Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Acquisition of Motor and Cognitive Skills through Repetition in Typically Developing Children

  • Sara Magallón ,

    S.Magallon@leeds.ac.uk; smagallon@unav.es

    Affiliations School of Psychology, Faculty of Medicine and Health, University of Leeds, Lifton Place, LS2 9JZ, Leeds, West Yorkshire, United Kingdom, Faculty of Education and Psychology, University of Navarra, Campus Universitario, 31080, Pamplona, Navarra, Spain

  • Juan Narbona,

    Affiliations Faculty of Education and Psychology, University of Navarra, Campus Universitario, 31080, Pamplona, Navarra, Spain, Unit of Paediatrics Neurology, Faculty of Medicine, University of Navarra, Av. de Pío XII, 36, 31008 Pamplona, Navarra, Spain

  • Nerea Crespo-Eguílaz

    Affiliations Faculty of Education and Psychology, University of Navarra, Campus Universitario, 31080, Pamplona, Navarra, Spain, Unit of Paediatrics Neurology, Faculty of Medicine, University of Navarra, Av. de Pío XII, 36, 31008 Pamplona, Navarra, Spain

Acquisition of Motor and Cognitive Skills through Repetition in Typically Developing Children

  • Sara Magallón, 
  • Juan Narbona, 
  • Nerea Crespo-Eguílaz
PLOS
x

Abstract

Background

Procedural memory allows acquisition, consolidation and use of motor skills and cognitive routines. Automation of procedures is achieved through repeated practice. In children, improvement in procedural skills is a consequence of natural neurobiological development and experience.

Methods

The aim of the present research was to make a preliminary evaluation and description of repetition-based improvement of procedures in typically developing children (TDC). Ninety TDC children aged 6–12 years were asked to perform two procedural learning tasks. In an assembly learning task, which requires predominantly motor skills, we measured the number of assembled pieces in 60 seconds. In a mirror drawing learning task, which requires more cognitive functions, we measured time spent and efficiency. Participants were tested four times for each task: three trials were consecutive and the fourth trial was performed after a 10-minute nonverbal interference task. The influence of repeated practice on performance was evaluated by means of the analysis of variance with repeated measures and the paired-sample test. Correlation coefficients and simple linear regression test were used to examine the relationship between age and performance.

Results

TDC achieved higher scores in both tasks through repetition. Older children fitted more pieces than younger ones in assembling learning and they were faster and more efficient at the mirror drawing learning task.

Conclusions

These findings indicate that three consecutive trials at a procedural task increased speed and efficiency, and that age affected basal performance in motor-cognitive procedures.

Background

From the simplest act of clapping to the complexity of playing the violin, all require the ordering and timing of actions [1]. “The acquisition of a new motor skills normally relies on several phases of learning, including a fast early learning stage, a slow later stage, consolidation, automaticity and retention” [2, 3]. Procedural memory and learning allows acquisition and consolidation of motor skills and contributes to the use of those skills [46] and to the establishment of cognitive routines [6, 7]. In contrast to declarative memory, which refers to memories which can be consciously recalled, such as, facts and knowledge, and is concerned with what something is, procedural memory is concerned with behavioral and cognitive action, i. e how to do things [8]. Procedural memory does not require intentionality for retrieval [9]; given the appropriate cue, the procedural memory pops into mind whether we intend or not, even when we may be busy with other activities requiring attention [10].

That declarative and procedural memory skills are fundamentally separate is indicated by the occurrence of dissociation between them: it is widely found and reported that the procedural memory skills of patients suffering from anterograde amnesia are still intact [1115] whereas declarative memory skills are impaired. In contrast, children with motor and coordination difficulties often retain declarative memory [1619].

The fact that the performance at a given activity improves with repetition indicates that learning is involved in procedural tasks [20, 21]. If this were not the case, performance in ordinary everyday actions would consume disproportionate amounts of cognitive resources (i.e. actualized consciousness, or attention), preventing simultaneous involvement in other tasks. Similarly, if procedures were not retained in memory, they would take much longer to implement.

Automation of a cognitive or motor procedure is achieved through repeated practice. The performance of an expert at a procedure is characterized by mastery of the skill and a consequent release of cognitive resources for other tasks [22]. Therefore, for a given task, in addition to the effectiveness and efficiency of strategies, what differentiates an experienced practitioner from a novice is that the former can do other actions at the same time.

In performing a learned procedural task, fluent movement is conducted using open-loop (feed-forward) control and is attained in an automated manner. In learning a new procedural task, more reliance on feedback information is required. The use of a closed-loop feedback control requires practice to attain automation of movement. The notion of open- and closed-loop controls has been applied to the study of motor control in fine motor learning skills as handwriting [2325].

In children, experience combined with neurobiological development results in the improvement of procedural skills (as well as other skills) [26, 27]. Children learn some procedures naturally through repetition or trial and error, with little cognitive effort. Other procedures can be acquired whilst playing games, or at school as part of a more systematic training based on repetition. Children are often unaware of the progressive development of their procedural skills and typically cannot specify exactly what they are doing or list the steps they follow. That is, children demonstrate that they can do something (i.e. their procedural learning) but may also demonstrate a lack of knowledge about how they do it (i.e. a lack of explicit learning) [28, 29].

Methods

Participants

Ninety typically developing Spanish children aged between 6 and 12 years who were randomly recruited from schools in Pamplona and Zaragoza (Spain) were included in the present study. Sex and age data are shown in Table 1. All participants came from families with a Hollingshead socioeconomic index [30] between two and three. Children schooled in a class below that corresponding to their age and children with an intelligence quotient below 85, as measured by the Peabody Picture Vocabulary Test-PPVT-III [31], were excluded. The PPVT-III was used in this case because it demands less time to be managed than other intelligence scales and it has been found to be strongly correlated with both verbal and nonverbal Intelligence Quotient (IQ) as measured by the Wechsler Intelligence Scale for Children -WISC-III- [32], the Kaufman Adolescent and Adult Intelligence Test -KAIT- [33] and the Kaufman Brief Intelligence Test -K-BIT- [34]. However, it would have been interesting to measure the intelligence by a more comprehensive test, including nonverbal skills.

All children participated voluntarily and informed written consent was obtained from their parents. The ethics committee of the Clínica Universidad de Navarra gave prior approval of the study.

Measures

Two standard procedural learning tasks were adapted to measure procedural learning: an assembly learning task, requiring primarily motor skills, and a mirror drawing learning task, which requires greater cognitive functions. Procedural learning was defined in terms of the improvement in performance on each task over repeated trials, as reflected by higher scores and greater efficiency and speed.

The Assembly Learning Task.

The assembly learning task used in this study is a motor procedural learning task adapted from the assembly subtest of the Purdue Pegboard Test [35, 36]. The Purdue Pegboard has been widely used as a predictor of the presence and laterality of cerebral lesions in adults [37, 38]. The validity and reliability of the Purdue Pegboard Test in population of 5–14 year-old children has been proved [39]. In addition, recent studies looking at motor development and motor impairment within samples constituted by children used the Purdue Pegboard Test as a measure [40, 41]. The test involves the assembly of small metal pins (pegs), collars and washers in groups of four onto a pegboard. The order of assembly is pin-washer-collar-washer. Children are asked to alternate the hand for each component added. Right-handed children are asked to start with the right hand and left-handed children, with the left. The score is the number of assembled pieces (NAP) in 60 seconds.

The adaptation made in this study was that participants were asked to repeat the task four times: three times consecutively, and the fourth after a 10-minute nonverbal interference task. This adaptation was made in order to evaluate the process of procedural learning. Three external researchers (not involved in this study) who are experts on the assessment of procedural learning agreed to evaluate the validity of the task for this purpose. It was found agreement between the three of them. This adaptation has been used as a measure of procedural learning in a recent study [42].

Percentage improvement in NAP scores were calculated as, for example: %NAP1-2 = [(NAP2 –NAP1) 100] / NAP1, where the subscripts 1 and 2 refer to the first and second trials, respectively. NAP1 reflects the baseline scores (basal skills); NAP2 and NAP3 reflect performances after repetition; NAP4 reflects performance after interference. Similarly, %NAP1-2, %NAP1-3, and %NAP1-4 measure improvement for the first to the second, third and fourth trials, respectively. In addition to NAP scores, we recorded whether children learned the assembly order and whether they alternated the hand for each component added. Motor skill improvement has been measured by percentage improvement in other studies [43].

The Mirror Drawing Learning Task.

The mirror drawing learning task used in this study was based on the Mirror Drawing Test [4447]. The original task involves drawing a five-pointed star through a mirror. The test has been used to study preserved skills in individuals with anterograde amnesia [12], in neuroimaging studies [48], in research into perceptual motor skills [49] and in research on anxiety and mental fatigue caused by prolonged cognitive load [5052]. A computerized version of the test is included in Physiology of Behavior [53]. Balinsky & Stone [54] established the normal performance values for high-school children at mirror drawing a six-pointed star, and Clinton [47] published norms on mirror-drawing for children by age (7–13 years old) and sex.

In this study we used an adapted task with the following characteristics. Instead of a star, participants were asked to draw a line in a single stroke. The drawing sheet was under a small "table" where it was not directly visible but where it could be seen, together with the hand, by means of a mirror. Each child was tested individually, and only provided with verbal instructions when they had the set-up in front of them. Specifically, the task involved drawing a line in the space contained between two straight, parallel lines, if possible without lifting the pencil from the drawing sheet. In the case of right-handed children, the drawing stroke was to run downward from left to right. Left-handed children (8 participants) were asked to draw downward from right to left. Each subject performed the task four times: three trials in a row and the last one after a period with interference. Three external researchers with extensive experience using the Mirror Drawing Test [4447] agreed on the validity of our adaptation for the measurement of procedural learning. This adaptation has been used as a measure of procedural learning in a recent study [42]. Even with its simplified and adapted form, the mirror drawing task used here is considerably more complex than the assembly learning task.

For each trial, we recorded the time required to draw the line (from start until the end of the parallel lines was reached) and the number of errors (leaving the parallel lines and/or skipping stretches). Number of errors has been proved to have an important influence on the motor skills acquisition of children [55]. Errors were manually counted independently by two of the authors and only in case of disagreement, the third author was involved. If a subject had required more than three minutes and 30 seconds to complete the trial, the trial was considered failed. From the time spent (T) and the number of errors (NE) we calculated an efficiency index (EI) as: EI = 10 (40—NE / T). A credit of 40 points was assigned for completion of the line, the precise value being chosen on the basis of the maximum number of errors made by any one subject (which was 38).

Improvement was measured as the percentage improvement [43] in time and also as the percentage improvement in efficiency index. Percentage time improvement (% T), for example between trials one and two, was calculated as: %T1-2 = [(T1 –T2) 100] / T1. The corresponding percentage efficiency improvement (%EI) was calculated as: %EI1-2 = [(EI2 –EI1) 100] / EI1.

As with the Assembly Learning Task, measurement and score subscripts refer to sequential order of trials; T1 and EI1 reflect basal skill; T2, EI2, T3 and EI3 reflect skills developing with practice; and T4 and EI4 reflect performance after interference. Similarly, %T1-2 and %EI1-2, %T1-3 and %EI1-3, and%T1-4 and %EI1-4 reflect the improvement from the first to the second, third and fourth trials, respectively.

Statistical analysis

The influence of repeated practice on performance was evaluated by means of analysis of variance (ANOVA) with repeated measures, using Bonferroni correction for Post hoc test, when the differences between pairs were normally distributed; and paired-sample tests (Wilcoxon signed-rank Test or Sign Test) were used with non-parametric data, for which the scores on different trials of the same test were considered to be paired samples.

In order to examine the relationship between age and performance, we calculated Pearson and Spearman correlation coefficients and analyzed differences with the Mann-Whitney U test (for two independent samples). In addition, a simple linear regression test (Theil's Incomplete Method) was used. Correlations between the scores of both tasks were evaluated by Spearman coefficient.

Results

Assembly Learning Task

Scores obtained by participants in their first trial were consistent with those in the Purdue Pegboard Examiner Manual for children between 6–12 years old [35]. All participants learned the order in which the pieces had to be assembled, and 90.1% of them properly alternated the hand for each component added. Number of assembled pieces (NAP) scores increased by 18.5% after three trials and 20.7% after the interference process.

As shown in Table 2 and Fig 1, typically developing children, as a group, achieved higher NAP scores through repetition. There are significant differences between NAP1 and NAP2 in all age ranges except the 10-year-old group; between NAP1 and NAP3 in all age groups; and between NAP1 and NAP4 in all age ranges except the 7-year-old group (see descriptive statistics in S1 Appendix).

thumbnail
Fig 1. Performance on Assembly Learning Task.

Median scores of Number of assembled pieces in trials 1 and 4. o, outliers.

https://doi.org/10.1371/journal.pone.0158684.g001

thumbnail
Table 2. Performance on Assembly learning task and Mirror drawing learning task.

https://doi.org/10.1371/journal.pone.0158684.t002

Older children fitted more pieces than younger ones in all trials (Fig 2 and S1 Appendix). There was strong correlation (rs > 0.7) between age and performance in each trial, and coefficients in regression studies were also significant (Fig 3 and Table 3).

thumbnail
Fig 2. Performance on Assembly Learning Task by age.

Legend: Number of assembled pieces (mean scores) in trials 1 and 4.

https://doi.org/10.1371/journal.pone.0158684.g002

thumbnail
Fig 3. Number of assembled pieces in trial 1 by age.

Legend: Regression line (with upper and lower confidence intervals).

https://doi.org/10.1371/journal.pone.0158684.g003

In order to simplify analysis of the relationship between improvement (improvement percentages) and age, participants were grouped into the three age ranges by which elementary school education is divided in Spain: 6–8, 9–10 and 11–12 years. Children in the 11–12 year-old group had higher NAP improvement percentages than children in the 6–8 and 9–10 year-old groups. Specifically, there were significant differences in %NAP1-2 between 6–8 and 11–12 year-olds; in %NAP1-2 between 9–10 and 11–12 year-olds; and in %NAP1-3 between 6–8 and 11–12 year-olds (Table 4). Thus the older group demonstrated larger improvement of skills than the younger groups. However, 9–10 year-olds did not have higher improvement percentages than 6–8 year-olds (Table 5).

Mirror Drawing Learning Task

The difficulty of the mirror drawing learning task was reflected by the fact that 16% of the participants required more than three minutes and 30 seconds to complete the task the first time they faced it; after four trials this percentage decreased to 8%.

Completion time decreased over the course of the first three consecutive trials as well as in the final post-interference trial (Table 2 and Fig 4). There were significant differences between T1 and T4 in all age ranges (see descriptive statistics in S1 Appendix). Shorter completion times correlated with older age (Table 3 and Fig 5): the correlations between age and T1 and T3 were moderate, and correlation between age and T4 was strong.

thumbnail
Fig 4. Median scores in Mirror Drawing Learing Task completion times in trials 1 and 4.

Legend: o, outliers; *, extreme outliers.

https://doi.org/10.1371/journal.pone.0158684.g004

thumbnail
Fig 5. Mirror drawing learning task completion times in trials 1 and 4 by age (mean times).

https://doi.org/10.1371/journal.pone.0158684.g005

With repetition, the typically developing children in our sample became more efficient (measured by Efficiency Index-EI) at the mirror drawing learning task (Table 2 and Fig 6). There were significant differences between EI1 and EI3 and between EI1 and EI4 in all age groups (see descriptive statistics in S1 Appendix). There was a strong correlation between age and EI1 and EI2 and moderate correlation between age and EI3 and EI4; the increase in EI with age is shown in Fig 7. Note that EI increases specially at the stage of 11 years; an explanation for this result could be that at this stage the proportion of males is larger than the number of females. Equations of the regression lines are shown in Table 3.

thumbnail
Fig 6. Mirror drawing learning task efficiency indices in trials 1 and 4.

Legend: o, outliers.

https://doi.org/10.1371/journal.pone.0158684.g006

thumbnail
Fig 7. Mirror drawing learning task efficiency indices by age (mean values).

https://doi.org/10.1371/journal.pone.0158684.g007

Efficiency improvement percentages decreased with age (Table 5): %EI1-3 was higher in 6–8 year-olds than in 11–12 year-olds (p < .01); %EI1-3 was higher in 9–10 year-olds relative to 11–12 year-olds (p < .01); and %EI1-4 was higher in 6–8 year-olds than 11–12 year-olds (p < .01) (Table 4).

Relationship between scores in the assembly learning task and the mirror drawing learning task

Correlations between the scores in the assembly learning task and the mirror drawing learning tasks were found in the 6–8 year-old group and in the 11–12 year-old group (S2 Appendix).

Discussion

Influence of training on procedural learning

In our study, three consecutive trials at a procedural task increased speed, score and efficiency. Improvement by repetition occurred in both of the tasks evaluated: assembly, which requires motor skills, and mirror drawing, which requires more cognitive functions. Although it was possible to identify differences between groups at a criterion of significance of p < .01, it should be noted that standard deviations in performance measurements in this study tended to be high, indicating the need for a large sample size in any future studies along these lines.

In the assembly learning task, participants were allowed a fixed 60-second time period in which to do the assembly trial. Determination of how much time to allow was not part of the experimental design, but 60 seconds is, perhaps, rather short to permit maximal improvement between the consecutive trials. Nevertheless, statistically significant performance differences were observed. In the second task used, the mirror drawing learning task, repetition reduced both the time required and, to a greater degree, the number of errors.

A ten-minute period of interference with procedural memory tasks, which was imposed after the three consecutive trials, resulted in only a slight stalling in the rate of improvement in performance. Note that this interference period did not impair performance in the tasks, suggesting that repeating a trial three times is sufficient to significantly improve it.

Our results are consistent with published reports. In a longitudinal study of implicit memory, as a secondary finding it was noted that training on a computerized serial reaction-time task reduced the reaction time [56]. Ward et al. [15], using a rotary pursuit task and a mirror reading test, studied procedural memory in children with amnesia. Participants repeated the tasks four times in a row, and a fifth time after a 30 minute break. As an incidental finding, the authors report that for both tasks the performance of the typically developing children evaluated as controls improved through training. Learning was defined as a decrease in the time required and a decrease in number of errors; the authors do not specify whether one of these measures predominated. Interestingly, children with amnesia due to traumatic brain injury had preserved procedural memory skills.

Prehn-Kristensen et al. [57] used a learning session comprising ten trials at a mirror tracing task as part of a study into the influence of sleep on emotional declarative and procedural memory. The authors noted that participants got faster and made fewer errors as the learning session progressed. Sullivan et al. [58] examined the practice of 200 trials of a discrete arm movement with specific spatiotemporal parameters, finding that all participants (twenty adults and twenty 8–14 year-old children), regardless the beedback given, improved accuracy and consistency across practice trials. In a similar design, Murphy et al. [59] analyzed the effects of three types of augmented feedback on the acquisition and retention of a stationary kicking skill through repetition; all children (third grade elementary students) showed significant performance improvement independently of the type of feedback. The effect of part and whole practice in motor learning was recently studied in a sample of first, third and fifth grade children; the results suggested that all students improved their juggling skills through repetition (both in part and whole practice conditions) [60]. The effects of practice on the acquisition of a simple grapho-motor task has been measured in a sample of 5–8 year-old children [61]. Vicari et al. [62, 63] investigated the effects of specific types of tasks on the efficiency of implicit procedural learning in the presence of developmental dyslexia. Participants and matched normal-reader controls were given the serial reaction-time test and the mirror-drawing test, in which implicit knowledge was gradually acquired across multiple trials. In the control participants, the speed of tracing increased and the number of errors decreased with repetition. Elbert et al. [64] reported that, with procedural tasks, the number of errors was initially high but could decrease with repetition to the standards of an expert. Similar results have been reported in studies of motor learning in adults. Reddon et al. [65] evaluated temporal stability and efficacy of lateralization for the Purdue Pegboard test in 26 adult participants assessed five-times at weekly intervals; the performance of female participants on the assemblies subtest was found to increase significantly.

Influence of age on the development of procedural memory

Procedural memory involves the learning of a cognitive process (which is then done with greater efficiency) or of a motor procedure (which can then be done with greater spatial and temporal accuracy). When a cognitive or motor exercise is repeated sufficiently to automate it, the attention required to carry it out decreases to the point that it no longer requires awareness to be carried out [10].

In the present study, we found that age affected basal performance in motor procedures (assembly) and affected the basal time requirement and basal efficiency in the use of cognitive strategies (mirror drawing). These results are consistent with those reported by other researchers. Several studies conclude that the basal ganglia, which are crucial at the neural level for implicit learning, attain highest development between 7.5 and 10 years of age [66, 67].

Nelson [68] assessed visuomotor sequence learning in 4- to 10-year-old children using a serial reaction-time (SRT) task to which half of the participants had previous exposure. Age-related differences were found in explicit knowledge but also, to a lesser degree, in implicit knowledge. Differences on the SRT task performance across age groups have been reported by other authors (Du, 2012). Thomas et al. [69] studied performance at an implicit learning task (requiring a bimanual response) by 7-year-old children and adults aged between 23 and 33 years. Various age-related differences were found. Similarly, De Guise & Lassonde [70] found a directly proportional relationship between age and implicit learning of a two-hand (but not single-hand) response. Cognitive procedural learning among children and adolescents (9–18 years old) with or without spastic cerebral palsy was analyzed: an age effect was found among typically developing children on Probabilistic Classification Learning (PCL) [71].

In contrast, Meulemans and Van der Linden [72] found no age-related differences in SRT performance in a sample of 6- and 10-year-old children and adults. Karatekin, Marcus, & White [73], also using SRT tests, found little evidence of differences in incidental learning capacities (sequence-learning indices) during middle childhood and adolescence. Their results suggested that the ability to learn a sequence rapidly under incidental conditions is mature by 8 to 10 years of age. In a recent study, examining motor and cognitive procedural learning (SRT and PCL) the results showed similar learning effects in three age groups (8, 10 and 12 years old) [74]. Schacter & Moscovitch [75] have suggested that the brain structures involved in implicit memory develop before those crucial for explicit memory.

That age influences baseline procedural skills as a consequence of neurobiological development and experience would not be surprising [26], although there is not an over-abundance of studies that specifically analyze and demonstrate it. However, there is even less research on how age affects an individual's capacity to improve, by means of repetition, his or her performance of procedural tasks. In the present study, we calculated percentage improvement from the first to successive trials and compared these percentages for our participants divided into three age groups (6–8, 9–10 and 11–12 year-olds). At the assembly learning task, 11–12 year-olds improved faster than 6–8 year-olds. At the predominantly cognitive task of mirror-drawing, however, 6–8 year-olds improved in efficiency faster than the 11–12 year-olds. This latter result may be a consequence of a ceiling effect in the learning of mirror-drawing; ceiling effects have been reported for healthy subjects in various procedural memory tests, such as, the Porteus Maze [14, 76], the Pursuit Rotor test [14] and performing faster finger responses [77]. Other explanations are that implicit sequence learning depends on the structure of response execution and on the relative task difficulty [78, 79], and that the greatest learning is exhibited at an optimal level of cognitive challenge [80]. In view of the importance of age in the development and maturation of the capacity to learn cognitive and motor skills, it would be interesting to evaluate the learning of assembly and mirror-drawing tasks in children under the age of six years.

Although it can be difficult to verbalize the steps followed in an efficient performance of a procedure or to justify one order rather than another [81], this does not necessarily mean, that it is not possible to become aware of how to perform a strategy. Making the sequence of actions that constitute a task explicit, for example, by prior or in situ verbalization, can help children with difficulties in the acquisition and automation of procedures [82].

A limitation of this study is that, the small sample size of a wide age range, resulted to a few children in each age group of the study.

Conclusions

These findings indicate that in the population of 6–12 years old typically developing children, three consecutive trials at a procedural task increased speed and efficiency. And that age affected basal performance in motor-cognitive procedures.

Supporting Information

S1 Appendix. Mean and standard deviation of the measures of performance by age range.

https://doi.org/10.1371/journal.pone.0158684.s001

(DOCX)

S2 Appendix. Correlation between Assembly Learning Task scores and Mirror Drawing Learning Task scores.

https://doi.org/10.1371/journal.pone.0158684.s002

(DOCX)

Acknowledgments

This research was supported by the “Pre-doctoral grant from the Government of Navarra”. We are very grateful to the children, parents and teachers who participated in this project for their generous cooperation. Finally, we are immensely grateful to the School of Psychology of the University of Leeds, and the Marie-Curie Actions (European Commission) for funding the publication of the paper.

Author Contributions

Conceived and designed the experiments: JN NCE. Performed the experiments: SM. Analyzed the data: SM. Contributed reagents/materials/analysis tools: JN NCE. Wrote the paper: SM JN.

References

  1. 1. Clark JE, editor. Sequence learning: An old problem revisited-Introduction. Journal of Sport & Exercise Psychology; 2012: Human Kinetics Publ Inc.
  2. 2. Doyon J, Penhune V, Ungerleider LG. Distinct contribution of the cortico-striatal and cortico-cerebellar systems to motor skill learning. Neuropsychologia. 2003;41(3):252–62. pmid:12457751
  3. 3. Barakat M, Doyon J, Debas K, Vandewalle G, Morin A, Poirier G, et al. Fast and slow spindle involvement in the consolidation of a new motor sequence. Behavioural Brain Research. 2011;217(1):117–21. pmid:20974183
  4. 4. Heindel W, Butters N, Salmon D. Impaired learning of a motor skill in patients with Huntington's disease. Behavioral Neuroscience. 1988;102:141–7. pmid:2965592
  5. 5. Petersen S, Mier Hv, Fiez J, Raichle M. The effects of practice on the functional anatomy of task performance. Proceedings of the National Academy of Sciences. 1998;USA:853–60.
  6. 6. Cavaco S, Anderson S, Allen J, Castro-Caldas A, Damasio H. The scope of preserved procedural memory in amnsia. Brain. 2004;127:1853–67. pmid:15215216
  7. 7. Raichle M, Fiez J, Videen T, MacLeod A, Pardo J, Fox P, et al. Practice-related changes in human brain functional anatomy during nonmotor learning. Cerebral Cortex. 1994; 4:8–26. pmid:8180494
  8. 8. Crespo-Eguílaz N, Magallón S, Narbona J. Procedural skills and neurobehavioral freedom. Frontiers in Human Neuroscience. 2014;8.
  9. 9. Squire L. Mechanisms of memory. Science. 1986;232:1612–19. pmid:3086978
  10. 10. Moscovitch M. Recovered consciousness: A hypothesisconcerning modularity and episodic memory. Journal of Clinical & Experimental Neuropsychology. 1995;17:276–90.
  11. 11. Dunn R. Case of suspension of the mental faculties. Lancet. 1845;2:588–90.
  12. 12. Milner B. Memory disturbance after bilateral hippocampal lesions. In: Milner P, Glickman S, editors. Cognitive processes and the brain. Princeton, NJ: Van Nostrand; 1965.
  13. 13. Cohen N, Squire L. Preserved learning and retention of pattern analyzing skill in amnesics: Dissociation of knowing how and knowing that. Science. 1980;210:207–10. pmid:7414331
  14. 14. Ewert J, Levin H, Watson M, Kalinsky Z. Procedural memory during posttraumatic amnesia in survivors of severe closed head injury. Archives of Neurololy. 1989;46:911–6.
  15. 15. Ward H, Shum D, Wallace G, Boon J. Pediatric traumatic brain injury and procedural memory. Journal of clinical and experimental neuropsychology. 2002;24(4):458–70. Epub 2002/08/21. pmid:12187459
  16. 16. Rourke B. Syndrome of nonverbal learning disabilities: the final common pathway of white-matter disease/dysfunction? Clinical Neuropsychologist. 1987;1:209–34.
  17. 17. Rourke B. Nonverbal learning disabilities: the síndrome and the model. New York: Guilford Press.; 1989.
  18. 18. Rourke B. Syndrome of nonverbal learning disabilities: neurodevelopmental manifestations. New York: Guilford Press; 1995.
  19. 19. Rourke B, Tsatsanis K. Syndrome of nonverbal learning disabilities: Psycholinguistic assets and deficits. Topics in Language Disorders. 1996;16(2):30–44.
  20. 20. Willingham D. A Neuropsychological Theory of Motor Skill Learning. Psychological Review. 1998;105(3):558–84. pmid:9697430
  21. 21. Willingham D, Koroshetz W. Evidence for dissociable motor skills in Huntington's disease patients. Psychobiology. 1993;21:173–82.
  22. 22. Ericsson K. Protocol analysis and expert thought: concurrent verbalizations of thinking during experts' performance on representative tasks. In: Ericsson K, Charness N, Hoffman R, Feltovich P, editors. The Cambridge handbook of expertise and expert performance. Cambridge: Cambridge University Press; 2006.
  23. 23. Mergl R, Tigges P, Schroter A, Moller HJ, Hegerl U. Digitized analysis of handwriting and drawing movements in healthy subjects: methods, results and perspectives. J Neurosci Methods. 1999;90(2):157–69. pmid:10513598
  24. 24. Chang SH, Yu NY. Characterization of motor control in handwriting difficulties in children with or without developmental coordination disorder. Dev Med Child Neurol. 2010;52(3):244–50. pmid:20002122
  25. 25. Kharraz-Tavakol OD, Eggert T, Mai N, Straube A. Learning to write letters: transfer in automated movements indicates modularity of motor programs in human subjects. Neurosci Lett. 2000;282(1–2):33–6. pmid:10713389
  26. 26. Tulving E. Multiple memory systems and consciousness. Human Neurobiology. 1987;6:67–80. pmid:3305441
  27. 27. Tallet J, Albaret J-M, Rivière J. The role of motor memory in action selection and procedural learning: insights from children with typical and atypical development. Socioaffective neuroscience & psychology. 2015;5.
  28. 28. Schacter D. Memory distortion: History and current status. In: Schacter D, editor. Memory distortion How minds, brains, and societies reconstruct the past. Cambridge, MA: Harvard University Press; 1995.
  29. 29. Soprano A. Memoria humana: naturaleza y tipos. In: Soprano A, Narbona J, editors. La memoria del niño Desarrollo normal y trastornos. Barcelona: Elsevier-Doyma; 2007. p. 1–43.
  30. 30. Hollingshead A. Two factors index of social position. New Haven, CN: Author; 1957.
  31. 31. Dunn LM, Dunn L, Arribas D. Test de vocabulario en imágenes Peabody (PPVT-III). Madrid: TEA; 2006.
  32. 32. Wechsler D. Wechsler Intelligence Scale for Children. 3 ed. New York: Psychological Corporation.; 1991.
  33. 33. Kaufman A, Kaufman N. Kaufman Adolescent and Adult Intelligence Test Manual. Circle Pines, MN: American Guidance Service; 1993.
  34. 34. Kaufman A, Kaufman N. Manual for the Kaufman Brief Intelligence Test. Circle Pines, MN: American Guidance Service; 1990.
  35. 35. Tiffin J. Purdue pegboard: examiner manual. Chicago: Science Research Associates; 1968.
  36. 36. Tiffin J, Asher E. The Purdue Pegboard: norms and studies of reliability and validity. Journal of Applied Psychology. 1948;32(3):234–47. pmid:18867059
  37. 37. Costa L, Vaughan J, Herbert G, Levita E, Farber N. Purdue Pegboard as a predictor of the presence and laterality of cerebral lesions. Journal of Consulting Psychology. 1963;27(2):133–7.
  38. 38. Rapin I, Tourk L, Costa L. Evaluation of the Purdue Pegboard as a Screening Test for Brain Damage. Developmental Medicine & Child Neurology. 1966;8(1):45–54.
  39. 39. Knights RM, Moule AD. Normative data on the motor steadiness battery for children. Percept Mot Skills. 1968;26(2):643–50. pmid:5659094
  40. 40. O'Donnell KJ, Rakeman MA, Zhi-Hong D, Xue-Yi C, Mei ZY, DeLong N, et al. Effects of iodine supplementation during pregnancy on child growth and development at school age. Developmental Medicine & Child Neurology. 2002;44(02):76–81.
  41. 41. Louis ED, Garcia WE, Rauh VA. Tremor in a Population-Based Cohort of Children in New York City. Pediatr Neurol. 2015;52(2):187–91. pmid:25455018
  42. 42. Magallón S, Crespo-Eguilaz N, Narbona J. Procedural Learning in Children With Developmental Coordination, Reading, and Attention Disorders. Journal of Child Neurology. 2015.
  43. 43. Walker MP, Brakefield T, Seidman J, Morgan A, Hobson JA, Stickgold R. Sleep and the Time Course of Motor Skill Learning. Learning & Memory. 2003;10(4):275–84.
  44. 44. Starch D. A demonstration of the trial and error method of learning. Psychological Bulletin. 1910;7:20–4.
  45. 45. Yoakum C, Calfee M. An analysis of the mirror drawing experiment. Journal of Educational Psychology. 1913;4(5):283–92.
  46. 46. Whipple G. Manual of mental and physical tests. Baltimore, MD: Warwick & York; 1921.
  47. 47. Clinton R. Nature of mirror-drawing ability: norms on mirror-drawing for white children by age and sex. Journal of Educational Psychology. 1930;21(3):221–8.
  48. 48. Desmond J, Fiez J. Neuroimaging studies of the cerebellum: language, learning and memory. Trends in Cognitive Science. 1998;2:355–62.
  49. 49. Marks R. Ipsilateral and contralateral skill acquisition following random practice of unilateral mirror-drawing. Perceptual & Motor Skills. 1996;83:715–22.
  50. 50. Mizuno K, Tanaka M, Yamaguti K, Kajimoto O, Kuratsune H, Watanabe Y. Mental fatigue caused by prolonged cognitive load associated with sympathetic hyperactivity. Behavioral and Brain Functions. 2011;7:17. pmid:21605411
  51. 51. Yoshiuchia K, Nomuraa S, Andob K, Ohtakec T, Shimosawab T, Kumanoa H, et al. Hemodynamic and Endocrine Responsiveness to Mental Arithmetic Task and MirrorDrawingTest in Patients With Essential Hypertension. American Journal of Hypertension. 1997;10(3):243–9. pmid:9056680
  52. 52. Homma S. Correlations between the responses of electrogastrograms, heart rate and respiratory rate to the stress of the mirror drawing test in human subjects. Journal of Smooth Muscle Research. 2006;42(1):9–19. pmid:16702760
  53. 53. Carlson N. Fisiología de la conducta. Madrid: Pearson-Addison Wesley; 2006.
  54. 54. Balinsky B, Stone I. High school norms for the mirror-drawing test of the six-pointed star. The Pedagogical Seminary and Journal of Genetic Psychology. 1940;56:207–10.
  55. 55. Capio C, Sit C, Abernethy B, Masters R. The possible benefits of reduced errors in the motor skills acquisition of children. Sports Medicine, Arthroscopy, Rehabilitation, Therapy & Technology. 2012;4(1):1.
  56. 56. Lum J, Kidd E, Davis S, Conti-Ramsdem G. Longitudinal study of declarative and procedural memory in primary school-aged children. Australian Journal of Psychology. 2010;62(3):139–48.
  57. 57. Prehn-Kristensen A, Göder R, Chirobeja S, Breßmann I, Ferstl R, Baving L. Sleep in children enhances preferentially emotional declarative but not procedural memories. Journal of Experimental Child Psychology. 2009;104:132–9. pmid:19251274
  58. 58. Sullivan K, Kantak S, Burtner P. Motor learning in children: feedback effects on skill acquisition. Phys Ther. 2008;88:720–32. pmid:18339797
  59. 59. Murphy KL, Liu J, Parrow DM, Coughlin MA. The effects of three types of augmented feedback on children's acquisition and retention of a motor skill. Research Quarterly for Exercise and Sport. 2002;73(1):A51–A.
  60. 60. Chan JSY, Luo Y, Yan JH, Cai L, Peng K. Children’s age modulates the effect of part and whole practice in motor learning. Human Movement Science. 2015;42:261–72. pmid:26112404
  61. 61. Julius MS, Adi-Japha E. Learning of a simple grapho-motor task by young children and adults: similar acquisition but age-dependent retention. Frontiers in Psychology. 2015;6:225. pmid:25798120
  62. 62. Vicari S, Finzi A, Menghini D, Marotta L, Baldi S, Petrosini L. Do children with developmental dyslexia have an implicit learning deficit? Journal of Neurology, Neurosurgery & Psychiatry. 2005;76:1392–7.
  63. 63. Vicari S, Marotta L, Menghini D, Molinari M, Petrosini L. Implicit learning deficit in children with developmental dyslexia. Neuropsychologia. 2003;41:108–14. pmid:12427569
  64. 64. Elbert T, Pantev C, Wienbruch C, Rockstroh B, Taub E. Increased cortical representation of the fingers of the left hand in string players. Science. 1995;270:305–7. pmid:7569982
  65. 65. Reddon J, Gill D, Gauk S, Maerz M. Purdue Pegboard: Test-Retest estimates. Perceptual and Motor. 1988;66:503–6.
  66. 66. Giedd J, Blumenthal J, Jeffries N, Castellanos F, Liu H, Zijdenbos A. Brain development during childhood and adolescence: a longitudinal MRI study. Nature Neuroscience. 1999;2:861–3. pmid:10491603
  67. 67. Lenroot R, Giedd J. Brain development in children and adolescents: Insights from anatomical magnetic resonance imaging. Neuroscience and Biobehavioral Reviews. 2006;30(718–729). pmid:16887188
  68. 68. Nelson C. The ontogeny of human memory: A cognitive neuroscience perspective. Developmental Psychology. 1995;31:723–38.
  69. 69. Thomas K, Hunt R, Vizueta N, Sommer T, Durston S, Yang Y. Evidence of developmental differences in implicit sequence learning: An fMRI stude of children and adults. Journal of Cognitive Neuroscience. 2004;16:1339–51. pmid:15509382
  70. 70. Guise ED, Lassonde M. Callosal contribution to procedural learning in children. Developmental Neuropsychology. 2001;19:253–72. pmid:11758668
  71. 71. Gofer-Levi M, Silberg T, Brezner A, Vakil E. Cognitive procedural learning among children and adolescents with or without spastic cerebral palsy: The differential effect of age. Research in Developmental Disabilities. 2014;35(9):1952–62. pmid:24858793
  72. 72. Meulemans T, Linden MVd. Implicit Sequence Learning in Children. Journal of Experimental Child Psychology. 1998;69:199–221. pmid:9654439
  73. 73. Karatekin C, Marcus D, White T. Oculomotor and manual indexes of incidental and intentional spatial sequence learning during middle childhood and adolescence. Journal of Experimental Child Psychology. 2007;96:107–30. pmid:16828110
  74. 74. Mayor-Dubois C, Zesiger P, Van der Linden M, Roulet-Perez E. Procedural learning: A developmental study of motor sequence learning and probabilistic classification learning in school-aged children. Child Neuropsychology. 2016;22(6):718–34. pmid:26144545
  75. 75. Schacter D, Moscovitch M. Infants, amnesics, and dissociable memory systems. In: Moscovitch M, editor. Advances in the stude of communication and affect. New York: Plenum Publishing Corporation; 1984. p. 173–216.
  76. 76. Vakil E, Agmon-Ashkenazi D. Baseline Performance and Learning Rate of Procedural and Declarative Memory Tasks: Younger Versus Older Adults. Journal of Gerontology: Psychological Sciences. 1997;52(B5):229–34.
  77. 77. Molinari M, Leggio M, Solida A, Ciorra R, Misciagna S, Silveri M, et al. Cerebellum and procedural learning: evidence from focal cerebellar lesions. Brain. 1997;120:1753–62. pmid:9365368
  78. 78. Bo J, editor. Sequence learning: An old problem revisited-Cognitive and neural contributions to motor sequence learning. Journal of Sport & Exercise Psychology; 2012: Human Kinetics Publ Inc.
  79. 79. Smith PJ, Wojewnik KT, editors. The effect of focus of attention and age on children's learning of two motor skills differing in complexity. Journal of Sport & Exercise Psychology; 2009: Human Kinetics Publ Inc.
  80. 80. Sidaway B, Bates J, Occhiogrosso B, Schlagenhaufer J, Wilkes D, editors. Task complexity and KR frequency interact in children's motor skill learning. Journal of Sport & Exercise Psychology; 2012: Human Kinetics Publ Inc.
  81. 81. Goodale M, Milner A. Separate visual pathways for perception and action. Trends in Neurosciences. 1992;15:20–5. pmid:1374953
  82. 82. Magallón S, Narbona J. Detección y estudios específicos en el trastorno de aprendizaje procesal. Revista de neurología. 2009;48(Supl 2):71–7.