A new perspective on the development of motor variability during middle childhood Golenia, Laura
IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below.
Document Version
Publisher's PDF, also known as Version of record
Publication date:
2018
Link to publication in University of Groningen/UMCG research database
Citation for published version (APA):
Golenia, L. (2018). A new perspective on the development of motor variability during middle childhood.
Rijksuniversiteit Groningen.
Copyright
Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons).
Take-down policy
If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.
Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons the number of authors shown on this cover page is limited to 10 maximum.
CHAPTER 6
General discussion
CHAPTER 6
Main experimental findings
Variability is an important characteristic of motor development [1–3], which has, unfortunately, received limited attention in the developmental period of middle childhood (5-10 years of age).
This thesis aimed to increase the understanding about developmental changes in motor variability during middle childhood by examining the structure of variability in joint angles over repetitions of trials in goal-directed reaching movements in typically and atypically developing children (children with Developmental Coordination Disorder, DCD). Joint angle variability in reaching movements was structured in terms of its effect on task performance using the Uncontrolled Manifold (UCM) method [4,5]. The UCM method partitions variability into joint angles in variability that does not affect the position of the index finger (Vucm) and into variability that does affect the position of the index finger (Vort) [6–8].
Results revealed that performance variability (characterized in terms of variable and constant error) and variability at the joint angle level (characterized in terms of Vucm and Vort) decreased with age (Chapter 2 and 3). But, importantly, the developmental trends found at the performance level differed from the trends found at the joint angle level. This indicates that different processes may play a role at different levels of the system, which require explanation. Results also revealed that the developmental trends of Vucm and Vort changed in relation with different constraints (organismic, environmental and task constraints). Availability of visual information of the arm did not affect the developmental trends of Vucm and Vort (Chapter 2), whereas increased task demands (uncer- tainty about the target location) changed the developmental trend of Vucm (Chapter 3). When task demands increased, 5 to 8-year-old children showed no changes in Vucm, whereas 9 and 10-year-old children and adults had higher values of Vucm, indicating that the ability to tailor Vucm to changing task constraints develops. In addition, results showed that children with DCD had higher values of Vucm compared to aged-match controls, whereas Vort was similar between groups (Chapter 4).
This demonstrates that variability might play a different role in DCD than assumed until now.
Together the results of Chapter 2,3, and 4 support the idea that motor variability has multiple developmental trajectories that emerge depending on the interaction between organismic, envi- ronmental, and task constraints.
Main conceptual contributions
This thesis also elaborated on how ideas of the Dynamic Systems (DS) theory can positively con- tribute to the understanding of developmental changes. As described in Chapter 1, 2, and 5, most earlier studies focusing on reaching in middle childhood (both in the TD and DCD literature) fol- lowed the computational neuroscience approach [9–13]. In Chapter 5, this thesis referred to the used theoretical approaches as ‘single-cause approaches’, because emphasis laid on single processes
or single components supposable causing the developmental changes seen in reaching perfor- mance. In contrast with these ‘single-cause approaches’, the DS theory argues to concentrate on all components of the system, including the environment and the task, because motor behavior and changes in motor behavior emerge from various contributing components [14–16]. Chapter 2 showed that in a reaching task it is important to describe and understand the developmental changes occurring at the joint angle level (in line with [17,18]). Thus, this thesis underlines the proposal of the DS theory that all levels and components of the systems should be examined so that a level-overarching explanation of development is achieved. The DS theory also emphasizes that at each point in time different components may act as rate-limiting constraint in the interac- tion of all components. For instance, it has been shown that infant´s postural capabilities act as a rate-limiting constraint on the emergence of reaching behavior [19–21]. In Chapter 5, this thesis proposed that in reaching experiments conducted with children aged 5 to 10-years of age different experimental constraints might act as rate-limiting constraints, which might explain the different developmental trends found across different previous studies [9,22–24]. Several authors have used this general line of argumentation of the DS theory before [14,25], but this thesis is one of the first to apply it in detail to the development of reaching in middle childhood.
The opportune aspect of the DS theory is that it´s principles of change are of general-purpose and can be applied to all aspects and timescales of a situation. In Chapter 5, this thesis proposed that if one wants to understand development in terms of attractors [e.g., 26,27], then also the task itself has to be described and understood in terms of attractors. There are a few models that have described the task of reaching in dynamic terms [28–31], but this description has not been coupled with the description of developmental changes. This coupling should be modeled and examined in future studies. Thus, this thesis makes a plea for using the general principles of change of the DS theory in all aspects of the observed situation when studying developmen- tal changes. This should result in a unified language of explanation and eventually in a better understanding of developmental processes in the field of reaching, but also in all other fields of development.
Not all variability in development should have a negative connotation
In the developmental period of middle childhood, variability in reaching movements in TD children [9,32–34] and in children with DCD [35–37] was mostly studied at the performance level. That is, variability was quantified by means of the amount of performance variability about a mean, such as the amount of errors around a target. Variability measured in this particular way is con- sidered to reflect inconsistency, which resulted in a negative connotation on variability in middle childhood development and in children with DCD. This thesis approached motor variability in a
CHAPTER 6 novel way: The structure in joint angle variability over repetitions of reaching movements was
examined by means of Vucm and Vort. Considering the findings of earlier studies about variability in middle childhood development, the following question arises: Are developmental changes in variability at the joint angle level a reflection of changes in consistency/inconsistency or is there more to it? Vort affects performance and can therefore be seen as a reflection of inconsistency when interpreted in a similar way as earlier studies have interpreted variability at the performance level.
Vucm does not affect performance and can therefore be seen as something more than inconsistency.
Based on the following two arguments it is proposed that the results of the experimental studies of this thesis show that variability in joint angles in the larger part reflects something more than inconsistency in performance.
First, although most types of variability showed a decrease with age, the developmental trends found for errors at the performance level (reflecting inconsistency) were different to the devel- opmental trends found at the joint angle level (Chapter 2 and 3). In addition, Chapter 2 revealed that the trends for Vucm and Vort were also different. These results indicate that rather than a similar reduction of all types of variability, which would be expected when all motor variability reflects inconsistency, certain types of variability are reduced at certain ages. Also in infant studies it has been shown that variability can have different developmental trends (see for an overview Adolph et al. [1]). Thus, it seems that different processes play a role in changes of different types of variability acting at different levels of the system. It is proposed that insight into the nature of the underlying developmental processes and thus the nature of the system being studied is increased by examining variability at different levels of the system. Second, the variable that showed most effects across all studies was Vucm, which is the variability in joint angles that does not affect performance. Vucm was highest in younger children and decreased the most with age (Chapter 2). When task demands increased, Vucm was higher in 9 and 10-year-old children and in adults rather than Vort (Chapter 3).
Moreover, Vucm and not Vort was higher in children with DCD compared to age-matched controls (Chapter 4). Thus, higher variability at the joint angle level was mostly Vucm, which is not a sign of inconsistency because this variability in joint angles does not affect performance, and therefore does not lead to inconsistency at the performance level.
Thus, these studies offer a compelling empirical argument to consider variability in middle child- hood as something more than just inconsistency. Not all variability in mid-childhood development has a negative connotation. This is in line with studies focusing on early childhood development (0-5 years of age), which have repeatedly indicated that variability can reflect more than incon- sistency [2,3,25,38,39]. The DS theory considers variability in development as something useful [26,40,41]. Given that the system seems to channel variability at the joint angle level into variabil- ity not affecting task performance, high levels of Vucm might be useful. This is in accordance with proposals [42–44] and observations [45–49] made in the adult literature. Even though one can argue that Vort reflects inconsistency (i.e., Vort affects performance), this might not be the whole
story to Vort. It is argued later that also Vort might reflect more than inconsistency. In sum, this thesis revealed exciting results that pave the way for a new perspective on variability in middle childhood in typically as well as in atypical developing children. In the following, some suggestions are proposed for what the role of Vucm and Vort in development might be.
Potential roles of V
ucmand V
ortin development
It should be noted that the current studies do not reveal the exact role of Vucm and Vort in development.
Before the experimental studies of the current thesis were conducted, no information existed about changes in the structure of joint angle variability in mid-childhood reaching. The first important step that had to be taken was to unfold how variability changes over age and in relation with different constraints. Because the studies of the current thesis acquired knowledge about how this variability changes over age, more concrete hypotheses about the role of variability can now be formulated and consequently be tested in future studies. Proposals and argumentations of this section should there- fore be seen as suggestions and ideas of what the results could mean. These suggestions are aimed to trigger and offer new ideas and possibilities for future studies. In the following, two suggestions about the potential role of Vucm and Vort in development will be worked out in more detail. These two suggestions have also been proposed in Chapter 2,3, and 4. The first suggestion concerns the com- pensation mechanism and the second one relates to exploratory processes.
Compensation mechanism
Based on the age trends that were found for Vucm and Vort in Chapter 2 and 3, the suggestion was made that changes in Vucm and Vort could be related to a compensation mechanism. This mecha- nism has been proposed in earlier studies using the UCM method [50–53]. Applied to the found developmental changes, this compensation mechanism entails that the developmental dynamics in younger children might result in a less stable system, which could explain the high Vort at younger ages. To compensate for this higher Vort, Vucm may need to be even higher to counter the variability in joint angles that destabilizes the index-finger position (see for a detailed explanation of this compensation mechanism Chapter 2 and 3). The essential aspect of this mechanism is that Vucm and Vort have to be coupled. That is, changes in Vucm and Vort have to occur in the same direction. This is the case with the age trend: Both, Vucm and Vort, decreased with age. However, when taking into account the remaining results, some questions arise about how this mechanism can explain certain changes of Vucm and Vort. For example, how would this compensation mechanism explain the high Vucm in the challenging situation that was found in 9 and 10-year-old children in Chapter 3? This high value of Vucm cannot be a compensation for Vort, because Vort did not increase. Also, children with DCD should be expected to have a less stable system than their age-match controls, but no differences in Vort were found between these two groups. If a less stable system of younger children supposable results in a high Vort, why would an expected less stable system of children with DCD
CHAPTER 6 not result in a high Vort? Thus, when considering all results of this thesis, it seems that there might
be more to the changes in Vucm and Vort than offered by the compensation mechanism explanation.
Exploratory processes
Another suggestion about what the role of Vucm and Vort in development could be is that both, Vucm and Vort, reflect exploration. Exploration has often been quantified at the performance level where it can be defined as the search for new movement solutions to perform a task within the perceptual-motor workspace [c.f., 54]. In this context several studies about adult learning have suggested that performance variability reflects exploration for novel movement solutions [55–59].
Importantly, defining exploration at the performance level leaves room for Vort, but not for Vucm, because Vucm is the variability that does not affect performance. However, the same end-effector position can come about by different organizations of the abundant joint angles, giving various opportunities for exploration within the joint angles that cannot be quantified at the performance level. That is why this thesis emphasizes to study exploration at the joint angle level.
At the joint angle level there is a different space of exploration than at the performance level.
Here, exploration occurs within the space spanned by the joint angles (the joint space) to find the manifold representing the solutions of the task. This exploration manifests itself partly in Vucm and partly in Vort. Vucm is the search within the solution manifold, which is not seen at the performance level. Vort is the search outside the solution manifold, which is reflected at the performance level (Chapter 2). That is why it is argued that Vort might reflect more than inconsistency. Vort could reflect exploration that might be necessary to find new solutions for a task. This means that even performance variability might reflect more than inconsistency when analyzed in alternative ways.
Future studies should quantify the trial by trial changes in errors, as it might reveal an exploration pattern [c.f., 60]. Studying exploration at the joint angle level brings forth new questions. For instance, if exploration within Vucm does not lead to task improvements, what is its benefit? One possibility might be that exploration within Vucm concerns exploration of constraints that are not directly coupled to task success. For example, performing the task in an energy efficient manner could be one of these constraints. Exploration of these constraints does not need to have a direct effect on task success, but it could shape the solution manifold in a certain way, resulting, for example, in more energy efficient movements.
How do the results of the current study fit within this suggestion about exploration? For 5-year-old children reaching is not a novel task, which means that a solution manifold likely already exists.
However, children´s intrinsic dynamics might still fluctuate a lot, because many components of the system are still developing [61–63]. It could be that the specific solution manifold that reflects the match between the system´s current intrinsic dynamics and the demands of the task still needs exploring. High Vort in younger children could reflect exploration related to task success, and high Vucm could reflect exploration of constraints not directly related to task success as mentioned
previously. This could result in performance improvements [9,10,12,24] and in possible other reaching-related improvements throughout middle childhood. It could also result in reduced explo- ration throughout middle childhood, because more and more constraints have shaped the solution space, leaving less possibilities of exploration. This links to the results found in Chapter 2 and 3.
Younger children might have high levels of Vucm and Vort to discover novel solutions that are a better fit with the task demands at hand, which eventually results in performance improvement with age as seen at the performance level and possible other improvements not quantified in this thesis.
Chapter 3 found that uncertainty about the target position (increased task demands) results in a higher level of Vucm onlyin 9 and 10-year-old children and in adults. The study of Zhang et al. [64]
helps to interpret this result. In this study, adult participants had to learn a ball hitting task in a virtual environment similar to tetherball. Participants had to hit a ball at the right moment, so that the ball release would achieve a successful target hit. The virtual set-up allowed the creation of timing windows, which meant that ball releases at several points in time achieved a successful target hit. Results of this study showed that timing errors were reduced first, followed by length- ening of the timing windows in which ball releases achieved target hits. The reduction of timing errors links to Vort and the lengthening of the timing window links to Vucm. This could relate to the results of Chapter 3 in that reaching errors first have to be reduced to a certain amount before the solution manifold can be expanded when required. Task success might be a rate limiting constraint in 5- to 8-year-old children. When task success is accomplished (for a certain amount), other con- straints become more important, which seem to result in an expansion of the solution manifold.
It should be noted that a plateau was found from 7&8-year-old children to 9&10-year-old children for error and Vort. If the level of error was low enough to allow an expansion of the solution man- ifold, why did 7&8-year-old children not expand the solution manifold? An important aspect for future studies is therefore to focus more on the relation between Vucm and Vort and the performance variables of reaching related to task success and other variables that contribute to reaching such as energy efficiency or movement effort.
The suggestion that motor variability might relate to performance improvements has also been made in motor learning studies in adults [55,57,64–66]. Studies that have found beneficial effects of variability typically used reaching adaptation paradigms, where the hand’s path to the target is distorted from its typical quasi straight-line movement by either a force field or a visual manipula- tion [45,47,55,66]. With practice, the new mapping between the hand movements and the applied constraint is learned and the hand eventually recovers a quasi straight-line path. Singh et al. [66]
found, for example, that the amount of Vucm in the baseline condition was correlated to the rate of learning, but not Vort. Wu et al. [55] measured the variability in the baseline condition that was irrelevant to the trajectory of the baseline condition, but relevant to the trajectory that their move- ments would be evaluated against in a subsequent condition. Results showed that participants who had more of this ‘task relevant’ variability (comparable to Vort) in the baseline condition were faster learners in the subsequent condition both in reinforcement and error-based learning. Even
CHAPTER 6 though the exact relation between Vucm and Vort and motor learning still needs to be determined
in future studies, the fact that several studies found relationships suggests that Vucm and Vort are relevant for learning. This suggestion can be transferred to developmental changes. That is, high levels of Vucm and Vort might promote development. Establishing the relationship between Vucm and Vort in development might even help to find the relationship in motor learning.
Research strategy to continue the study
of variability in joint angles over repetitions of trials in the future
As pointed out in Chapter 5, future studies focusing on mid-childhood development should use ideas from the DS theory. Here, a research strategy is specified that emphasizes in more detail how to continue studying variability in joint angles over repetitions of trials.
Examining how the system evolves over time
Understanding processes within a dynamic system requires to see how the system evolves over time [26,67,68]. Thus, future studies should preferable use longitudinal designs. Longitudinal studies have the advantage that more attention can be paid to the individual developmental trajectory [69].
Individual differences were also indicated in Chapter 3, especially in younger children (see Figure 3 from Chapter 3). If Vucm and Vort promote development, then a 5-year-old child with high values of Vucm and Vort should have a different developmental trajectory than a 5-year-old child with low values of Vucm and Vort. Longitudinal studies could therefore be used to examine whether and how the level of Vucm and Vort at the first time of measurement related to the developmental trends of Vucm and Vort and the variability at the performance level. This could also clarify the relation between changes at the joint angle level and changes at the performance level.
In addition, more understanding about how the system evolves over time can be achieved by focus- ing on the shorter timescale of learning within the longer timescale of development. The analysis of trial to trial changes in learning is necessary for a clear understanding of exploratory processes, as the search pattern of exploration is best mirrored in changes over time. Also, a new solution manifold must be found during learning and exploration is necessary to discover this manifold for the novel task. Thus, future studies should conduct learning experiments in 5 to-10-year-old chil- dren. This could, for example, be done with a visuomotor rotation task in which a conflict is created between the visual feedback of the hand position and the actual hand position. The new mapping between the visual feedback and the actual hand position has to be learned. Baseline assessment of variability should take place to assess whether different levels of variability at the beginning of learning result in different learning curves in relation with different ages [e.g., 55,65,66].
Another aspect that concerns how the system evolves over time is the reaching movement itself.
In the current studies, the UCM method was computed at movement termination. This time point in the trajectory of the reach was chosen because the endpoint is the only constraint in the reach- ing movement. Also, performance variability at the target was compared with variability in joint angles, which meant that also joint angle variability had to be examined at movement termination.
However, as stated before, in future studies all aspects of the task should be phrased in dynamic terms. During a reaching movement the position of the end-effector evolves over time. Future studies should examine Vucm and Vort over the trajectory to generate novel information about explo- ration during the reaching trajectory.
How to quantify changes over time
The UCM method has the methodological limitation of computing variability in elemental variables over a block of trials. To overcome this limitation, future studies could conduct learning experiments with multiple blocks to assess how Vucm and Vort change over these blocks [45,66,70]. In addition, different analysis techniques should be used to better quantify trial to trial changes. Other analysis techniques that could be used in addition to the UCM method are autocorrelation and principal component analysis (PCA). Autocorrelation describes the relation of the current state of the system with the past states as a function of lags between them, and therefore provides information about the exploration pattern [54,71]. PCA can decrease the dimensionality of a given set of kinematic data and can identify the main combinations of joint angles used to perform the reaching task. It can be used to quantify the degree to which different coordination patterns are explored [18,72].
Influence of experimental settings
The UCM analysis requires the collection of kinematic data of multiple trials of a task set-up with specific constraints [4,5]. This results in an artificial experimental situation. For example, each reach has to be performed with the same initial posture, which rarely occurs in daily live. Because certain aspects of the experimental setup have to be constraint when using the UCM method, future studies should focus more on the task itself. More difficult tasks with uncertain aspects could be used. When future studies use other analysis techniques to quantify variability as described earlier, more natural task setups should be used that involve a cascade of postural, visual, and manual actions. Studies about infant reaching have done this by means of a pivot paradigm where infants sit on a motorized chair that rotates them 360° past a toy [21,73].
Clinical implications
The clinical group that was examined in the current thesis were children with DCD, which are known for their high motor variability [74–79]. High performance variability in children with DCD has been shown to hinder their performance [74,80,81] and it has, therefore, been proposed to
CHAPTER 6 reduce variability in rehabilitation practices. Results of the current thesis indicated that high motor
variability is not always detrimental. Instead, high variability in joint angles might have a positive function. This implies that rehabilitation practices should distinguish different types of variability and, consequently, should approach each type of variability differently. Importantly, not all motor variability should be reduced in rehabilitation practices. Based on the results of this thesis, future studies may investigate whether allowing or inducing variability in in joint angle configuration helps children with DCD to find more solutions for a particular task [c.f., 72].
Multi-joint coordination is impaired in many patient groups [52,72,82,83], but still, motor perfor- mance is mostly examined and assessed. The same applies to DCD, which is especially surprising considering that DCD is a coordination disorder. Recently, several studies in the DCD literature have proposed to rivet on coordination [84–86]. In addition to a few other studies that have focused on coordination in DCD [87–90], this thesis showed that characteristics of multi-joint coordination in children with DCD differ from aged-match controls (Chapter 4). Given that multi-joint coordina- tion reveals novel and important understanding about possible characteristics and mechanism of this disorder, this thesis suggests that characteristics of multi-joint coordination patterns should also be considered as an important element for identifying and diagnosing DCD. Until now, clinical assessment tools that evaluate motor functions in DCD capture endpoint performance such as the amount of errors when performing a certain task. This thesis suggests to include multi-joint coordination characteristics in clinical assessment tools. Based on Chapter 4 one could assume that it is meant that all children with high levels of Vucm might have DCD. This is, of course, not what is implied. Future studies first need to achieve a more thorough understanding of multi- joint coordination characteristic that are different in DCD. The next step should then be to find out how these characteristics can be included in current clinical scales and tools that asses motor function in DCD. Advancements of low-cost motion tracking devices can increase the feasibility of kinematic measurement for joint coordination in clinical settings. Thus, an important aspect in future studies on DCD is to focus more on the C(oordination) in DCD. It should be noted that this does not mean that other aspects related to DCD should receive less attention. Perception is, for example, another important aspect in DCD that has been shown to differ in children with DCD [35,91–93]. This thesis has started with focusing on the coordination aspect, but future studies should include the perceptual aspect.
Concluding remarks
Variability is an inherent characteristic of motor development. No matter what the theoretical orientation of empirical studies on motor development is, variability of some movement parameter is nearly always observed. In recent decades, new perspectives on how to conceive motor variability in development have been proposed in many research fields. Unfortunately, in middle childhood
reaching, both in TD children as well as in children with DCD, new perspectives on variability have rarely been applied. This thesis took a first step in changing this. The studies of this thesis have offered a compelling empirical argument to consider motor variability in middle childhood as something more than just inconsistency. It follows that not all motor variability in middle childhood development should be associated with negativity. This is also an exciting finding for research concerning DCD, because broadening the concept of motor variability in DCD may offer new understanding about possible underlying coordination mechanisms of this disorder.
Altogether, this thesis paves the way for a new perspective on motor variability in middle child- hood development. New discussions about the role of variability in middle childhood are triggered and new ideas and possibilities for future studies are offered. Importantly, this thesis turns the spotlight on the developmental period of middle childhood, therewith rejuvenating the ‘forgotten years’ of development.
This thesis also illustrates how ideas of the DS theory can positively contribute to the understand- ing of variability and reaching in general during middle childhood. The studies within this thesis can be an inspiring example for developmental studies and studies on DCD by showing how to embrace the rich variability and complexity inherent in development and how to embed this com- plexity within a systems framework. This thesis proposes that a study of development and any other aspect of human behavior has much to gain from considering the Dynamic Systems theory.
CHAPTER 6
References
1. Adolph KE, Cole WG, Vereijken B. Intraindi- vidual Variability in the Development of Motor Skills in Childhood. In: Diehl M, Hooker K, Sli- winsk M, editors. Handbook of Intra-individual Variability Across the Lifespan. New York:
Routledge/Taylor & Francis Group; 2015. pp.
59–83.
2. Vereijken B. The complexity of childhood development: variability in perspective. Phys Ther. 2010;90: 1850–1859. doi:10.2522/
ptj.20100019
3. Hadders-Algra M. Variation and variability:
key words in human motor development.
Phys Ther. 2010;90: 1823–1837. doi:10.2522/
ptj.20100006
4. Scholz JP, Schöner G. The uncontrolled mani- fold concept: Identifying control variables for a functional task. Exp Brain Res. 1999;126:
289–306. doi:10.1007/s002210050738 5. Latash ML, Scholz JP, Schöner G. Toward a
new theory of motor synergies. Motor Control.
2007;11: 276–308. doi:17715460
6. Domkin D, Laczko J, Jaric S, Johansson H, Latash ML. Structure of joint variability in bimanual pointing tasks. Exp Brain Res.
2002;143: 11–23. doi:10.1007/s00221-001- 0944-1
7. Domkin D, Laczko J, Djupsjöbacka M, Jaric S, Latash ML. Joint angle variability in 3D biman- ual pointing: Uncontrolled manifold analysis.
Exp Brain Res. 2005;163: 44–57. doi:10.1007/
s00221-004-2137-1
8. Van Der Steen MC, Bongers RM. Joint angle variability and co-variation in a reaching with a rod task. Exp Brain Res. 2011;208: 411–422.
doi:10.1007/s00221-010-2493-y
9. Ferrel C, Bard C, Fleury M. Coordination in childhood: Modifications of visuomotor rep- resentations in 6- to 11-year-old children. Exp Brain Res. 2001;138: 313–321. doi:10.1007/
s002210100697
10. Hay L. Spatial-temporal Analysis of movements in children: Motor programs versus feedback
in the developement of reaching. J Mot Behav.
1979;11: 189–200.
11. Pellizzer G, Hauert C a. Visuo-manual aiming movements in 6- to 10-year-Old children:
evidence for an asymmetric and asynchro- nous development of information processes.
Brain Cogn. 1996;30: 175–193. doi:10.1006/
brcg.1996.0011
12. Wilson PH, Hyde C. The development of rapid online control in children aged 6-12years:
Reaching performance. Hum Mov Sci. 2013;32:
1138–1150. doi:10.1016/j.humov.2013.02.008 13. Hyde CE, Wilson PH. Impaired online control
in children with developmental coordination disorder reflects developmental immaturity.
Dev Neuropsychol. 2013;38: 81–97. doi:10.10 80/87565641.2012.718820
14. Turvey MT, Fitzpatrick P. Commentary : Devel- opment of Perception-Action Systems and General Principles of Pattern Formation. Child Dev. 1993;64: 1175–1190.
15. Spencer JP, Perone S, Buss AT. Twenty years and going strong: A dynamic systems revolu- tion in motor and cognitive development. Child Dev Perspect. 2011;5: 260–266. doi:10.1111/
j.1750-8606.2011.00194.x
16. Blumberg MS, Spencer JP, Shenk D.
Introduction to the collection “How We Devel- op-Developmental Systems and the Emergence of Complex Behaviors.” Wiley Interdiscip Rev Cogn Sci. 2017;8: 2016–2017. doi:10.1002/
wcs.1413
17. Schneiberg S, Sveistrup H, McFadyen B, McKinley P, Levin MF. The development of coordination for reach-to-grasp movements in children. Exp Brain Res. 2002;146: 142–154.
doi:10.1007/s00221-002-1156-z
18. Lee M, Farshchiansadegh A, Ranganathan R.
Children show limited movement repertoire when learning a novel motor skill. Dev Sci.
2017; e12614. doi:10.1111/desc.12614 19. Savelsbergh GJ, van der Kamp J. The effect
of body orientation to gravity on early infant
reaching. J Exp Child Psychol. 1994;58:
510–528. doi:http://dx.doi.org/10.1006/
jecp.1994.1047
20. Soska KC, Adolph KE. Postural Position Con- strains Multimodal Object Exploration in Infants. 2014;19: 138–161. doi:10.1111/
infa.12039
21. Rachwani J, Golenia L, Hertzberg-Keller O, Adolph KE. Postural, Visual, and Manual Coor- dination in the Development of Prehension.
submitted.
22. Hay L, Bard C, Fleury M, Teasdale N. Kinematics of aiming in direction and amplitude: A devel- opmental study. Acta Psychol (Amst). 1991;77:
203–215. doi:10.1016/0001-6918(91)90035-X 23. Chicoine A, Lassonde M, Proteau L. Develop- mental aspects of sensorimotor integration.
Dev Neuropsychol. 1992;8: 381–394.
24. Favilla M. Reaching movements in children:
Accuracy and reaction time development. Exp Brain Res. 2006;169: 122–125. doi:10.1007/
s00221-005-0291-8
25. Thelen E, Corbetta D, Spencer JP. Develop- ment of reaching during the first year: role of movement speed. J Exp Psychol Hum Percept Perform. 1996;22: 1059–1076.
doi:10.1037/0096-1523.22.5.1059
26. Thelen E, Smith LB. A dynamic system approach to development of cognition and action. Cam- bridge, MA: MIT Press; 1994.
27. Kamm K, Thelen E, Jensen JL. Dynamical Sys- tems Approach Motor Development. Phys Ther.
1990;70: 763–775.
28. Schöner G. A dynamic theory of coordination of discrete movement. Biol Cybern. 1990;63:
257–270. doi:10.1007/BF00203449 29. Schöner G. Dynamic theory of action-per-
ception patterns: The time-before-contact paradigm. Hum Mov Sci. 1994;13: 415–439.
doi:10.1016/0167-9457(94)90048-5 30. Huys R, Perdikis D, Jirsa VK. Functional archi-
tectures and structured flows on manifolds: A dynamical framework for motor behavior. Psy- chol Rev. 2014;121: 302–336. doi:10.1037/
a0037014
31. Knips G, Zibner SKU, Reimann H, Schöner G. A Neural Dynamic Architecture for Reaching and Grasping Integrates Perception and Movement Generation and Enables On-Line Updating.
2017;11: 1–14. doi:10.3389/fnbot.2017.00009 32. Yan JH, Thomas JR, Stelmach GE, Thomas
KT. Developmental features of rapid aiming arm movements across the lifes- pan. J Mot Behav. 2000;32: 121–140.
doi:10.1080/00222890009601365
33. Thomas JR, Yan JH, Stelmach GE. Move- ment substructures change as a function of practice in children and adults. J Exp Child Psychol. 2000;75: 228–244. doi:10.1006/
jecp.1999.2535
34. Takahashi CD, Nemet D, Rose-Gottron CM, Larson JK, Cooper DM, Reinkensmeyer DJ.
Neuromotor noise limits motor performance, but not motor adaptation, in children. J Neu- rophysiol. 2003;90: 703–711. doi:10.1152/
jn.01173.2002
35. Ameratunga D, Johnston L, Burns Y. Goal-di- rected upper limb movements by children with and without DCD: a window into percep- tuo-motor dysfunction? Physiother Res Int.
2004;9: 1–12. doi:10.1002/pri.295
36. van der Meulen JH, Denier van der Gon JJ, Gielen CC, Gooskens RH, Willemse J. Visuo- motor performance of normal and clumsy children. I: Fast goal-directed arm-movements with and without visual feedback. Dev Med Child Neurol. 1991;33: 40–54.
37. Biancotto M, Skabar A, Bulgheroni M, Carrozzi M, Zoia S. Neuromotor deficits in developmen- tal coordination disorder: Evidence from a reach-to-grasp task. Res Dev Disabil. 2011;32:
1293–1300. doi:10.1016/j.ridd.2011.02.007 38. Piek JP. The role of variability in early motor
development. Infant Behav Dev. 2002;25: 452–
465. doi:10.1016/S0163-6383(02)00145-5 39. Lee D, Cole WG, Golenia L, Adolph KE. The cost
of simplifying complex developmental phe- nomena: a new perspective on learning to walk.
Dev Sci. 2017; 1–15. doi:10.1111/desc.12615 40. Deutsch KM, Newell KM. Children’s coordina-
tion of force output in a pinch grip task. Dev
CHAPTER 6 Psychobiol. 2002;41: 253–264. doi:10.1002/
dev.10051
41. Deutsch KM, Newell KM. Deterministic and Stochastic Processes in Children’s Isometric Force Variability. Dev Psychobiol. 2003;43:
335–345. doi:10.1002/dev.10140
42. Latash M. There is no motor redundancy in human movements. There is motor abundance.
Motor Control. 2000;4: 259–260. doi:10.1123/
mcj.4.3.259
43. Latash ML. The bliss (not the problem) of motor abundance (not redundancy). Exp Brain Res. 2012;217: 1–5. doi:10.1007/s00221-012- 3000-4
44. Latash ML, Scholz JP, Schöner G. Motor Con- trol Strategies Revealed in the Structure of Motor Variability. Exerc Sport Sci Rev. 2002;30:
26–31. doi:10.1097/00003677-200201000- 00006
45. Yang JF, Scholz JP, Latash ML. The role of kine- matic redundancy in adaptation of reaching.
Exp Brain Res. 2007;176: 54–69. doi:10.1007/
s00221-006-0602-8
46. Reisman DS, Scholz JP, Schöner G. Coor- dination underlying the control of whole body momentum during sit-to-stand. Gait Posture. 2002;15: 45–55. doi:10.1016/S0966- 6362(01)00158-8
47. de Freitas SMSF, Scholz JP, Stehman AJ. Effect of motor planning on use of motor abundance.
Neurosci Lett. 2007;417: 66–71. doi:10.1016/j.
neulet.2007.02.037
48. Mattos DJS, Latash ML, Park E, Kuhl J, Scholz JP. Unpredictable elbow joint perturbation during reaching results in multijoint motor equivalence. J Neurophysiol. 2011;106: 1424–
1436. doi:10.1152/jn.00163.2011
49. Scholz JP, Reisman D, Schöner G. Effects of varying task constraints on solutions to joint coordination in a sit-to-stand task. Exp brain Res. 2001;141: 485–500. doi:10.1007/
s002210100878
50. Greve C, Hortobàgyi T, Bongers RM. Physical Demand but Not Dexterity Is Associated with Motor Flexibility during Rapid Reaching in Healthy Young Adults. PLoS One. 2015;10:
e0127017. doi:10.1371/journal.pone.0127017 51. Greve C, Zijlstra W, Hortobágyi T, Bongers
RM. Not All Is Lost: Old Adults Retain Flexi- bility in Motor Behaviour during Sit-to-Stand.
PLoS One. 2013;8. doi:10.1371/journal.
pone.0077760
52. Black DP, Smith BA, Wu J, Ulrich BD. Uncon- trolled manifold analysis of segmental angle variability during walking: preadolescents with and without Down syndrome. Exp brain Res.
2007;183: 511–21. doi:10.1007/s00221-007- 1066-1
53. Wu J, McKay S, Angulo-Barroso R. Center of mass control and multi-segment coordination in children during quiet stance. Exp Brain Res.
2009;196: 329–339. doi:10.1007/s00221-009- 1852-z
54. Pacheco M, Newell K. Transfer as a function of exploration and stabilization in original prac- tice. Hum Mov Sci. 2015;44: 258–269. doi:doi:
10.1016/j.humov.2015.09.009
55. Wu HG, Miyamoto YR, Gonzales Castro LN, Ölveczky BC, Smith M a. Temporal structure of motor vriability is dynamically regulated and predicts motor learning ability. Nat Neurosci.
Nature Publishing Group; 2014;17: 312–321.
doi:10.1038/nn.3616
56. Thorp EB, Kording KP, Mussa-Ivaldi FA.
Using noise to shape motor learning. J Neu- rophysiol. 2017;117: 728–737. doi:10.1152/
jn.00493.2016
57. Abe MO, Sternad D. Directionality in distribu- tion and temporal structure of variability in skill acquisition. Front Hum Neurosci. 2013;
doi:10.3389/fnhum.2013.00225
58. Dhawale AK, Smith MA, Ölveczky BP. The Role of Variability in Motor Learning. Annu Rev Neurosci. 2017;40: 479–498. doi:10.1146/
annurev-neuro-072116-031548
59. Cardis M, Casadio M, Ranganathan R. High variability impairs motor learning regardless of whether it affects task performance. J Neu- rophysiol. 2017; jn.00158.2017. doi:10.1152/
jn.00158.2017
60. Gelfand IM, Tsetlin ML. Some methods of control for complex systems. Russ Math Surv.
1962;17: 95–116.
61. Malina RM, Bouchard C, Bar-Or O. Growth, maturation, and physical activity. 2nd ed.
Champaign, Ill: Human Kinetics, (Chapter 3);
2004.
62. van der Heide JC, Otten B, van Eykern LA, Hadders-Algra M. Development of pos- tural adjustments during reaching in sitting children. Exp Brain Res. 2003;151: 32–45.
doi:10.1007/s00221-003-1451-3
63. Kandice Mah V, Lee Ford-Jones E. Spotlight on middle childhood: Rejuvenating the “for- gotten years.” Paediatr Child Health (Oxford).
2012;17: 81–83.
64. Zhang Z, Guo D, Huber ME, Park S, Sternad D. Exploiting the geometry of the solution space to reduce sensitivity to neuromotor noise. PLoS Comput Biol. 2018;14: e1006013.
doi:10.1371/journal.pcbi.1006013
65. Herzfeld DJ, Shadmehr R. Motor variability is not noise, but grist for the learning mill. Nat Neurosci. Nature Publishing Group; 2014;17:
149–50. doi:10.1038/nn.3633
66. Singh P, Jana S, Ghosal A, Murthy A. Explo- ration of joint redundancy but not task space variability facilitates supervised motor learning. Proc Natl Acad Sci. 2016;113: 14414–
14419. doi:10.1073/pnas.1613383113 67. Turvey MT, Fitzpatrick P. Commentary: Devel-
opment of perception–action systems and general principles of pattern formation. Child Dev. 1993;64: 1175–1190.
68. Whitall J, Clark JE. Developmental Coordi- nation Disorder from a Dynamic Systems Perspective: What is on offer? Curr Dev Disord Reports. 2016;3: 94–96.
69. Golenia L, Schoemaker MM, Mouton LJ, Bongers RM. Individual Differences in Learn- ing a Novel Discrete Motor Task. PLoS One.
2014;9: e112806. doi:10.1371/journal.
pone.0112806
70. Tuitert I, Bootsma RJ, Schoemaker MM, Otten E, Mouton LJ, Bongers RM. Does practicing a wide range of joint angle configurations lead
to higher flexibility in a manual obstacle-avoid- ance target-pointing task? PLoS One. 2017;12:
e0181041.
71. Newell KM, Mayer-Kress G, Liu Y-T. Aging, time scales, and sensorimotor variability. Psy- chol Aging. 2009;24: 809–818. doi:10.1037/
a0017911
72. Ranganathan R. Reorganization of finger coor- dination patterns through motor exploration in individuals after stroke. J Neuroeng Rehabil.
2017;14: 90. doi:10.1186/s12984-017-0300-8 73. Ekberg TL, Rosander K, Von Hofsten C,
Olsson U, Soska KC, Adolph KE. Dynamic reaching in infants during binocular and mon- ocular viewing. Exp Brain Res. 2013;229: 1–12.
doi:10.1007/s00221-013-3588-z
74. Smits-Engelsman BCM, Westenberg Y, Duysens J. Children with developmental coordination disorder are equally able to generate force but show more variability than typically develop- ing children. Hum Mov Sci. 2008;27: 296–309.
doi:10.1016/j.humov.2008.02.005
75. Roche R, Viswanathan P, Clark JE, Whitall J. Children with developmental coordina- tion disorder (DCD) can adapt to perceptible and subliminal rhythm changes but are more variable. Hum Mov Sci. 2016;50: 19–29.
doi:10.1016/j.humov.2016.09.003
76. Bo J, Bastian AJ, Kagerer FA, Contreras-Vidal JL, Clark JE. Temporal variability in con- tinuous versus discontinuous drawing for children with Developmental Coordination Disorder. Neurosci Lett. 2008;431: 215–220.
doi:10.1016/j.neulet.2007.11.040
77. Volman MJM, Geuze RH. Relative phase sta- bility of bimanual and visuomanual rhythmic coordination patterns in children with a Devel- opmental Coordination Disorder. Hum Mov Sci. 1998;17: 541–572. doi:10.1016/S0167- 9457(98)00013-X
78. Geuze RH, Kalverboer AF. Inconsistency and adaptation in timing of clumsy children. Hum Mov Sci. 1987;13: 421–432.
79. Williams HG, Woollacott MH, Ivry R. Timing and motor control in clumsy children. J Mot Behav. 1992;24: 165–172.
CHAPTER 6 80. Licari MK, Reynolds JE. Understanding
Performance Variability in Developmental Coordination Disorder: What Does It All Mean?
Curr Dev Disord Reports. 2017;4: 53–59.
doi:10.1007/s40474-017-0112-3
81. Wilson PH, Ruddock S, Smits-Engelsman B, Polatajko H, Blank R. Understanding perfor- mance deficits in developmental coordination disorder: a meta-analysis of recent research.
Dev Med Child Neurol. 2013;55: 217–228.
doi:10.1111/j.1469-8749.2012.04436.x 82. Tomita Y, Rodrigues MRM, Levin MF. Upper
Limb Coordination in Individuals With Stroke : Poorly Defined and Poorly Quantified. Neu- rorehabil Neural Repair. 2017;31: 885–897.
doi:10.1177/1545968317739998
83. Reisman DS, Scholz JP. Aspects of joint coor- dination are preserved during pointing in persons with post-stroke hemiparesis. Brain.
2003;126: 2510–2527. doi:10.1093/brain/
awg246
84. Sugden DA. Developmental coordination disor- der and its cause: The road less travelled. Hum Mov Sci. 2017;57: 501–504. doi:10.1016/j.
humov.2017.04.006
85. Henderson SE, Geuze RH. Ten Conferences on Developmental Coordination Disorder (DCD):
A Brief Commentary on 20 Years of Research.
Phys Occup Ther Pediatr. 2015;35: 97–102. doi :10.3109/01942638.2015.1008896
86. Wade MG, Kazeck M. Developmental coordi- nation disorder and its cause: The road less travelled. Hum Mov Sci. 2017;57: 489–500.
doi:10.1016/j.humov.2016.08.004
87. Wilmut K, Du W, Barnett AL. Gait patterns in children with Developmental Coordination Disorder. Exp Brain Res. 2016;234: 1747–
1755. doi:10.1007/s00221-016-4592-x
88. Rosengren KS, Deconinck FJA, DiBerardino LA, Polk JD, Spencer-Smith J, De Clercq D, et al. Differences in gait complexity and vari- ability between children with and without Developmental Coordination Disorder. Gait Posture. 2009;29: 225–229. doi:10.1016/j.
gaitpost.2008.08.005
89. Wilmut K, Gentle J, Barnett AL. Gait sym- metry in individuals with and without Developmental Coordination Disorder. Res Dev Disabil. 2017;60: 107–114. doi:10.1016/j.
ridd.2016.11.016
90. Castra Ferracioli M, Yukiko Hiraga C, Pelegrini AM. Emergence and stability of interlimb coordination patterns in children with develop- mental coordination disorder. Res Dev Disabil.
2014;35: 348–356.
91. Schoemaker MM, van der Wees M, Flapper B, Verheij-Jansen N, Scholten-Jaegers S, Geuze RH. Perceptual skills of children with devel- opmental coordination disorder. Hum Mov Sci. 2001;20: 111–133. doi:10.1016/S0167- 9457(01)00031-8
92. Smits-Engelsman BCM, Blank R, van der Kaay A-C, Mosterd-van der Meijs R, Vlugt-van den Brand E, Polatajko HJ, et al. Efficacy of inter- ventions to improve motor performance in children with developmental coordination disorder: a combined systematic review and meta-analysis. Dev Med Child Neurol. 2013;55:
229–37. doi:10.1111/dmcn.12008
93. Whitall J, Getchell N, McMenamin S, Horn C, Wilms-Floet a., Clark JE. Perception-action coupling in children with and without DCD: Fre- quency locking between task-relevant auditory signals and motor responses in a dual-motor task. Child Care Health Dev. 2006;32: 679–692.
doi:10.1111/j.1365-2214.2006.00676.x
