The Acute Effects of Aerobic Exercise on Cognitive Flexibility and Task-Related Heart Rate Variability in Children With ADHD and Healthy Controls

Abstract

Objective: To investigate cognitive flexibility and task-related heart rate variability following moderately intense aerobic exercise and after watching a video in both children with ADHD and healthy controls. Method: Using a cross-over design, participants completed cognitive assessments following exercise and a physically inactive control condition. Behavioral performance was assessed using the Alternate Uses task. Heart rate variability was recorded via electrocardiography during the cognitive task. Results: The statistical analysis revealed that in comparison with the control condition, both groups showed higher cognitive flexibility following aerobic exercise. Moreover, decreased low frequency and high frequency power was observed in the exercise condition. Conclusion: The findings suggest that exercise elicits similar benefits for cognitive flexibility in children with ADHD and healthy controls, partly due to an increase in arousal induced by parasympathetic withdrawal.

Keywords

alternate uses task executive function creativity autonomic nervous system physical activity

Introduction

With a worldwide prevalence rate of about 6%, ADHD is recognized as the most common neurodevelopmental disorder among children (Polanczyk, Willcutt, Salum, Kieling, & Rohde, 2014). According to the American Psychiatric Association (2013), this disorder is characterized by a developmentally inappropriate pattern of inattention and impulsiveness/hyperactivity, which is evident before children turn 12 years. These behavioral symptoms are accompanied by impairments in executive functions (Willcutt, Doyle, Nigg, Faraone, & Pennington, 2005) and other cognitive domains (Willcutt et al., 2005). Executive functions encompass top-down neurocognitive processes involved in conscious, goal-directed behavior and consist of the following three interrelated key components: inhibitory control, working memory, and cognitive flexibility (Diamond, 2013). From a neurophysiological point of view, ADHD-related deficits in this cognitive domain have been linked with a delayed structural maturation of the frontoparietal network (Rubia, Alegria, & Brinson, 2014) and its hypoactivation during cognitive load (Cortese et al., 2012). With regard to evidence-based medicine, meta-analytical findings have shown that regular administration of methylphenidate (MPH) elicits small to moderate improvements of executive functions in children and adolescents with ADHD (Tamminga, Reneman, Huizenga, & Geurts, 2016), but fails to normalize the recipients in the long-term (Shaw et al., 2012). Therefore, additional complementary methods or alternative interventions may be necessary to increase the efficiency of pharmacological treatment.

Among different interventions that enhance executive functions in children, physical activity has been attracting growing attention in recent years. In this respect, meta-analytical findings have shown that acute moderately intense aerobic exercise transiently benefits executive functions among healthy individuals (Ludyga, Gerber, Brand, Holsboer-Trachsler, & Pühse, 2016). Moderator analyses have further revealed that exercise sessions lasting 10 to 20 min elicit greater enhancements of cognitive performance than shorter or longer durations (Chang, Labban, Gapin, & Etnier, 2012). Although evidence on acute effects of exercise in children and adolescents with ADHD is limited, a single exercise session has been found to reduce the executive function deficits associated with this neurodevelopmental disorder (Grassmann, Alves, Santos-Galduróz, & Galduróz, 2017; Ludyga, Brand, Gerber, & Pühse, 2017a). Based on an investigation of individual differences in children, Drollette et al. (2014) further showed that low performers in executive function tasks can expect disproportionally higher benefits for executive function following aerobic exercise than high performers. Similar findings have been obtained in older adults (Sibley & Beilock, 2007), suggesting that individuals with deficits in executive function have a greater reserve for exercise-induced enhancements. As MPH does not necessarily normalize executive functions in children with ADHD (Swanson, Baler, & Volkow, 2011), they might as well have a greater capacity for improvements after a single exercise session than their healthy peers. To test this assumption, it is necessary to compare the acute effects of exercise between children with ADHD and healthy controls.

Whereas previous studies have focused on working memory and inhibitory control (Grassmann et al., 2017; Ludyga et al., 2016), acute effects of aerobic exercise on cognitive flexibility have largely been ignored in both children with ADHD and healthy controls (Ludyga et al., 2017a). Cognitive flexibility is generally understood as ability to adjust one’s behavior to changing task demands and allows a change of perspectives and thinking outside the box if needed (Diamond, 2013). Given that this executive function component predicts school readiness (Vitiello, Greenfield, Munis, & George, 2011) and social understanding (Bock, Gallaway, & Hund, 2014), it should be an important target for interventions in children. Despite the relevance of cognitive flexibility for academic skills (Blair & Razza, 2007), there is paucity of studies investigating acute effects of exercise on this core component of executive function. So far, a few experimental findings support improvements of cognitive flexibility following moderately intense aerobic exercise in children with ADHD (Chang, Liu, Yu, & Lee, 2012) and healthy controls (Chen, Yan, Yin, Pan, & Chang, 2014), whereas others have not reported any effect on this core component of executive functions (Jäger, Schmidt, Conzelmann, & Roebers, 2014). However, due to the small number of studies, it is premature to draw conclusions on the efficiency of exercise to enhance cognitive flexibility.

As improvements of executive function following moderately intense exercise have been linked with an optimal facilitation of arousal levels (Kashihara, Maruyama, Murota, & Nakahara, 2009), the autonomic nervous system modulation indexed by heart rate variability (HRV) may contribute to a deeper understanding of the underlying mechanisms. With regard to frequency domain HRV measures, low frequency (LF) power is considered to be an indicator of predominantly sympathetic influence (with a parasympathetic component), whereas high frequency (HF) power corresponds to respiratory sinus arrhythmia and, thus, is regarded a marker of parasympathetic influence (Michael, Graham, & Davis, 2017; Shaffer, McCraty, & Zerr, 2014). The LF/HF quotient is suggested to index sympathovagal modulation of the instantaneous heart rate, with low values reflecting greater parasympathetic than sympathetic activity (Shaffer et al., 2014).

Based on the neurovisceral integration hypothesis, executive functions are modulated by brain regions that are also involved in the parasympathetic control of the heart rate (Thayer, Hansen, Saus-Rose, & Johnsen, 2009). This is supported by findings showing associations between HRV and activity of the frontal cortices (Jennings, Sheu, Kuan, Manuck, & Gianaros, 2016; Thayer, Ahs, Fredrikson, Sollers, & Wager, 2012) due to their structural connections with sympathetic effector organs (Dum, Levinthal, & Strick, 2016). During cognitive tasks, a decrease in HRV indexed by parasympathetic withdrawal has been linked with higher demands on executive functions (Byrd, Reuther, McNamara, DeLucca, & Berg, 2014) and increased behavioral performance (Mathewson et al., 2010). Aerobic exercise has been found to reduce HRV and it is well known that the HRV recovery depends on the intensity of the preceding exercise bout (Michael et al., 2017). Consequently, the shift from a balanced HRV toward sympathetic dominance reflects an increase in arousal level, which is suggested to facilitate executive function (Kashihara et al., 2009).

So far, only a few studies have investigated the acute effects of exercise on HRV during tasks demanding executive control. Despite no changes in behavioral performance, increased LF power and decreased HF power during tasks demanding executive control were reported after an incremental exercise test in athletes (Di Luft, Takase, & Darby, 2009). However, high cognitive performance was associated with sympathetic-modulation-related indices of HRV. Investigating the acute effects of aerobic exercise at a self-selected intensity in young adults, Murray and Russoniello (2012) found improvements of executive function along with alterations of the LF component of the HRV. The association between LF power and task performance followed a quadratic trend, indicating that participants with moderate arousal levels after exercise performed best on the executive function tasks. As executive function deficits in children with ADHD have been related to hypoarousal during cognitive tasks (Cortese et al., 2012), a parasympathetic withdrawal and/or increased sympathetic modulation of the heart rate induced by exercise might be accompanied by improved behavioral performance. This is important as MPH administration restores the autonomic balance at rest, but inhibits the normal autonomic nervous system response to a cognitive challenge (Negrao, Bipath, van der Westhuizen, & Viljoen, 2011). Consequently, it is possible that a single exercise session elicits additional benefits for cognitive flexibility in MPH users by increasing arousal levels. However, a contribution of changes in HRV to enhancements of executive function following exercise has not yet been investigated in children with ADHD and healthy peers. Investigating task-related HRV changes may therefore provide new insights on the underlying mechanisms of exercise-induced benefits for cognitive flexibility.

The purpose of the present study was to examine the acute effects of moderate aerobic exercise on cognitive flexibility and HRV in children with ADHD and healthy controls. Based on previous findings (Chang, Liu, et al., 2012; Chen et al., 2014), we expected that performance on a creativity task would be higher after exercise compared with a physically inactive control condition. As it has been suggested that exercise-induced benefits are higher in low performers compared with high performers (Drollette et al., 2014; Sibley & Beilock, 2007), we further hypothesized that differences in task performance between the exercise and control condition would be higher in children with ADHD compared with healthy controls. With regard to HRV measures during the cognitive task, it was assumed that LF power would be higher and HF power would be lower after exercise than after the control condition (Di Luft et al., 2009; Murray & Russoniello, 2012), resulting in an increase of the LF/HF quotient.

Materials and Method

Participants

Children with ADHD (n = 18) and healthy peers (n = 18) aged between 11 and 16 years were recruited from local pediatricians, the University of Basel Children’s Hospital, and local schools. Children with ADHD were deemed eligible, if the diagnostic criteria of ADHD-combined type according to the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American Psychiatric Association [APA], 2013) were fulfilled and they were undergoing pharmacological treatment with MPH. These criteria were chosen to rule out the possibility that any exercise-induced changes in dependent variables are affected by the ADHD type and treatment. Using multiple assessments (anamnesis, standardized questionnaires, assessment of comorbidities), neuropediactricians and pediatricians specialized on ADHD verified the ADHD diagnosis of eligible participants. Exclusion criteria were autism as comorbid condition as well as any acute or chronic disease, which is either classified as a contraindication for exercise according to ACSM standards or impairs the practicability of the planned exercise session. After being informed on possible risks of the study, informed written consent was obtained from all participants and their legal guardians. The study protocol was approved by the local ethics committee and procedures were in line with the Declaration of Helsinki.

Design

The study was part of a project and comprised one screening visit and three experimental sessions (Ludyga et al., 2017b). For the present investigation, only two of these experimental conditions were compared. At the first visit, participants underwent a health check-up, which included measurement of blood pressure and pulmonary function as well as recording the electrocardiogram. In addition, legal guardians reported the medical history of their participating child and completed the Conners 3 scales (Lidzba, Christiansen, & Drechsler, 2013). Following familiarization with the cognitive test station, participants completed the PWC170 on a cycle ergometer according to the 2-min protocol that is recommended for children and adolescents (Bland, Pfeiffer, & Eisenmann, 2012).

The two experimental conditions were separated by at least 3 days and the first session always took place 7 to 14 days after the screening visit. Using a cross-over design, participants completed 20-min aerobic exercise and a physically inactive control condition. The order of conditions was counterbalanced and randomized across participants. After each condition, participants completed the Alternate Uses task (Guilford, 1967). Simultaneously, RR intervals were recorded using electrocardiography. The study design was comparable to previous investigations on the acute effects of exercise on cognitive performance (e.g., Drollette et al., 2014; Hillman et al., 2009). Both experimental conditions were scheduled at the same time of the day. The environmental temperature was held constant at 20° during the tests and the surrounding noise was reduced to a minimum.

Conditions

In the aerobic exercise condition, participants completed a 20-min moderately intense cycling bout on an ergometer (E200 P, COSMED, Italy). Based on Norton, Norton, and Sadgrove (2010), moderate intensity was defined as 65% to 70% of the maximum heart rate. As recommended for children and adolescents (Mahon, Marjerrison, Lee, Woodruff, & Hanna, 2010), the maximum heart rate was estimated using the formula 208 − 0.7*(age). While the cadence was held constant at 70 to 80 rpm, the power output was adjusted to make participants remain in their individual heart rate target zone. The heart rate during the exercise bout was continuously controlled and recorded using V800 heart rate monitors with a chest belt (Polar Electro, Finland).

The control condition took place in the same room, but on a separate day. For comparability with previous studies (Piepmeier et al., 2015; Stroth et al., 2009), watching a video was chosen as physically inactive control condition. While participants were seated, a 20-min documentary on exercise behavior in adults was shown. The video was appropriate for all ages and not considered to be cognitively demanding. Similar to the aerobic exercise condition, heart rate was recorded continuously using heart rate monitors.

Alternate Uses Task

The Alternate Uses task has been found to be a valid and reliable cognitive test for assessing cognitive flexibility (Benedek, Mühlmann, Jauk, & Neubauer, 2013). As previous meta-analytical findings indicate that the power to detect cognitive benefits is highest after a delay following exercise, the task was administered 15 to 20 min after the exercise and control condition (Chang, Labban, et al., 2012). In the Alternate Uses task, participants are asked to come up with as many alternative and novel uses as possible for common household items. For each stimulus object, participants were allowed to give verbal responses within a 60-s time period. The responses were collected using a dictating device placed in front of the participants. Prior to the task, standardized instructions were provided by an investigator trained on cognitive assessments. To ensure that the participants understood the task, instructions included the following example: If “newspaper” was given as the stimulus object, appropriate alternative uses would be “make a paper hat” and “use as a fly swat.” In each session, participants completed one set of stimulus objects, which consisted of three different items. The sets were randomized and counterbalanced across participants, so that one set was never completed twice by the same individual. The sets comprised the following items: drinking glass, car tire, and cardboard box (Set 1); paperclip, tin can, and shoe (Set 2); brick, bottle, and knife (Set 3).

For each item, fluency, flexibility, originality, and elaboration scores were assessed from the participants’ responses. Whereas fluency corresponded to the total number of correct responses (no repetitions and common uses allowed) for a stimulus object, flexibility reflected the total number of different categories used (e.g., “play football with tin can” and “play basketball with tin can” would fall into the same category). Based on the elaboration of the idea for a given object, each verbal response was rated with a score of 0, 1, or 2 points. For example, “a doorstop” would count 0 and “door stop to prevent door slamming shut in a strong wind” would count 2 as alternate use for a brick. Regarding the originality score, each response was compared to the responses of the whole sample. Responses given by one individual were scored 2 points, responses by two to three individuals were scored 1 point, and all other responses counted 0 points. For originality and elaboration, scores on each response were averaged. Fluency and flexibility scores were calculated as the mean of stimulus objects within a set. The analysis of performance on the Alternate Uses task was performed independently by two trained investigators blinded to the condition and group. Differences in ratings were resolved by consensus.

HRV

At rest and during the Alternate Uses task, the electrocardiogram was continuously recorded at a sampling rate of 2000 Hz (Kalamed, KEC-1000, Switzerland). Collected data were exported to Kubios HRV Analysis Software 3.0.2 (The Biomedical Signal and Medical Imaging Analysis Group, Department of Applied Physics, University of Kuopio, Finland) for off-line processing, which was performed by an investigator blinded to treatment. The HRV time series resulting from RR-intervals were converted to equidistantly sampled series by using a 4 Hz cubic spline interpolation. Subsequently, a linear detrend correction based on smoothness priors regularization (0.001 Hz cut-off) was applied to the R-R series to remove slow nonstationary trends from the signal (Tarvainen, Ranta-Aho, & Karjalainen, 2002). Based on HRV analysis guidelines (Camm et al., 1996), at least a period of 2 min is required to estimate frequency domain measures from short-term recordings. A previous study has further shown that vagal-afferent HRV indices are not influenced by tachogram length varying between 3 and 10 min (Grant, van Rensburg, Strydom, & Viljoen, 2011). As the time-on-task was 3 min in the cognitive test, epochs of identical length were subjected to Fast-Fourier transform by using Welch’s periodogram (300 s with 50% overlap). The resulting spectrum estimates were divided into very low frequency (VLF: 0-0.04 Hz), low frequency (LF: 0.04-0.15 Hz), and high frequency (HF: 0.15-0.4 Hz) bands. LF and HF power as well as the LF/HF quotient were analyzed as dependent variables. In contrast, VLF was not reported as the interpretability of this measure is limited in short-term recordings of 5-min length and less (Camm et al., 1996).

Statistics

Sample size was calculated a priori for a repeated measures analysis of variance (ANOVA) using G*Power 3.1 (Faul, Erdfelder, Buchner, & Lang, 2009). Based on a moderate effect size (f = 0.27) reported from a previous meta-analysis (Ludyga et al., 2016), a sample size of 30 participants was required to reach 80% statistical power at an alpha level of .05. For statistical analysis of collected data, SPSS 25.0 (IBM Statistics, USA) for Windows was used. In advance, the Shapiro Wilk test was applied to verify the Gaussian distribution of the data. Body mass index, body mass, age, submaximal power, ADHD symptoms, and heart rate were compared between children with ADHD and healthy controls using Students t-test. In case a variable was significantly different between groups, it was entered as covariate in the subsequent analyses that examined the effects of exercise on cognitive flexibility and HRV. To assess whether or not the Alternate Uses task performance was influenced by the objects included in the set, a 3 (set: 1, 2, 3) × 2 (condition: aerobic exercise, watching a video) multivariate analysis of variance (MANOVA) was applied on the four scores. Subsequently, possible carry-over effects due to the study design were investigated by applying a 6 (order: Set 1-2, Set 1-3, Set 2-3, Set 2-1, Set 3-1, Set 3-2) × 2 (condition) MANOVA. Main effects of set and order as well as the interaction of order and condition were reported. In the next step, the acute effects of exercise on the primary outcomes were examined by applying 2 (group: ADHD, healthy controls) × 2 (condition) MANOVAs separately on cognitive flexibility (flexibility, fluency, originality, and elaboration) and HRV (LF power, HF power). Main effects and/ or interactions were further examined using univariate ANOVAs. In addition, a 2 (group) × 2 (condition) ANOVA was employed to investigate the effect of acute exercise on LF/HF quotient. For all statistical comparisons, an alpha level of p ≤ .05 was considered as significant.

Results

Of 36 eligible participants, two children from the ADHD group discontinued the study prematurely due to illness. For the remaining participants, there were no differences between groups in anthropometric measures, relative power in the PWC170, resting heart rate as well as LF and HF power at rest (Table 1). In contrast, children with ADHD scored higher on the Conners 3 symptom scales. During the aerobic exercise session, participants’ mean heart rate was not different from the predefined heart rate target (139.1 ± 0.8 vs. 139.4 ± 2.1 bpm), t(33) = −7.24, p = .474. In the control condition, participants’ heart rate (70.7 ± 8.9 bpm) was lower compared with the aerobic exercise session, t(33) = 44.7, p < .001.

Table 1.

Participants’ Characteristics.

	ADHD (n = 5 f/11 m)		Controls (n = 7 f/11 m)		Student’s t-test
	M	SD	M	SD	t	p
Age in years	12.8	1.8	13.5	1.3	−1.3	0.217
Body mass in kg	54.1	16.1	55.4	12.5	−0.3	0.791
Body mass index in kgm⁻²	20.8	5.0	20.2	3.3	0.4	0.664
DSM-IV inattention	63.6	6.4	47.1	11.1	5.2	<0.001
DSM-IV hyperactivity	68.1	6.6	50.2	8.0	7.0	<0.001
DSM-IV combined	67.1	5.6	47.9	10.6	6.5	<0.001
PWC170 in Wkg⁻¹	2.4	0.7	2.5	0.5	−0.6	0.557
Heart rate in bpm	75.0	9.6	69.2	11.1	1.6	0.116
LF power in ms²	1,393.9	1,506.6	1,373.4	1,191.0	0.5	0.965
HF power in ms²	2,106.6	2,888.6	2,030.4	3,030.6	0.1	0.941

Note. DSM–IV clinical symptoms were assessed using the Conners 3 Scales–Parent Version; reported are T-values, corrected for sex. DSM-IV = Diagnostic and Statistical Manual of Mental Disorders (4th ed.); LF = low frequency; HF = high frequency.

Cognitive Flexibility

With regard to carry-over effects, there was no main effect of order, Wilks’s λ = .522, F(20, 83.9) = 0.9, p = .579, η² = .15, and no order by condition interaction for cognitive flexibility, Wilks’s λ = .619, F(20, 83.9) = 0.6, p = .888, η² =.11. In addition, no main effect of set on scores obtained from the Alternate Uses task was found, Wilks’s λ = .957, F(4, 29) = 0.3, p = .858, η² = .43.

Comparing cognitive flexibility between children with ADHD and healthy controls, there was no significant difference between groups, Wilks’s λ = .804, F(4, 29) = 1.8, p = .163, η² = .20. Regarding the acute effects of exercise on task performance, the MANOVA revealed a significant multivariate main effect for condition, Wilks’s λ = .725, F(4, 29) = 2.8, p = .047, η² = .28, and power to detect the effect was 0.68. Based on further examination, significant univariate main effects for condition were obtained for category, F(1, 32) = 4.5, p = .043, η² = .12; fluency, F(1, 32) = 4.7, p = .038, η² = .13; and originality, F(1, 32) = 4.3, p = .045, η² = .12. These effects indicated higher scores following aerobic exercise compared with the control condition (Figure 1). No interaction of condition and group was observed, Wilks’s λ = .995, F(4, 29) = 0.1, p = .998, η² = .01 (Table 2).

Figure 1.

Scores on fluency and category (Panel A) as well as originality and elaboration (Panel B) obtained from the Alternate Uses task following aerobic exercise and the control condition.

Table 2.

Performance on the Alternate Uses Task Following Aerobic Exercise and the Control Condition in Children With ADHD and Healthy Controls.

	ADHD (n = 5 f/11 m)				Controls (n = 7 f/11 m)
	Aerobic exercise		Control condition		Aerobic exercise		Control condition
	M	SD	M	SD	M	SD	M	SD
Category	4.0	1.5	3.6	1.3	4.5	1.6	4.0	1.4
Fluency	5.2	2.2	4.5	1.5	5.9	2.2	5.1	2.2
Originality	0.8	0.4	0.7	0.3	0.9	0.3	0.7	0.3
Elaboration	0.5	0.4	0.5	0.4	0.8	0.5	0.7	0.5

HRV

There was a main effect of condition on heart rate, F(1, 32) = 26.5, p < .001, η² = .45, indicating a lower heart rate during cognitive testing following the control condition (78.8 ± 10.3 bpm) compared with aerobic exercise (85.8 ± 10.2 bpm). With regard to HRV measures, the statistical analysis revealed a significant multivariate main effect for condition, Wilks’s λ = .704, F(2, 29) = 6.5, p = .004, η² = .30, and the power to detect the effect was 0.87. Given the significance of the overall test, the main effects were further examined using ANOVAs. Significant univariate main effects for condition were found for both LF power, F(1, 30) = 5.3, p = .029, η² = .14, and HF power, F(1, 30) = 13.2, p = .001, η² = 0.29, indicating lower HF and LF power following aerobic exercise compared with the control condition (Figure 2). No interaction of condition and group was observed, Wilks’s λ = .945, F(2, 31) = 0.9, p = .413, η² = .06. For LF/HF, there was a main effect of condition, F(1, 32) = 4.1, p = .050, η² = .11, indicating higher LF/HF following aerobic exercise (3.06 ± 2.47) compared with watching a video (2.31 ± 1.34).

Figure 2.

Task-related absolute low frequency and high frequency power following aerobic exercise and the control condition.

Discussion

Based on the examination of the acute effects of moderately intense aerobic exercise on cognitive flexibility, the present results indicate that behavioral performance on the Alternate Uses task was higher following the exercise session compared with the physically inactive control condition in both children with ADHD and healthy peers. Another novel finding was that participants showed a parasympathetic withdrawal during the task in the exercise condition, which was indexed by increased LF/HF quotient.

The observed improvements of cognitive flexibility were in line with meta-analytical findings showing general benefits for executive functions 10 to 15 min following moderate aerobic exercise (Chang, Labban, et al., 2012; Ludyga et al., 2016). Both children with ADHD and healthy controls had increased scores on category, fluency and originality in the Alternate Uses task. Although this task is classified as a tool to measure the cognitive flexibility component of executive function (Lezak, Howieson, & Loring, 2004), it has also been used to assess creative potential. According to Benedek et al. (2013), fluency and originality scores are suggested to reflect quantity and quality of ideation performance, respectively. As fluency counts the total number of alternative uses to common objects, improvements following moderate aerobic exercise reflect increased processing speed during a task demanding cognitive flexibility. Exercise-induced increases on the category score indicate both qualitative and quantitative improvements, but are not independent from fluency, as the maximum score that can be achieved increases with the number of responses. In addition, higher originality scores in the exercise condition further suggest that exercise enhanced the participants’ ability to find highly creative uses for common objects, thus reflecting improved quality of divergent thinking ability (Benedek et al., 2013).

So far, only a few experimental studies have shown that a single aerobic exercise session also enhances cognitive flexibility in both children with ADHD (Chang, Liu, et al., 2012) and healthy controls (Chen et al., 2014). The present findings provide further evidence that this core component of executive function is sensitive to aerobic exercise at child age. Studies investigating cognitive flexibility are rare, since this component is hardly separable from working memory and inhibition in early years, but improves almost gradually through adolescence (Best & Miller, 2010). Based on this late maturation, cognitive flexibility can be used as a marker of normal and atypical cognitive development. The transient improvements observed in the present study suggest that the positive influence of aerobic exercise on this executive function component is partly due to a high functional plasticity of the brain during this developmental period (Buttelmann & Karbach, 2017). This finding is consistent with a recent meta-analysis showing that in individuals undergoing developmental changes, aerobic exercise induces greater improvements of executive function than in other age groups (Ludyga et al., 2016).

The benefits observed in children with ADHD indicate that there is reserve for further cognitive improvements following exercise despite MPH treatment. In this respect, acute exercise might be seen as a complementary treatment, which allows a temporary enhancement of executive function beyond the normal range. As behavioral performance differences between the aerobic exercise and control condition were similar between children with ADHD and healthy controls, previous findings showing disproportionally higher exercise-induced benefits in low performers were not supported (Drollette et al., 2014; Sibley & Beilock, 2007). This might be partly due to the fact that children with ADHD showed no deficits in cognitive flexibility when compared with healthy controls, although previous meta-analytical findings suggest that MPH does not fully normalize executive functions in ADHD (Swanson et al., 2011). It should be noted that other components of executive function were not assessed, so that it cannot be ruled out that there were deficits in inhibitory control and/ or working memory. However, the findings by Pontifex, Saliba, Raine, Picchietti, and Hillman (2013) suggest that children with ADHD and healthy controls can expect similar benefits for inhibitory control following an aerobic exercise session.

Studies using functional near-infrared spectroscopy have found that in young adults acute aerobic exercise improves performance on frontal-lobe dependent tasks by increasing the activity of the (dorsolateral) prefrontal cortex (Byun et al., 2014; Yanagisawa et al., 2010). The Alternate Uses task also depends on frontal-lobe function, as highly creative uses for common objects were associated with greater activation of the inferior frontal gyrus (Benedek et al., 2014). Consequently, it is possible that exercise improves cognitive flexibility by a similar mechanism. Based on the neurovisceral integration hypothesis (Thayer et al., 2009), HRV is associated with executive function due to its ability to index the activation of prefrontal neural structures. The increased LF/HF ratio following the aerobic exercise condition might therefore indicate a favorable change of prefrontal cortex activity while performing the Alternate Uses task. A change of the sympathico-vagal balance induced by parasympathetic withdrawal has also been related to higher performance on executive function tasks in previous studies (Di Luft et al., 2009; Mathewson et al., 2010). Murray and Russoniello (2012) further showed that exercise enhances behavioral performance, if increases in sympathetic tone as indexed by LF power are moderate. However, children with ADHD and healthy controls showed decreased LF and HF power in the exercise compared with the control condition. Heterogeneous findings on LF power might be explained by the fact that this frequency range includes components of both parasympathetic and sympathetic activation (Goldstein, Bentho, Park, & Sharabi, 2011). The increased LF/HF quotient following exercise was due to a higher decrease of HF compared with LF power, so that the observed changes reflect an increase in arousal level due to reduced parasympathetic modulation of the heart rate (Shaffer et al., 2014). Cognitive benefits by facilitation of arousal have previously been linked with an increased release of catecholamines and endorphines (Dishman & O’Connor, 2009; McMorris, Collard, Corbett, Dicks, & Swain, 2008). This indicates that moderate aerobic exercise promotes an arousal state, which allows optimal task performance during executive function demands (Kashihara et al., 2009). A comparable increase of arousal levels in children with ADHD and healthy controls provides some indication that the mechanisms by which aerobic exercise benefits cognitive flexibility was similar between groups.

Due to some study limitations, the present findings have to be interpreted with caution. First, task performance was compared following exercise and after watching a video. Although previous cross-over studies have used a similar design (Drollette et al., 2014; Hillman et al., 2009), day-to-day variability cannot be ruled out as a potential confounder. However, the Alternate Uses task is suggested to be inappropriate for a pre–post design, because initial responses (pretest) would affect subsequent responses (posttest) when the task is repeated in a short period of time. Second, the choice of the control condition might have influenced the present results. Studies included in a recent meta-analysis on the acute effects of aerobic exercise on executive function used seated rest, stretching, passive cycling, or watching a video as control conditions (Ludyga et al., 2016). As children generally prefer any task over seated rest, comparisons between exercise and other physically inactive control conditions are suggested to be of higher practical relevance. Third, children with ADHD included in the present study were undergoing treatment with MPH and were diagnosed with ADHD-combined type. Therefore, the exercise-induced benefits for cognitive flexibility should not be generalized and projected onto all ADHD types and treatments. In addition, it should be noted that children with ADHD showed no deficits in cognitive flexibility when compared with healthy peers, so that it can be assumed that the MPH response was optimal. Thus, it remains unclear if a single aerobic exercise session elicits greater benefits in nonresponders. Fourth, improvements of cognitive flexibility elicited by a single exercise session are temporary. As there was only one assessment following exercise, it remains unclear for how long task performance was increased in comparison to the control condition. Future studies are therefore encouraged to examine the time-course of exercise-induced benefits for cognitive flexibility in children.

Conclusion

A single session of moderately intense aerobic exercise elicits temporary improvements of cognitive flexibility in children with ADHD, who are undergoing treatment with MPH, and their healthy peers. An increase in task-related arousal by withdrawal of the parasympathetic modulation seems to be one of the mechanisms underlying exercise-induced benefits for this particular component of executive function. Given that children’s executive functions are challenged in many different settings (e.g., school classes, examinations), a short aerobic exercise bout can be recommended to reach an adaptive state that allows optimal behavioral performance in a situation demanding cognitive flexibility.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Gottfried & Julia Bangerter-Rhyner Foundation (8472 / HEG-DSV [to SL]).

ORCID iD

Sebastian Ludyga

Author Biographies

Sebastian Ludyga is a sports scientist specialized in exercise neuroscience. He is currently working at the Department of Sport, Exercise and Health of the University of Basel and his research focus is on the effects of exercise on executive function in children and adolescents.

Markus Gerber is an assistant professor at the Department of Sport, Exercise and Health of the University of Basel, and he is head of the Division Sport and Psychosocial Health. His main research interests revolve around the following areas: stress, psychosocial health, psychiatric disorders, sleep, burnout, depression and promotion of physical activity.

Manuel Mücke is a researcher in Sports Science and has specialized in Sports Psychology and Cognition. Currently working at the Department of Sport, Exercise and Health, University of Basel, as scientific assistant.

Serge Brand is licenced in clinical psychology and psychotherapy. He is working as psychotherapist at the Psychiatric Hospital of the University of Basel. Further, he is adjunct professor at the Faculty of Psychology and Faculty of Medicine, the Department of Sport, Exercise and Health (University of Basel), and visiting professor at the Kermanshah University of Medical Sciences in Kermanshah (Iran).

Mark Brotzmann is lincenced in Paediatrics and specialized in developmental paediatrics. Currently working at the University Children’s Hospital Basel, Division of Neuropediatrics and Developmental Medicine, with special interest in ADHD and ASD.

Peter Weber is licenced in Medicine and Psychology and specialized in Child Neurology and Developmental Pediatrics. He works at the University Children Hospital Basel as head of the Division of Child Neurology and Developmental Medicine. His main research topics are neuropsychological and developmental problems of neurological diseases in childhood as well as developmental disorders.

Uwe Pühse is full professor at the Department of Sport, Exercise and Health of the University of Basel, and he is head of the Division Sport and Health Pedagogy. His main research interests involve the relation between physical activity and psycho-social health in different settings.

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