants (McDonnell & Abraham, 1979, 1981). The aftereffect did not show significant difference either, however, the analysis of the aftereffect extinction showed significant age-dependent differences, with younger children showing slower forgetting. This adaptation/aftereffect change rate difference could be seen as paradoxical if the extinction of the aftereffect is simply viewed as a re-adaptation. However, recent findings support the notion that adaptation and aftereffect could be the result of different mechanisms (Galea, Vazquez, Pasricha, de Xivry, & Celnik, 2011; Hadipour-Niktarash, Lee, Desmond, & Shadmehr, 2007). In one study it was shown that the disruption of primary motor cortex during a visuomotor rotation task results in a faster forgetting during the de-adaptation period, despite having the same adaptation rate (Hadipour-Niktarash et al., 2007). The authors suggested that the disrupted process in the primary motor cortex may represent a slow motor memory component which plays a significant role in retention, but not during adaptation (Hadipour-Niktarash et al., 2007). These results could be instantiating the different forgetting rates for the procedural and strategic processes participating during a visuomotor learning task that have been demonstrated with different approaches. In one of the initial studies showing the time decay difference between the two systems it was shown, using a wedge prism adaptation task, that most of the fast decay occurs within one minute after ending the adaptation phase (Fernandez-Ruiz et al., 2004), a finding later replicated using a visuomotor rotation task (Hadjiosif & Smith, 2013). The reversing prism results also point towards an asynchronous maturation rate of two systems involved in visuomotor learning. Our results show that the percentage of kids adapting to the reversing prisms only reached adult levels in the older group, suggesting that younger kids do not have the cognitive abilities needed to master the reversing prism. Similar conclusions have been reached with the antisaccade task, which is similar to the reversing prism, with the exception that in the reversing prism no rule is explicitly given, so the subjects have to develop an internal strategy to solve it (Lillicrap et al., 2013; Luna et al., 2001). Finally, it should be mentioned that it could be possible that different mechanisms other than those proposed here are involved in the larger aftereffect persistence observed in the younger children. Recent studies include the proposal of an

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ultraslow visuomotor learning mechanism and the participation of reinforcement mechanisms modulating the persistence of novel visuomotor representations (Galea, Mallia, Rothwell, & Diedrichsen, 2015; Inoue et al., 2015). Further experiments aimed at exploring the participation of those mechanisms are granted. 5. Conclusions Our study shows that there are significant visuomotor changes across childhood development. The behavioral patterns observed across development fit with the behavioral expression of at least two systems with asynchronous maturation rates. Early in development a fully functional slow procedural visuomotor learning mechanism combined with an incipient strategic system would result in slower forgetting rates. Later on, as the cognitive strategic system keeps on maturing, the forgetting rates would become faster, approaching adult levels. Competing interest statements The authors on this manuscript do not have any conflicts of interest. Acknowledgments This study was supported in part by: Universidad Nacional Autonoma de Mexico (PAPIIT IN214716) and Consejo Nacional de Ciencia y Tecnologia (220871) grants to Juan Fernandez Ruiz, as well as a CONACYT scholarship for graduate studies #176431 to Rosinna Gómez-Moya. References Abdelghani, M. N., Lillicrap, T. P., & Tweed, D. B. (2008). Sensitivity derivatives for flexible sensorimotor learning. Neural Computation, 20, 2085–2111. Anguera, J. A., Reuter-Lorenz, P. A., Willingham, D. T., & Seidler, R. D. (2011). Failure to engage spatial working memory contributes to age-related declines in visuomotor learning. Journal of Cognitive Neuroscience, 23, 11–25. Baugh, L. A., & Marotta, J. J. (2009). When what’s left is right: Visuomotor transformations in an aged population. PLoS ONE, 4, e5484. Block, H. J., & Bastian, A. J. (2012). Cerebellar involvement in motor but not sensory adaptation. Neuropsychologia, 50, 1766–1775. Bock, O., & Schneider, S. (2002). 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