University of Groningen Movement, cognition and underlying brain functioning in children van der Fels, Irene

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University of Groningen

Movement, cognition and underlying brain functioning in children

van der Fels, Irene

DOI:

10.33612/diss.109737306

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Publication date: 2020

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van der Fels, I. (2020). Movement, cognition and underlying brain functioning in children. Rijksuniversiteit Groningen. https://doi.org/10.33612/diss.109737306

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537804-L-bw-vd Fels 537804-L-bw-vd Fels 537804-L-bw-vd Fels 537804-L-bw-vd Fels Processed on: 3-12-2019 Processed on: 3-12-2019 Processed on: 3-12-2019

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Movement, cognition and

underlying brain functioning

in children

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The studies described in this thesis have been conducted at the Center for Human Movement Sciences, part of the University Medical Center Groningen and the University of Groningen, the Netherlands and at the Vrije Universiteit Amsterdam, Clinical Neuropsychology Section, The Netherlands.

This study was financially supported by the Netherlands Initiative for Education Research (NRO), grant number 405-15-410, and the Dutch Brain Foundation, grant number GH 2015-3-01. PhD training was facilitated by the Research Institute Science in Healthy Ageing and healthcaRE (SHARE), part of the Graduate School for Medical Sciences.

Printing of this thesis was financially supported by: • University Medical Center Groningen • University of Groningen

• Research Institute SHARE • Jan Luiting Fonds

Cover design & layout Bianca Pijl, www.pijlldesign.nl

Groningen, the Netherlands

Printed by Ipskamp Printing

Enschede, the Netherlands

ISBN 978-94-034-2174-2 (print)

978-94-034-2173-5 (digital)

All rights reserved. No part of this thesis may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without prior written permission of the author, or when appropriate, of the publishers of the publications included in this thesis.

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3

Proefschrift

ter verkrijging van de graad van doctor aan de Rijksuniversiteit Groningen

op gezag van de

rector magnificus prof. dr. C. Wijmenga en volgens besluit van het College voor Promoties

De openbare verdediging zal plaatsvinden op maandag 27 januari 2020 om 12.45 uur

door

Irene Maria Joanne van der Fels geboren op 1 maart 1991

te Deventer

Movement, cognition and

underlying brain functioning

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4 Promotores Dr. E. Hartman Prof. dr. C. Visscher Prof. dr. R.J. Bosker Copromotor Dr. J. Smith Beoordelingscommissie Prof. dr. M. Chin A Paw Prof. dr. B. Steenbergen Prof. dr. L.H.V. van der Woude

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Paranimfen Christa van der Fels Danique Vlaskamp

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7 Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Chapter 6 Chapter 7 Chapter 8 Appendices Table of contents General introduction

The relationship between motor skills and cognitive skills

in 4-16-year-old typically developing children: A systematic review Relations between gross motor skills and executive functions, controlling for the role of information processing and lapses of attention in 8-10-year-old children

Relations between gross motor skills, cardiovascular fitness and visuospatial working memory-related brain activation in 8-10-year-old children

The acute effects of two physical activity types in physical education on response inhibition and lapses of attention in children aged 8-10 years: A cluster randomized controlled trial Effects of aerobic and cognitively engaging physical activity on cardiovascular fitness and gross motor skills in primary school children: A cluster randomized controlled trial

Differential effects of aerobic versus cognitively engaging physical activity on children’s visuospatial working memory-related brain activation: A cluster randomized controlled trial Summary and general discussion

References

Nederlandse samenvatting Dankwoord

Curriculum Vitae

Research Institute SHARE

9 21 55 75 99 123 141 175 189 207 209 215 219 223

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11 Relations between gross motor skills and cognitive functions

Gross motor skills

The childhood years are critical years for the development of gross motor skills1_{. Gross motor skills} represent abilities that involve large body muscles in posture, orientation and movement of the trunk and limbs and involve abilities such as locomotor skills, balancing and ball skills (Bishop, 2014). Children obtain gross motor skills during childhood through experience and practice, either in unstructured or structured situations, and this forms the foundation for more complex movements and sport-specifi c skills (Clark & Metcalfe, 2002). Therefore, profi ciency in gross motor skills is a strong predictor for a lifelong active lifestyle (Clark & Metcalfe, 2002; Seefeldt, Nadeau, Newell, & Roberts, 1980).

Gross motor skills are not only important for physical development, but also for the development of cognitive functions (e.g. Rigoli, Piek, Kane, & Oosterlaan, 2012a; Roebers & Kauer, 2009; Wassenberg et al., 2005). At a young age, a child is able to move through the environment, interacting with objects or other people, therefore exposed to opportunities to further develop gross motor skills, but also to learn and acquire knowledge (Bornstein, Hahn, & Suwalsky, 2013). Later in life, children play together in structured or unstructured physical activity requiring goal-oriented behavior and cognitive strategies, which supports the development of cognitive functions.

Cognitive functions

Cognitive functions encompass a set of mental processes that contribute to perception, memory, and action, and include, amongst others, executive functions, information processing, and attention. From a neuropsychological view, it is assumed that gross motor skills are particularly related to cognitive functions that require a high amount of cognitive control, e.g. executive functions (Tomporowski, Davis, Miller, & Naglieri, 2008). Executive functions are higher-order cognitive functions important for goal-directed behavior (Banich, 2009). Three core aspects of executive functions can be distinguished: inhibition (response inhibition and interference control), working memory (verbal and visuospatial), and cognitive ﬂ exibility (also called shifting; Miyake et al., 2000). These functions play a critical role in the development during childhood and are necessary for success throughout life in general (Best, Miller, & Jones, 2009; Diamond, 2013). Furthermore, executive functions are strongly related to academic achievement as the ability to inhibit automatic behavior and confl icting stimuli, updating of working memory, and shifting between diff erent tasks have shown to be related to reading, mathematics and spelling (Best, Miller, & Naglieri, 2011).

General introduction

1 _{Defi nitions of terms shown in italics can be found in Box 1.}

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The speed and variability with which information is processed (information processing) and the ability to maintain attention are cognitive functions that are important prerequisites for executive functioning. Information processing develops rapidly during childhood and improvements in information processing have been shown to be related to improvements in executive functions (Anderson, Anderson, Northam, Jacobs, & Catroppa, 2001; Christ, White, Mandernach, & Keys, 2001; Fry & Hale, 1996; Hale, 1990; Span, Ridderinkhof, & van der Molen, Maurits, 2004; Welsh, Pennington, & Groisser, 1991). Furthermore, short-term unavailability of attention, also known as lapses of attention, affects the speed and quality of executive functioning (Unsworth, Redick, Lakey, & Young, 2010). Information processing and attention have also shown to be related to gross motor skills in children, although this is mainly investigated in children with developmental disorders (Klotz, Johnson, Wu, Isaacs, & Gilbert, 2012; Niederer et al., 2011). Children with attention deficit/hyperactivity disorder (ADHD) or developmental coordination disorder (DCD) show both motor and cognitive deficits which are linked to attentional and information processing problems (Dewey, Kaplan, Crawford, & Wilson, 2002; Klimkeit, Sheppard, Lee, & Bradshaw, 2004). Furthermore, information processing and attention have shown to attenuate relations between gross motor skills and executive functions in typically developing children (Luz, Rodrigues, & Cordovil, 2015; Piek et al., 2004; Roebers & Kauer, 2009; Wassenberg et al., 2005), although these have not been investigated together. Therefore, further research is needed to investigate the influence of information processing and lapses of attention together in the relationship between gross motor skills and executive functions in typically developing children.

Neuropsychological pathways

Hypothesized relations between gross motor skills and executive functions can be explained at a brain level. Neuroimaging studies have shown that the prefrontal cortex is not only important for executive functions, but also plays an important role in skilled motor performance (Desmond, Gabrieli, Wagner, Ginier, & Glover, 1997; Diamond, 2000; Dum & Strick, 1991). Functions depending on the prefrontal cortex, such as holding information in mind, inhibiting actions when another behavior is more appropriate, resisting distraction, sequencing, monitoring and planning, are also important for motor performance (Desmond et al., 1997; Diamond, 2000). Furthermore, the prefrontal cortex is connected with brain regions that are more directly involved in motor skills, such as the premotor cortex and the supplementary motor area (Dum & Strick, 1991; Künzle, 1978; Tanji, 1994). Additionally, the cerebellum and basal ganglia, neuroanatomical structures important for the control of movements, have also shown to be involved in executive functions (Desmond et al., 1997; Diamond, 2000; Dum & Strick, 1991; Lou, Henriksen, Bruhn, Børner, & Nielsen, 1989). Therefore, the prefrontal cortex, motor cortices, the cerebellum and the basal ganglia appear to participate in neural circuitries that are important for both motor skills and executive functions and this gives support for an interrelation between the two domains. The proposed underlying functional brain mechanisms have not yet been investigated in children by linking brain activity during executive function tasks to motor skill performance, therefore leaving this theory untested.

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13 Physical activity and cognitive functioning

Physical activity is important for several health-related factors in children, such as gross motor skills and cardiovascular fi tness. Unfortunately, children have become less physically active and signifi cant declines in gross motor skills and cardiovascular fi tness have been shown since the 1980s (Runhaar et al., 2010; Timmermans et al., 2017; Tomkinson, Lang, & Tremblay, 2017). Therefore, there is a need for physical activity interventions that stimulate gross motor skills and cardiovascular fi tness.

Physical activity interventions are not only important to stimulate gross motor skills and cardiovascular fi tness, but can also be eff ective for the development of executive functions. The development of executive functions goes hand in hand with maturation of the brain (Stuss, 1992). Maturation of the brain occurs by progressive and regressive changes and this is partly driven by the child’s experience (O’Hare & Sowell, 2008). Physical activity seems to be such an experience that enhances maturation and could therefore subsequently stimulate the cognitive development (Best, 2010). Physical activity interventions can be distinguished into acute interventions and longitudinal interventions, and into aerobic interventions and cognitively engaging interventions, each relying on diff erent underlying mechanisms.

Acute physical activity interventions

Several meta-analyses and reviews have shown that one single bout of physical activity, e.g. an acute bout, can be benefi cial for cognitive functioning in children (Chang, Labban, Gapin, & Etnier, 2012; McMorris & Graydon, 2000; Tomporowski, 2003; Verburgh, Konigs, Scherder, & Oosterlaan, 2014). A recent meta-analysis by de Greeff , Bosker, Oosterlaan, Visscher, and Hartman (2018a) has shown that acute physical activity does not infl uence cognitive functions in general, but specifi c domains of cognitive functions are enhanced through acute physical activity in children. This meta-analysis showed that acute physical activity has a small to moderate eff ect on inhibition (Eff ect Size [ES] = 0.28, p = 0.042) and attention (ES = 0.43, p = 0.013), whereas there is no signifi cant eff ect on working memory and cognitive fl exibility.

The strongest positive eff ects of acute physical activity on attention and inhibition have been shown in laboratory settings, where the intensity is controlled and adjusted to the child’s individual level (e.g. Chen, Yan, Yin, Pan, & Chang, 2014; Hillman, Buck, Themanson, Pontifex, & Castelli, 2009; Niemann et al., 2013; Pontifex, Saliba, Raine, Picchietti, & Hillman, 2013; Tine & Butler, 2012). Positive eff ects of physical activity on attention and inhibition in ecologically valid learning environments for children, such as physical education, have also been found, but the eff ects were less pronounced (e.g. Jäger, Schmidt, Conzelmann, & Roebers, 2014). The eff ects were dependent on the test sequence (Pirrie & Lodewyk, 2012), were only found 90 minutes after the activity and not immediately (Schmidt, Egger, & Conzelmann, 2015a), or were only found after two bouts of activity, whereas not after one bout (Altenburg, Chinapaw, & Singh, 2016).

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Some studies have investigated the effects of different types of acute physical activity on inhibition and attention in children. Studies by Jäger, Schmidt, Conzelmann, and Roebers (2015) and Schmidt, Benzing, and Kamer (2016) showed no effect of either aerobic physical activity or cognitively engaging physical activity on inhibition and selective attention respectively. The study by Gallotta et al. (2015) found that cognitively engaging physical activity led to significantly less improvements on selective attention compared to aerobic physical activity. The study by Best (2012) showed that physical activity, independent of the type of activity, did enhance processing speed in an inhibition task. Thus, there is an inconsistency between studies regarding the effects of different types of physical activity, which may be due to difference in duration, types of activity, or outcome variables (de Greeff et al., 2018a). This highlights the importance of further examining the differential effects of acute aerobic and cognitively engaging physical activity in ecologically valid learning environments for children.

Longitudinal physical activity interventions

Studies on longitudinal aerobic interventions, varying from 15 weeks to nine months, performed five times per week during physical education or after school interventions have shown to enhance specific aspects of executive functioning. The meta-analysis by de Greeff et al. (2018a) showed that longitudinal physical activity did have a small to moderate effect on working memory (ES = 0.36, p = 0.007), a small effect on cognitive flexibility (ES = 0.18, p = 0.040) and a large effect on attention (ES = 0.90, p < 0.001). Longitudinal physical activity had no significant effect on inhibition. Regarding the type of physical activity, a small to moderate effect was found for effects of aerobic physical activity on cognitive functions (ES = 0.29, p = 0.001) and a moderate to large effect was found for effects of cognitively engaging physical activity on cognitive functions (ES = 0.53, p = 0.008). These results suggest that longitudinal cognitively engaging physical activity is a promising type of physical activity to enhance cognitive functions. However, heterogeneity between the studies that were included in the meta-analysis was high and several factors influence the effectiveness of interventions, such as duration, intensity, frequency and type of intervention. Furthermore, there may be subgroups of children that benefit from physical activity interventions, whereas other subgroups do not (de Greeff et al., 2018a; Vazou, Pesce, Lakes, & Smiley-Oyen, 2016). Therefore, further research is needed to examine the effects of different types of physical activity and take into account individual characteristics of children.

Mechanisms underlying the effects of physical activity on cognitive functions

Several mechanisms have been proposed to explain the effects of physical activity on cognitive functions. The physiological mechanism and the cognitive stimulation hypothesis have been used as a framework for this thesis.

Physiological mechanism

The physiological mechanism is based on physiological changes in the body as a result of physical activity that subsequently lead to better cognitive functions (Sibley & Etnier, 2003). Acute physical activity is thought to lead to immediate changes in the brain, such as enhanced cerebral

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15 blood fl ow (Querido & Sheel, 2007), and triggers the upregulation of neurotransmitters that are important for cognitive functions (e.g. dopamine, epinephrine, norepinephrine; Dishman et al., 2006; McAuley, Kramer, & Colcombe, 2004). It is assumed that these neurophysiological changes lead to an increase in the level of arousal, which in turn leads to better cognitive performance. This mechanism has been investigated with brain studies. Hillman et al. (2009) and Pontifex et al. (2013) investigated the eff ects of 20 minutes of acute aerobic physical activity on a treadmill on brain functioning and cognitive functions in children. The P3 amplitude increased after aerobic physical activity, which is likely to represent the allocation of attention (Polich, 1987), and this was related to better cognitive functions, supporting evidence for the physiological arousal mechanism.

In the long-term, the up-regulation of neurotransmitters is thought to lead to neurogenesis and angiogenesis in brain areas that are important for cognitive functions, which subsequently leads to better cognitive performance (Cotman, Berchtold, & Christie, 2007; Dishman et al., 2006; Holmes, Galea, Mistlberger, & Kempermann, 2004; Van Praag, 2008). There are a few studies that have investigated the eff ects of longitudinal physical activity on functional and structural changes in the brain in children. Higher white matter integrity in the uncinate fasciculus (Schaeff er et al., 2014) and in the superior longitudinal fasciculus (Kraff t et al., 2014), which are white matter pathways between brain areas that are important for executive functions, has been found as a result of physical activity in overweight children. Functional brain studies showed a decrease in brain activation in the inferior frontal gyrus, the anterior cingulate cortex (Kraff t et al., 2014), and in the parietal cortex (Davis et al., 2011a) during executive function tasks, whereas an increase in brain activation was shown in the prefrontal cortex (Davis et al., 2011a) after longitudinal aerobic interventions in overweight children. Only one study linked the changes in brain activation to cognitive functioning and found that a decrease in activation in the anterior prefrontal cortex was related to better executive functioning in typically developing children (Chaddock-Heyman et al., 2013). As eff ects of physical activity on the brain have been mainly studied in overweight children, further research is needed to examine the eff ects of physical activity on the brain in typically developing children.

Cognitive stimulation hypothesis

Many forms of physical activity are cognitively engaging. For example, team games require cooperation between children, strategic play and anticipation of teammates and opponents and this recruits similar processes as executive function tasks (Best, 2010). Furthermore, the cognitive demands inherent in the coordination of motor tasks lead to the involvement of neural circuitries that are also important for cognitive functions (Diamond, 2000; Serrien, Ivry, & Swinnen, 2007). Therefore, it can be hypothesized that physical activity that is cognitively demanding, either by the demands inherent in games or by the demands inherent in the coordination of complex motor tasks, would lead to larger eff ects on cognitive functions than aerobic physical activity alone (Schmidt, Jäger, Egger, Roebers, & Conzelmann, 2015b).

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The cognitive stimulation hypothesis has been investigated in a study with rats. It was found that physical activity in an engaging context leads to angiogenesis in both the hippocampus and the prefrontal cortex, whereas simple and repetitive physical activity only leads to angiogenesis in the hippocampus (Ekstrand, Hellsten, & Tingström, 2008). Only one study examined the differential effects of aerobic physical activity and cognitively engaging physical activity on the brain in humans, but this was investigated in older adults (Voelcker- Rehage & Niemann, 2013). It was found that both interventions lead to decreased activation in the prefrontal cortex and also to improved executive functioning. Differential effects of different types of physical activity were also shown; the aerobic intervention group showed decreased activation in the sensorimotor network, while the coordination group showed increased activation in the visuospatial network and the thalamus and caudate body (both important subcortical structures for process automatization). These studies showed that different types of physical activity may lead to differential effects on the brain. However, this needs to be further examined in children.

Objectives and outline of this thesis

The first aim of this thesis is to investigate relationships between gross motor skills and specific aspects of cognitive functions in children and the proposed brain mechanisms underlying relations between gross motor skills and executive functions. The second aim of this thesis is to explore the differential effects of acute aerobic and cognitively engaging physical activity on response inhibition and attention. Third, the effects of longitudinal aerobic and cognitively engaging physical activity on cardiovascular fitness, gross motor skills, visuospatial working memory, and underlying brain functioning will be examined.

This thesis is part of a larger project, “Learning by Moving”, which is a cluster randomized controlled trial (RCT) investigating the effects of aerobic physical activity and cognitively engaging physical activity on cardiovascular fitness, gross motor skills, cognitive functions, academic achievement, brain structure, and brain functioning. Participants in this project were 8-10-year-old children (n = 891) from 22 primary schools (grades three and four) in the Netherlands. Two 14-week longitudinal interventions were developed and delivered. The aerobic intervention contained activities performed at a moderate-to-vigorous intensity. The cognitively engaging intervention consisted of team games or exercises that require complex coordination of movements, strategic play, cooperation between children and anticipating the behavior of teammates or opponents. The interventions were implemented four times per week by specialist teachers during regular physical education lessons and during two additional physical education lessons. The control group followed the regular physical education lessons two times per week. Children’s cardiovascular fitness, gross motor skills, cognitive functions, academic achievement, brain structure and brain functioning were measured at baseline and after the interventions. Baseline measures were used for the studies related to the first aim of this thesis (Chapters 3 and 4). Baseline and posttest measures were used for the studies related to the second and third aims of this thesis (Chapters 5 – 7). The effects on executive functions and academic achievement are the main focus of two other theses (executive functions: Meijer, in progress; academic achievement: de Bruijn, 2019).

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17 Chapter 2 contains a systematic review investigating relations between broad domains of motor skills and cognitive functions in 4-16-year-old typically developing children. It examines which specifi c domains of motor skills and cognitive functions are related and whether these relations change over age categories. The results of this review contribute to the understanding of specifi c relations between motor skills and cognitive functions in children.

The aim of Chapter 3 is to investigate the relation between gross motor skills and specifi c aspects of executive functions, namely verbal working memory, visuospatial working memory, response inhibition and interference control. Furthermore, the role of information processing and lapses of attention is examined. Baseline scores of the children in the “Learning by Moving” project (n = 891) on gross motor skills and cognitive functioning are used for this study. The results contribute to the understanding of relations between gross motor skills and specifi c domains of executive functions in 8-10-year-old children and the role of information processing and lapses of attention in these relations.

Chapter 42_{investigates visuospatial working memory-related brain activity with functional} Magnetic Resonance Imaging (fMRI). Additionally, it is examined whether brain activity during visuospatial working memory is related to gross motor skills and cardiovascular fi tness. A subsample of 92 children from the total sample in the “Learning by Moving“ project participated in an MRI protocol in which brain activation during a visuospatial working memory task was measured. This study contributes to insights into the mechanisms underlying the relations of gross motor skills and cardiovascular fi tness with visuospatial working memory in 8-10-year-old children.

Chapter 5 studies the eff ects of an acute aerobic intervention and an acute cognitively engaging intervention on response inhibition and lapses of attention. A subsample of 89 children from the total sample in the “Learning by Moving“ project participated in this study. Children in the intervention group followed either an acute aerobic physical education lesson or an acute cognitively engaging physical education lesson. Heart rate was monitored during the intervention lessons with Polar heart rate monitors. Children in the control condition followed a seated academic classroom lesson with their own teacher. This study contributes to insights into the diff erential eff ects of acute aerobic and cognitively engaging physical activity, performed in ecologically valid learning environments, on inhibition and attention, two aspects of cognitive functions that have shown to benefi t most from acute physical activity.

The aim of Chapter 6 is to study the eff ects of a longitudinal aerobic and cognitively engaging intervention on gross motor skills and cardiovascular fi tness. Furthermore, it is investigated whether eff ects depend on baseline levels of gross motor skills and cardiovascular fi tness and the

2 _{Chapters 4 and 7 have shared fi rst authorship with A.G.M. de Bruijn and appear therefore also in the thesis by de}

Bruijn (The brain in motion, 2019). Both authors have equally contributed to these chapters.

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dose of moderate-to-vigorous physical activity (MVPA). Children (n = 891) were assigned to the aerobic intervention group, the cognitively engaging intervention group, or the control condition in a Cluster RCT design. Children in the intervention groups (either aerobic or cognitively engaging physical activity) followed four physical education lessons per week for 14 weeks. Children in the control group followed their regular physical education lessons two times per week. The amount of MVPA during the physical education lessons was measured with accelerometers in all study conditions. The results of this study contribute to insights into the differential effects of two types of physical activity on gross motor skills and cardiovascular fitness. The results will also lead to insights into individual characteristics that are important to take into account for the development and delivering of physical activity interventions.

Chapter 72_{investigates the effects of the longitudinal aerobic and cognitively engaging physical} activity interventions on visuospatial working memory-related brain activation with fMRI in children (n = 92). Brain activation before and after the intervention period are compared for three study conditions (the control group, the aerobic intervention group and the cognitively engaging intervention group). Insights into the brain mechanisms underlying the effects of different types of physical activity on cognitive functions will be obtained with this study.

Finally, Chapter 8 presents a summary of the most important results of this thesis and provides a discussion in light of existing knowledge and the theories described in this introduction. Additionally, limitations are discussed and practical implications and suggestions for further research are given.

2 _{Chapters 4 and 7 have shared first authorship with A.G.M. de Bruijn and appear therefore also in the thesis by de}

Bruijn (The brain in motion, 2019). Both authors have equally contributed to these chapters.

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General introduction

Box 1. Defi nitions

Acute physical activity. One single bout of physical activity.

Aerobic physical activity. Physical activity to improve cardiovascular fi tness. Angiogenesis. The growth of new blood vessels linked to neurogenesis (Best, 2010).

Attention. A cognitive state of focused awareness on a selection of available perceptual information (Gerrig & Zimbardo, 2002).

Cardiovascular ﬁ tness. The ability of the circulatory and respiratory systems to supply oxygen during sustained physical activity (Corbin, Pangrazi, & Franks, 2000).

Cognitive engagement. The amount of cognitive eff ort and allocated attention that is needed for a certain activity, or to master certain skills (Tomporowski, McCullick, & Pesce, 2015a).

Cognitive ﬂ exibility. The ability to alternate attention between two simultaneous goals (Arbuthnott & Frank, 2000).

Cognitive functions. A set of mental processes that contribute to perception, memory, and action which include, amongst others, attention and executive functioning (Donnelly et al., 2016). Executive functions. A subset of inter-related processes that are involved in purposeful, goal-directed behavior, such as inhibition and working memory (Banich, 2009).

Gross motor skills. The involvement of large body muscles in balance, limbs and trunk movements (Bishop, 2014).

Information processing. The effi ciency (speed and variability) with which information is processed (Kail & Salthouse, 1994).

Inhibition. The ability to deliberately suppress dominant, automatic, or prepotent responses and confl icting stimuli (Nigg, 2000; Verbruggen & Logan, 2008).

Interference control. The ability to cognitively suppress confl icting stimuli (Nigg, 2000). Longitudinal physical activity. Continuous physical activity over several weeks.

Neurogenesis. The process of proliferation and development of new neurons (Churchill et al., 2002). Physical activity. All bodily movements produced by skeletal muscles that result in energy expenditure (Ortega, Ruiz, Castillo, & Sjöström, 2008).

Response inhibition. The ability to suppress planned actions that are no longer required or appropriate (Verbruggen & Logan, 2008).

Selective attention. The ability to complete a task without being distracted by other stimuli that are being presented (Janssen et al., 2014).

Working memory. The ability to store and manipulate information in short-term memory, whereby specialized processes exist for verbal and visual information (Baddeley & Hitch, 1994).

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2

The relationship between motor skills and

cognitive skills in 4-16-year-old typically

developing children: A systematic review

Irene M.J. van der Felsa_{, Sanne C.M. te Wierike}a_{, Esther Hartman}a_, Marije T. Elferink-Gemsera,b_{, Joanne Smith}a_{, Chris Visscher}a a_{University of Groningen, University Medical Center Groningen,}

Center for Human Movement Sciences, The Netherlands b_{Institute for Studies in Sports and Exercise,} HAN University of Applied Sciences, The Netherlands

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22 Abstract Objectives

This review aims to give an overview of studies providing evidence for a relationship between motor and cognitive skills in typically developing children.

Design

A systematic review. Methods

PubMed, Web of Science, and PsychINFO were searched for relevant articles. A total of 21 articles were included in this study. Methodological quality was independently assessed by two reviewers. Motor and cognitive skills were divided into six categories.

Results

There was either no correlation in the literature, or insufficient evidence for or against many correlations between motor skills and cognitive skills. However, weak-to-strong evidence was found for some correlations between underlying categories of motor skills and cognitive skills, including complex motor skills and higher-order cognitive skills. Furthermore, a stronger relationship between underlying categories of motor and cognitive skills was found in prepubertal children compared to pubertal children (older than 13 years).

Conclusions

Weak-to-strong relations were found between some motor and cognitive skills. The results suggest that complex motor intervention programs can be used to stimulate both motor and higher-order cognitive skills in prepubertal children.

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23 Introduction

Historically, there have been diff erent views about the relationship between motor skills and cognitive skills in children. On the one hand, motor and cognitive skills have been considered as entirely diff erent processes, developing independently, and involving diff erent brain regions (Hertzberg, 1929). On the other hand, Piaget (1952) considered that motor and cognitive skills are closely related. Piaget’s theory was based on the idea that children learn from observable motor actions with objects. There are several explanations for a possible relationship between motor and cognitive skills in children. First, research has shown co- activations between the prefrontal cortex, the cerebellum, and the basal ganglia during several motor and cognitive tasks, especially when a task is diffi cult, a task is new, conditions of a task change, a quick response is required, and concentration is needed to perform a task (Desmond, Gabrieli, Wagner, Ginier, & Glover, 1997; Diamond, 2000). A second explanation for a relationship between motor and cognitive skills is that they might have a similar developmental timetable with an accelerated development between the ages of 5 and 10 years (Anderson, Anderson, Northam, Jacobs, & Catroppa, 2001). Third, both motor and cognitive skills have several common underlying processes, such as sequencing, monitoring, and planning (Roebers & Kauer, 2009). These possible explanations highlight a need to explore how motor skills relate with cognitive skills and whether the link is specifi c to certain categories of skill.

Motor and cognitive skills are broad concepts and have been defi ned in a number of diff erent ways. In the current review, motor skills are defi ned as learned sequences of movements that are combined to produce a smooth, effi cient action in order to master a particular task (Davis, Pitchford, & Limback, 2011b). Diff erent categories of motor skills are distinguished: (1) Gross motor skills, this includes skills like jumping, sprinting, and walking. Furthermore, all underlying physical abilities like strength, agility, fl exibility, and balance, that are needed to perform a task are included in this category; (2) Fine motor skills, which are tasks where fi ne motor precision and integration are needed (Davis, Pitchford, Jaspan, McArthur, & Walker, 2010); (3) Bilateral body coordination, this includes whole body coordination tasks and demands engagement of almost all body parts and bilateral motor coordination of lower and upper extremities (Planinšec & Pišot, 2006); (4) Timed performance in movements, these are tasks (gross/fi ne motor skills or object control tasks) in which the time a child takes to perform a required number of movements is important and are often divided into repetitive movements and sequenced movements (Jenni, Chaouch, Cafl isch, & Rousson, 2013). Repetitive movements are simple movements that are repeated as quickly as possible (Martin, Tigera, Denckla, & Mahone, 2010). Sequenced movements include alternating patterns of more complex movements performed as quickly as possible (Martin et al., 2010); (5) In the category object control, skills are included in which an object has to be controlled, such as ball skills; Finally, (6) Total motor score, which is described as the sum score of a combination of motor skills out of the fi ve other categories. It is worth to note that the categories are not exclusive and as such, motor skills from one category may contain elements of other categories.

A systematic review

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24

Cognitive skills are understood as the mental actions or processes of acquiring knowledge and understanding through thought, experience, and the senses (Davis et al., 2011b). Different aspects of cognitive skills are included in this review, based on the skills used in literature. Executive functions are described as higher-order cognitive skills that enable self-control and include the following metacognitive skills: response inhibition, which is described as the suppression of actions that are no longer required or that are inappropriate; planning, which is described as a plan that can be represented as a hierarchy of sub goals, each requiring actions to achieve the goal; attention, which is described as the ability to attend to some things while ignoring others; and working memory, which is described as the ability to store and manipulate information over a period of seconds to minutes (Gazzaniga, 2009). Visual processing is described as a path that information takes from visual sensors to cognitive processing (Boden & Giaschi, 2007). Short-term memory is described as the capacity to hold information in mind in the absence of external stimulation over a short period of time (Nee & Jonides, 2013). Information retained for a significant time is referred to as long-term memory (Gazzaniga, 2009). Fluid intelligence is the ability to think logically and solve problems in novel situations; this is independent of acquired knowledge (Cattell, 1971). Crystallized intelligence refers to the capacity to use skills, knowledge, and experience by accessing information from long-term memory (Cattell, 1971). Intelligence quotient (IQ) is a measure to calculate a person’s intelligence. Academic skills are skills developed or measured in educational settings.

Recent literature has reviewed relationships between motor and cognitive skills in children with DCD and children born preterm (Jongbloed-Pereboom, Janssen, Steenbergen, & Nijhuis- van der Sanden, 2012; Wilson, Ruddock, Smits-Engelsman, Polatajko, & Blank, 2013). Wilson et al. (2013) suggested a relationship between impaired motor skills like rhythmic coordination, gait and postural control, catching and interceptive action and impaired cognitive skills like internal (forward) modeling, executive function, and aspects of sensoriperceptual function in children with DCD. Jongbloed-Pereboom et al. (2012) found that information regarding the relationship between different components of motor learning and working memory in children born preterm was not available in literature. However, we are not aware of any reviews that focus on the relationship between motor skills and cognitive skills in typically developing children. Therefore, the present review aims to give an overview of studies providing evidence for a relationship between motor and cognitive skills in typically developing children. If there are indications for relationships between components of motor and cognitive skills, programs focusing on one domain could be designed to optimize performance of both motor and cognitive skills in typically developing children.

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25 Methods

The databases used for the literature search were PubMed, Web of Science, and PsycINFO; they were searched for records that contained one of the following combinations of terms ([1 AND 2] OR 3):

Motor skills (OR motor skill competency OR motor performance OR motor coordination OR motor function OR motor development OR motor abilities OR motor control OR motor examination OR motor milestones OR motor behavior OR fi ne motor skills OR gross motor skills OR postural control OR movement assessment battery OR fi ne and gross motor development) OR test of gross motor development.

Cognitive skills (OR cognitive performance OR cognitive function OR cognitive abilities OR cognitive behavior OR cognitive control OR cognitive processes OR cognition) OR intelligence (OR IQ) OR academic achievement (OR kindergarten achievement) OR language development OR executive functions (OR memory OR working memory OR attention).

Cognitive-motor structures (OR cognitive predictors of motor functions OR motor and cognitive dimensions OR executive function, motor performance and externalizing behavior). Inclusion criteria for this review were that the studies were (1) published between 2000 and 2013, (2) written in English, (3) focused on children aged 4–16-year-old, (4) reporting a correlation, regression analysis, or factor structure between motor skills and cognitive skills, and (5) original articles. The age range was chosen, because motor functioning as well as executive functions show an accelerated development between 5 and 10 years with a continued development into adolescence (Anderson et al., 2001). The limited range of literature between 2000 and 2013 was selected, because it gives an overview of the most recent literature on the relationship between motor and cognitive skills, without constraining the broad defi nitions of motor and cognitive skills.

Exclusion criteria for this review were (1) studies with special populations (e.g. children with developmental disorders, brain injuries, adoptees, children born preterm, children with gifted performance), and (2) intervention studies.

The stages adopted in the systematic search resulted in 21 relevant articles being identifi ed for further analysis (Figure 1).

1.

2.

3.

A systematic review

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26

Figure 1. Stages adopted in the selection of articles. a_{Based on inclusion criteria 1, 2, and 5 and the search was}

based on title; b_{Based on inclusion criterion 1, 2, and 3 (child: birth – 18 years);}c_{Based on inclusion criterion 1, 2,}

and 3 (childhood, preschool age, school age, adolescence) and the search was based on title; d_{We asked several}

principal investigators in the fi eld for suggestions to prevent missing key publications not included by searching electronic databases.

Chapter 2

Articles located based on literature search

Based on inclusion criteria 1 and 2 n = 774

Web of Sciencea _{n = 536}

PubMedb _{n = 229}

PsycINFOc _{n = 9}

Analysis based on reading titles (n = 750)

Analysis based on reading abstract (n = 86)

Analysis based on reading full text (n = 24)

Articles selected from electronic databases as described above (n = 18)

Articles included in the review (n = 18 + 3 = 21)

Exclusion of duplicate studies (n = 24)

Exclusion after reading titles n = 664 Based on exclusion criterion 1 n = 364 Based on inclusion criterion 5 n = 170 Based on inclusion criterion 3 n = 96 Based on exclusion criterion 2 n = 27 Based on inclusion criterion 4 n = 7

Exclusion after reading abstract n = 62 Based on inclusion criterion 5 n = 28 Based on inclusion criterion 3 n = 13 Based on inclusion criterion 4 n = 11 Based on exclusion criterion 1 n = 8 Based on exclusion criterion 2 n = 2

Exclusion after reading full text n = 6 Based on inclusion criterion 3 n = 5 Based on exclusion criterion 1 n = 1

Articles suggested by principal investigators in the fieldd_{(n = 3)}

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27 The included articles were evaluated for methodological quality according to the guidelines by Law et al. (1998). This method evaluated each article using the following main categories: study purpose, literature background, study design, sample, outcomes, intervention, results, conclusions and clinical implications. The methodological quality was assessed using 14 questions (see footnote Table 1). These questions were scored as either 1 (met the criteria) or 0 (did not meet the criteria). The scores on the 14 questions were summed for each article. For question fi ve, articles only met the criteria when the sample size was at least 100 (Hair, Black, Babin, Anderson, & Tatham, 2006). For questions seven and eight, articles only met the criteria when all the assessment tools were reliable or valid. A total score below seven was considered as low methodological quality, a score between seven and ten points was considered as good methodological quality and 11 points or higher was considered as high methodological quality. Two reviewers independently assessed the methodological quality of the studies. Diff erent scores were discussed and consensus was reached in all cases. Table 1 shows the methodological quality of the reviewed studies.

A systematic review

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28

Table 1. Methodological quality of the reviewed studiesa

Note. a_{1 = meet criteria; 0 = does not meet criteria;}b_{1) Was the study purpose stated clearly? 2) Was relevant}

background literature reviewed? 3) Was the design appropriate for the research question? 4) Was the sample described in detail? 5) Was sample size justified? 6) Was informed consent obtained? 7) Were the outcome measures reliable? 8) Were the outcome measures valid? 9) Were results reported in terms of statistical significance? 10) Were the analysis methods appropriate? 11) Was clinical importance reported? 12) Were conclusions appropriate given the study methods? 13) Are there any implications for clinical practice given the results of the study? 14) Were limitations of the study acknowledged and described by the authors?

Chapter 2

Table 1. Methodological quality of the reviewed studiesa_. Question numberb 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Total 1 1 1 1 1 0 1 1 1 1 0 1 1 1 12 1 1 1 0 0 0 0 0 1 1 0 1 0 0 6 1 1 1 1 1 1 1 1 1 1 1 1 1 1 14 1 1 1 1 1 1 1 1 1 1 1 1 1 1 14 1 1 1 0 1 0 1 1 1 1 1 1 1 0 11 1 1 1 1 1 1 0 0 1 1 0 1 0 1 10 1 1 1 1 1 0 0 0 1 1 0 1 0 0 8 1 0 1 1 1 1 1 1 1 1 1 1 0 0 11 1 1 1 1 0 1 1 0 1 1 0 1 0 0 9 1 1 1 1 1 1 1 1 1 1 0 1 1 1 13 1 1 1 1 1 1 1 1 1 1 0 1 1 1 13 1 1 1 1 1 0 1 1 1 1 1 1 1 0 12 1 1 1 1 1 0 1 1 1 1 0 1 1 1 12 1 1 1 1 1 0 1 1 1 1 0 1 0 0 10 1 1 1 1 1 0 1 1 1 1 0 1 0 0 10 1 1 1 1 1 1 1 1 1 1 0 1 0 0 11 1 1 1 1 0 1 1 1 1 1 1 1 1 1 13 1 1 1 1 0 1 1 1 1 1 0 1 1 1 12 1 1 1 1 1 1 0 0 1 1 1 1 1 1 12 1 1 1 1 1 1 1 1 1 1 1 1 1 1 14 Cameron et al. (2012) Castelli et al. (2006) Davis et al. (2010) Davis et al. (2011b) Decker et al. (2011) Jenni et al. (2013) Katic and Bala (2012) Kovač and Strel (2000) Livesey et al. (2006) Martin et al. (2010) Morales et al. (2011) Nourbakhsh (2006) Pangelinan et al. (2011) Planinsec (2002a) Planinsec (2002b) Planinsec and Pisot (2006) Rigoli et al. (2012a) Rigoli et al. (2012b) Roebers and Kauer (2009) Smits-Engelsman and Hill (2012)

Wassenberg et al. (2005) 1 1 1 1 1 0 1 1 1 1 0 1 0 0 10

Note. a_{1 = meet criteria; 0 = does not meet criteria;}b_{1) Was the study purpose stated clearly? 2) Was}

relevant background literature reviewed? 3) Was the design appropriate for the research question? 4) Was the sample described in detail? 5) Was sample size justiﬁed? 6) Was informed consent obtained? 7) Were the outcome measures reliable? 8) Were the outcome measures valid? 9) Were results reported in terms of statistical signiﬁcance? 10) Were the analysis methods appropriate? 11) Was clinical importance reported? 12) Were conclusions appropriate given the study methods? 13) Are there any implications for clinical practice given the results of the study? 14) Were limitations of the study acknowledged and described by the authors?

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29 To interpret levels of evidence, the following regulations were used (Berghmans et al., 2000; de Croon et al., 2004):

To state that there is strong evidence for or against a relationship between motor and cognitive skills, at least three high methodological quality studies with consistent results for this relationship were needed, or more than four studies of which more than 66% found consistent results and no more than 25% found an opposite result.

To state there is weak evidence for or against a relationship between motor and cognitive skills, three studies of which two are in agreement and the third which is not in agreement, or at least three low or good quality studies with consistent positive results for or against the relationship were needed.

There was insuffi cient evidence for a correlation between motor and cognitive skills when there were low or moderate quality studies with inconsistent results or with fewer than three studies of whatever quality.

There was no evidence for a correlation between motor and cognitive skills when there was only one study available.

Motor skills were divided into the following six categories: gross motor skills, fi ne motor skills, bilateral body coordination, timed performance in movements, object control, and total motor score. Motor skills from one category might contain elements of other categories, since the categories are not exclusive. When this was the case, these skills were classifi ed in the category where they fi tted the best according to the original article. Most of the studies reported correlations between motor skills and cognitive skills. Correlations lower than 0.3 were considered as weak, correlations between 0.3 and 0.5 were considered as moderate, and correlations above 0.5 were considered as strong (Cohen, 1988; Field, 2009).

Results

Appendix 2.1 shows the authors, number of participants, motor and cognitive skills, and the results of each of the 21 studies according to their category. All correlations (positive and negative) indicated that better performance in motor skills is related to better performance in cognitive skills. It is worth noting that sometimes lower scores in one test indicated better performance (the test had to be performed in less time) while in the other test, higher scores indicated better performance. The correlation between two tests can thus be negative, even though it indicates that better performance in one test is related to better performance in the other test. Some of the included articles studied diff erent categories of motor skills, so they were included in more than one category. Table 2 provides a summary of the results section, including the relationships investigated and strength of evidence for or against relationships.

1. 2. 3. 4. A systematic review

2

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30 Table 2. Summar y of the r esults section Table 2. Summary of the result section. Motor skill Cognitive skill No correlation Weak correlation

Moderate correlation Strong correlation

Evidence

Gross motor skills

Executive

functions

Strong (no correlation)

Visual processing Davis et al. (2010) a Davis et al. (2011b) a Insufficient Short-term memory Insufficient Long-term memory

Insufficient Strong (no correlation) Weak

(weak) Insufficient Rigoli et al. (2012b) c Roebers & Kauer (2009) Davis et al. (2010) a Davis et al. (2011b) a Davis et al. (2010) a Davis et al. (2011b) a Davis et al. (2010) a Davis et al. (2010) a Davis et al. (2011b) a Insufficient No Fluid intelligence

Crystallized intelligence IQ Academic skills General

knowledge

Visuospatial

working

memory

Livesey et al. (2006) Rigoli et al. (2012a)

c

Roebers & Kauer (2009) Davis et

al. (2011b) a Kovac & Strel (2000) Planinsec (2002 a) Planinsec (2002 b) Cameron et al. (2012) No

Jenni et al. (2013) Rigoli et al. (2012b)

b

Cameron et al. (2012) Rigoli et al. (2012b)

b

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31 Insufficient Cameron et al. (2012)

Weak (no correlation)

Rigoli et al. (2012a) b Rigoli et al. (2012b) b Rigoli et al. (2012a) b Rigoli et al. (2012b) b

Rigoli et al. (2012a)

b

No No

Fine motor skills Weak (weak- moderate)

Davis et al. (2010) a,c Davis et al. (2011b) a,c

Insufficient Weak (weak- moderate)

Davis et al. (2010) a,c Davis et al. (2011b) a,c Insufficient Davis et al. (2010) a,c Davis et al. (2011b) a,c

Strong (moderate- strong) No

Working

memory

Verbal comprehension Attention Cognitive

capacity to encode and analyze information Short-term memory

Long-term memory Fluid

intelligence Crystallized intelligence Visual processing General knowledge Academic skills Rigoli et al. (2012b) b Katic & Bala (2012) Davis et al. (2011b) a,c Davis et al. (2010) a,c Davis et al. (2011b) a,c Davis et al. (2010) a,c Cameron et al. (2012) Cameron et al. (2012) Cameron et al. (2012) c Davis et al. (2010) a Davis et al. (2011b) a,c Davis et al. (2010) a,c Davis et al. (2011b) a Davis et al. (2010) a,c Davis et al. (2011b) a,c Davis et al. (2010) a,c Davis et al. (2011b) a,c Cameron et al. (2012) c Morales et al. (2011) Insufficient

2

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32 Insufficient No Rigoli et al. (2012b) b Rigoli et al. (2012b) b Rigoli et al. (2012b) b No Livesey et al. (2006) Insufficient

b

No

Bilateral body coordination

Roebers & Kauer (2009)

No Davis et al. (2010) a Davis et al. (2011b) a

Insufficient Insufficient Insufficient

Planinsec (2002b) c Planinsec & Pisot (2006) c Davis et al. (2010) a Davis et al. (2011b) a Planinsec (2002a) b

Strong (weak- moderate correlation) No

Verbal comprehension Working memory Visuospatial working

memory Executive functions Attention Executive functions Visual

processing Short-term memory Long-term memory Fluid intelligence

Academic skills Cognitive capacity

to encode and analyze information Katic & Bala (2012) p Cameron et al. (2012) Rigoli et al. (2012a) b Davis et al. (2010) a Davis et al. (2011b) a Davis et al. (2010) a Davis et al. (2011b) a Kovac & Strel (2000) Planinsec (2002a) g Planinsec (2002b) c Planinsec & Pisot (2006) c Nourbakhsh (2006) Katic & Bala (2012) pp No

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33 Crystallized intelligence Davis et al. (2010) a Davis et al. (2011b) a Insufficient

Timed performance in movements

Executive

functions

Roebers & Kauer (2009)

No IQ Jenni et al. (2013) c

Weak (weak- moderate)

Planinsec (2002a)

m,c

Weak (weak- moderate) No

Object control Jenni et al. (2013) c Kovac & Strel (2000) p Planinsec (2002b) Pangelinan et al. (2001) Livesey et al. (2006) Rigoli et al. (2012a) b Castelli et al. (2006) Insufficient Weak (weak) Fluid intelligence Spatial working memory

Executive functions Fluid

intelligence Working memory Jenni et al. (2013) c Martin et al. (2010) Pangelinan et al. (2001) Kovac & Strel (2000) pp Planinsec (2002a) f Planinsec (2002a) m,c Decker et al. (2011)

Planinsec (2002a) Planinsec &

Pisot (2006) Decker et al. (2011) Rigoli et al. (2012a) b Rigoli et al. (2012b) b Weak (weak)

2

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34 Not e. aStudies b y D avis et al . (2010; 2011b) r epor

ting on the same sample siz

e; bStudies b y R igoli et al . (2012a; 2012b) r epor

ting on the same sample siz

e; cStudies used differ ent underlying aspects of mot or sk ills and found differ ent results; fFemale par ticipants; mMale par ticipants; ppPr epuber tal childr en (<13 years); pPuber tal childr en (>13 y ears).

Strong (weak) Insufficient

Morales et

al. (2011)

pp

Strong (weak- moderate) No No No

Total motor score Davis et al. (2011b)

a

No Weak (no correlation) No Insufficient No

Hill

(2012)

Smits-Engelsman

&

No

Decker et al. (2011) Rigoli et al. (2012a)

b Rigoli et al. (2012b) b Rigoli et al. (2012b) b

Decker et al. (2011) Decker et al. (2011) Rigoli

et al. (2012a) b Wassenberg et al. (2005) Wassenberg et al. (2005) No Visuospatial working memory Verbal comprehension

Academic skills Attention Knowledge Quantitative

reasoning

Total

cognitive score

Executive functions Attention Working

memory Verbal comprehension IQ Visual motor integration Visual processing

b Rigoli et al. (2012b) b Morales et al. (2011) p Rigoli et al. (2012a) b Livesey et al. (2006) Wassenberg et al. (2005) Rigoli et al. (2012a) b Rigoli et al. (2012a) b Rigoli et al. (2012a) b Wassenberg et al. (2005) No

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35 Twelve articles were included in the category gross motor skills (Cameron et al., 2012; Davis et al., 2010; Davis et al., 2011b; Jenni et al., 2013; Katic & Bala, 2012; Kovač & Strel, 2000; Livesey, Keen, Rouse, & White, 2006; Planinsec, 2002a; Planinsec, 2002b; Rigoli, Piek, Kane, & Oosterlaan, 2012a; Rigoli, Piek, Kane, & Oosterlaan, 2012b; Roebers & Kauer, 2009). Five articles had good methodological quality and seven articles had high methodological quality. Appendix 2.1 and Table 2 show strong evidence for no correlation between gross motor skills and both executive functions and fl uid intelligence (Davis et al., 2010; Davis et al., 2011b; Kovač & Strel, 2000; Livesey et al., 2006; Planinsec, 2002a; Planinsec, 2002b; Rigoli et al., 2012a; Rigoli et al., 2012b; Roebers & Kauer, 2009). There was weak evidence for no correlation between gross motor skills and verbal comprehension (Cameron et al., 2012; Rigoli et al., 2012a; Rigoli et al., 2012b). Weak evidence was found for a weak correlation between gross motor skills and crystallized intelligence (Cameron et al., 2012; Davis et al., 2010; Davis et al., 2011b). There was insuffi cient evidence for a correlation between gross motor skills and visual processing, short-term memory, long term memory, IQ, academic skills, and working memory (Cameron et al., 2012; Davis et al., 2010; Davis et al., 2011b; Jenni et al., 2013; Rigoli et al., 2012a; Rigoli et al., 2012b). There was no evidence for a correlation between gross motor skills and general knowledge, visuospatial working memory, attention, and cognitive capacity to encode and analyze (Cameron et al., 2012; Katic & Bala, 2012; Rigoli et al., 2012a; Rigoli et al., 2012b).

Seven articles were included in the category fi ne motor skills (Cameron et al., 2012; Davis et al., 2010; Davis et al., 2011b; Livesey et al., 2006; Morales, González, Guerra, Virgili, & Unnithan, 2011; Rigoli et al., 2012a; Rigoli et al., 2012b). One article had good methodological quality and six articles had high methodological quality. Appendix 2.1 and Table 2 show strong evidence for a moderate-to-strong correlation between fi ne motor skills and visual processing (Davis et al., 2010; Davis et al., 2011b). There was weak evidence for a weak-to-moderate correlation between fi ne motor skills and both short-term memory and fl uid intelligence (Davis et al., 2010; Davis et al., 2011b). There was insuffi cient evidence for a correlation between fi ne motor skills and executive functions, long-term memory, crystallized intelligence, academic skills, and verbal comprehension (Cameron et al., 2012; Davis et al., 2010; Davis et al., 2011b; Livesey et al., 2006; Morales et al., 2011; Rigoli et al., 2012b). No evidence was found for a correlation between fi ne motor skills and general knowledge, working memory, visuospatial working memory, and attention (Cameron et al., 2012; Rigoli et al., 2012a; Rigoli et al., 2012b; Roebers & Kauer, 2009).

Nine articles were included in the category bilateral body coordination (Davis et al., 2010; Davis et al., 2011b; Katic & Bala, 2012; Kovač & Strel, 2000; Nourbakhsh, 2006; Planinsec, 2002a; Planinšec & Pišot, 2006; Planinsec, 2002b; Roebers & Kauer, 2009). Three articles had good methodological quality and six articles had high methodological quality. Appendix 2.1 and Table 2 show strong evidence for a weak-to-moderate correlation between bilateral body coordination and fl uid intelligence (Davis et al., 2010; Davis et al., 2011b; Kovač & Strel, 2000; Planinsec, 2002a; Planinšec & Pišot, 2006; Planinsec, 2002b). There was insuffi cient evidence for a correlation between bilateral body coordination and visual processing, short-term memory, long-term memory, and crystallized intelligence (Davis et al., 2010; Davis et al., 2011b). There was no evidence for a relation

A systematic review