The effects of an exercise intervention on neuroelectric activity and executive function in children with overweight/obesity : The ActiveBrains randomized controlled trial

This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ The effects of an exercise intervention on neuroelectric activity and executive function in children with overweight/obesity : The ActiveBrains randomized controlled trial © 2023 the Authors Published version Mora‐Gonzalez, Jose; Esteban‐Cornejo, Irene; Solis‐Urra, Patricio; Rodriguez‐ Ayllon, María; Cadenas‐Sanchez, Cristina; Hillman, Charles H.; Kramer, Arthur F.; Catena, Andrés; Ortega, Francisco B. Mora‐Gonzalez, J., Esteban‐Cornejo, I., Solis‐Urra, P., Rodriguez‐Ayllon, M., Cadenas‐Sanchez, C., Hillman, C. H., Kramer, A. F., Catena, A., & Ortega, F. B. (2024). The effects of an exercise intervention on neuroelectric activity and executive function in children with overweight/obesity : The ActiveBrains randomized controlled trial. Scandinavian Journal of Medicine and Science in Sports, 34(1), Article e14486. https://doi.org/10.1111/sms.14486 2024 Scand J Med Sci Sports. 2023;00:1–17. | 1 wileyonlinelibrary.com/journal/sms Received: 21 April 2023 | Revised: 11 July 2023 | Accepted: 21 August 2023 DOI: 10.1111/sms.14486 ORIGINAL ARTICLE The effects of an exercise intervention on neuroelectric activity and executive function in children with overweight/obesity: The ActiveBrains randomized controlled trial JoseMoraGonzalez1 | IreneEstebanCornejo1,2 | PatricioSolisUrra1,3 | MaríaRodriguezAyllon1,4 | CristinaCadenasSanchez1,2 | Charles H.Hillman5,6 | Arthur F.Kramer5,7 | AndrésCatena8 | Francisco B.Ortega1,2,9 1Department of Physical Education and Sports, Faculty of Sport Sciences, Sport and Health University Research Institute (iMUDS), University of Granada, Granada, Spain 2Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain 3Faculty of Education and Social Sciences, Universidad Andres Bello, Viña del Mar, Chile 4Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands 5Department of Psychology, Northeastern University, Boston, Massachusetts, USA 6Department of Physical Therapy, Movement & Rehabilitation Sciences, Northeastern University, Boston, Massachusetts, USA 7Beckman Institute, University of Illinois at UrbanaChampaign, Champaign, Illinois, USA 8School of Psychology, University of Granada, Granada, Spain 9Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland Correspondence Jose MoraGonzalez and Irene EstebanCornejo, Department of Physical Education and Sports, Faculty of Sport Sciences, University of Granada, Carretera de Alfacar 21, Granada 18071, Spain. Email: [email protected] and [email protected] Funding information Agencia Nacional de Investigación y Desarrollo; Andalusian Operational Programme; European Commission; European Regional Development Fund; EXERNET Research Network on Exercise and Health; Fundación Alicia Koplowitz; Fundación Ramón Areces; Junta de Andalucía; Ministerio de Ciencia e Innovación; PN I+D+I 20172021; RETICS; SAMID III network; Spanish Ministry of Economy and Abstract Objective: To investigate whether a 20week aerobic and resistance exercise program induces changes in brain current density underlying working memory and inhibitory control in children with overweight/obesity. Methods: A total of 67 children (10.00 ± 1.10 years) were randomized into an exercise or control group. Electroencephalography (EEG)- based current density (μA/mm2) was estimated using standardized lowresolution brain electromagnetic tomography (sLORETA) during a working memory task (Delayed nonmatchedtosample task, DNMS) and inhibitory control task (Modified flanker task, MFT). In DNMS, participants had to memorize four stimuli (Pokemons) and then select between two of them, one of which had not been previously shown. In MFT, participants had to indicate whether the centered cow (i.e., target) of five faced the right or left. Results: The exercise group had significantly greater increases in brain activation in comparison with the control group during the encoding phase of DNMS, This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2023 The Authors. Scandinavian Journal of Medicine & Science In Sports published by John Wiley & Sons Ltd. 2 | MORAGONZALEZ et al. 1 | INTRODUCTION Childhood is considered a critical period for cognitive and neural development.1,2 In this context, one highly prevalent exposure that negatively alters brain health is obesity, as it has been associated with detectable structural brain abnormalities underlying executive function.3,4 Executive function constitutes supervisory control of higher cognitive processes that enable forethought and goaldirected actions.5 Specifically, executive function refers to specific cognitive domains including working memory (i.e., ability to briefly store and manipulate information), inhibitory control (i.e., ability to suppress irrelevant information and maintain focus), and cognitive flexibility (i.e., ability to shift attention when appropriate) that are vital to success in school and in life. A metaanalysis supported the existence of broad executive function deficits, including working memory and inhibitory control in children with overweight/obesity.6 Indeed, having an obesity condition is clearly associated with a reduced capacity to modulate and control the executive function networks, therefore, predisposing individuals to gain overweight.7 This could be explained in that much of our behavior is determined by an interaction between the impulsive system and the executive control system.6 Thus, children who show lower levels of executive control may be more susceptible to obesityrelated behaviors (e.g., increased intake of fatty foods due to impulsive behaviors and loss of control). Accordingly, there exists a fundamental neurobiological principle that affirms that biological events in the brain, although sometimes small, are amenable to modification by environmental factors.8,9 This indicates the importance of understanding how environmental factors such as physical activity (PA) may influence brain health, particularly in children with overweight/ obesity. The recent, rapid development of neuroelectric and other neuroimaging techniques has favored the advance of research on the understanding of the neural foundations of PAinduced benefits to brain health.10 Brain activity changes identified by functional magnetic resonance imaging (fMRI) and resulting from exercise interventions have been observed in children of normal weight11 and with overweight or obesity.12,13 Electroencephalography (EEG) and, more specifically, eventrelated brain potentials (ERP) (e.g., P3 component which is a positivegoing, stimuluslocked potential peaking occurring approximately 300 to 800 ms following stimulus onset) have been among the most prominent approaches to study exercise effects on brain function.14,15 In general, this body of evidence has shown that children participating in exercise programs exhibit larger amplitude16– 19 and shorter latency16 P3ERP components. Subsequently, substantial effects of exercise have been observed during tasks that measure higherorder executive functions, which are considered vital to success in school,20 and include working memory and inhibitory control. However, it should be noted that a consensus has not been reached in the literature as some studies have observed null effects of exercise on cognitive outcomes.12,21– 23 The vast majority of research addressing exercise effects on brain function in children has used an ERP approach.14,15,24 Despite the excellent temporal resolution of this measurement technique in milliseconds, a fundamental limitation of this approach is the inverse problem; that is, the measure is challenged in localizing activated brain regions by scalprecorded EEG activity.25 particularly during retention of second stimuli in temporal and frontal areas (peak t = from 3.4 to 3.8, cluster size [k] = from 11 to 39), during the retention of the third stimuli in frontal areas (peak t = from 3.7 to 3.9, k = from 15 to 26), and during the retention of the fourth stimuli in temporal and occipital areas (peak t = from 2.7 to 4.3, k = from 13 to 101). In MFT, the exercise group presented a lower current density change in the middle frontal gyrus (peak t = −4.1, k = 5). No significant change was observed between groups for behavioral performance (p ≥ 0.05). Conclusion: A 20week exercise program modulates brain activity which might provide a positive influence on working memory and inhibitory control in children with overweight/obesity. KEYWORDS brain activity, brain function, cognitive function, cognitive performance, physical activity, youth Competitiveness; Unit of Excellence on Exercise and Health; Universidad de Granada 16000838, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/sms.14486 by University Of Jyväskylä Library, Wiley Online Library on [06/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 3 MORAGONZALEZ et al. Alternatively, fMRI has a far superior spatial resolution capability than EEG, but is inherently slower (i.e., on the scale of seconds) and the low temporal resolution of this measurement may mask temporally separated processes into a single, more widespread spatially distributed activity.26 In the last decade, EEG source localization algorithms have emerged as an alternative approach that inherit the high temporal resolution of EEG and additionally generate an estimation (i.e., current source density) of the brain activity with greater spatial sensitivity.27 Specifically, standardized lowresolution brain electromagnetic tomography (sLORETA) has become an accepted EEGbased tool for the reliable detection of temporal– spatial brain activity involving simple, economical, and noninvasive use.28 Thus, to better understand modulations in brain activity induced by exercise, we used an EEGbased brain source analysis to take advantage of its unique characteristic of spatially estimating brain activation underlying higherlevel cognitive function (e.g., working memory and inhibitory control) during a specific time frame in which these processes occur (i.e., the millisecond range). By using sLORETA, the present study adds spatial sensitivity over previous EEGbased and ERPbased studies by detecting regional brain locations and networks that are influenced by exercise, while also providing a veryhigh temporal resolution over previous fMRI studies by detecting, on the order of a millisecond, in which cognitive processes (e.g., encoding, maintenance or retrieval processes during working memory operations) the effects of exercise (if any) occur. Therefore, this approach combines both an improved spatial resolution with a veryhigh temporal resolution, which may enhance the understanding of where and when the effects of exercise occur in brain function during cognitive operations. To the best of our knowledge, there is only one study in children of normal weight that has used EEGbased sLORETA brain source localization to investigate the acute effects of moderate exercise on current source density.29 However, no previous studies have investigated the longterm effects of exercise on current source density underlying working memory and inhibitory control operations in children with overweight/obesity. Furthermore, aerobic exercise (i.e., use of oxygen to meet energy demands during exercise via aerobic metabolism) has been the most predominant type of exercise in studies assessing the effects of exercise on brain activity,15,24 with no information to date about the effects of other types of exercise such as the resistance training (i.e., the goal is to strengthen muscles via physical effort to overcome bodily or external loads). Previous examinations into the implications of muscular strength for health30 indicated that higher levels of muscular strength are associated with a variety of health benefits such as decreased adiposity,31 improved metabolic control,32,33 and reduced insulin resistance,34 which may consequently be beneficial for cognition, especially in children with obesity.35 Furthermore, resistance exercise targeting improvements in muscular fitness may be beneficial for brain and cognitive processes36 given that skeletal muscle serves as an endocrine organ influencing brain metabolism through cytokines and peptides that are produced and released by muscle contractions.37 As such, the international PA guidelines suggest that exercise in children should be mostly aerobic, yet muscleand bonestrengthening activities should be performed at least three times per week to maximize the health benefits in this age group.38 Therefore, the aim of the present study was to investigate whether a 20week exercise program combining aerobic and resistance training, based on meeting PA recommendations,38 induces significant changes from preto postintervention in spatial– temporal brain current source density while performing tasks of working memory and inhibitory control in children with overweight/obesity. Following previous evidence, we hypothesized that a 20week exercise program will induce significant changes in brain current source density underlying working memory and inhibitory control as well as produce a significant improvement in behavioral performance in children with overweight/obesity. 2 | METHODS 2.1 | Design and participants The ActiveBrains project was a twogroup randomized controlled trial (RCT) carried out in children with overweight/obesity with the aim of analyzing the effects of a 20week aerobic and resistance exercise program on brain health, including brain structure and function, cognition and academic performance, and on physical and mental health outcomes (http://profi th.ugr.es/activ ebrains).39,40 Details of the ActiveBrains project and the CONSORT (Consolidated Standards of Reporting Trials) checklist have been previously described.39,40 The present study analyzed brain function and executive function outcomes, while the exercise effects on primary outcomes can be found elshewhere.41 All data were collected at preand postintervention from November 2014 through June 2016. Eligibility screening was performed over 115 children, and finally, 112 were accepted in the study after meeting inclusion/exclusion criteria (Figure1). Of these 112, 3 children chose not to continue and therefore randomization was applied over 109 children who were allocated to an exercise group, which participated in the exercise program, or a waitlist control group. The implementation of waitlist control group strategy has been done in previous 16000838, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/sms.14486 by University Of Jyväskylä Library, Wiley Online Library on [06/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 4 | MORAGONZALEZ et al. research.11,42 Following this strategy, participants of the waitlist group also receive the exercise program once the whole project has been completed. A computer random number generator in SPSS software for Windows (version 25.0; Armonk, NY, USA) was used to perform participants' simple random allocation into the exercise or the control FIGURE 1 CONSORT flow chart describing the study sample selection for the analysis. ADHD, AttentionDeficit Hyperactivity Disorder; DNMS, Delayednonmatched to sample task; EEG, Electroencephalography; MFT, Modified flanker task; sLORETA, Standardized lowresolution brain electromagnetic tomography. 16000838, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/sms.14486 by University Of Jyväskylä Library, Wiley Online Library on [06/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 5 MORAGONZALEZ et al. group. In this context, a “blinded” researcher (FBO) not involved in the assessments nor exercise program was responsible of the randomization. Equal probability of being allocated to either of the two groups (ratio 1:1) was warranted. For the reduction of the risk of bias, the following actions were carried out: (1) the person that conducted computer random generation was not involved in the assessments; (2) the randomization was performed immediately after the preintervention assessments; and (3) the people in charge of the exercise program did not take part in the assessments or randomization processes. For the present study, EEG data were collected during a delayed nonmatchtosample (DNMS) task (i.e., working memory) and a modified flanker task (MFT) (i.e., inhibitory control). Of the 109 randomized children, 107 successfully completed the EEG and task performance assessments at preintervention (Figure1). At postintervention, EEG data during DNMS task were collected for 90 children and EEG data during MFT for 92 children. Participants were included in analyses only if they had valid EEG data (i.e., good quality of EEG register) and valid cognitive tasks data (i.e., more than 20 trials completed) for both preand postintervention assessments, as well as whether they met the perprotocol criteria (see next section). Therefore, of the 90 (DNMS) and 92 (MFT) children with preand postintervention EEG data, 7 were excluded from analyses due to not meeting the perprotocol criteria (i.e. attending to at least 70% of the 3 recommended sessions/week), 1 was excluded due to having less than 20 trials completed for the DNMS task, and 21 (DNMS) and 18 (MFT) were excluded due to having an excessive noise of preor postintervention EEG register after visual inspection. Accordingly, for analyses, a total of 61 children (exercise group, n = 33; control group, n = 28) and 67 children (exercise group, n = 35; control group, n = 32) were included in analyses for working memory and inhibitory control tasks, respectively. An exploratory analysis was performed to determine whether significant baseline differences for the demographics and cognitive variables existed between the included and excluded participants of the present study. No significant differences were observed (p > 0.05; TableS1). The Human Research Ethics Committee of the University of Granada approved the ActiveBrains project. Registration was performed in Clini calTr ials.gov (identifier: NCT02295072). 2.2 | Physical exercise program The physical exercise program lasted 20 weeks. This program was designed based on the international PA guidelines valid at the time the study was being carried out (http://www.health.gov/pagui delin es/).41 According to the PA guidelines, young people should perform at least an average of 60 min/day of aerobic PA as well as muscleand bonestrengthening exercises should be incorporated at least 3 days/week to obtain health benefits.38 Participants were offered five sessions/week from Monday to Friday with a session's duration of 90 min. Following the guidelines, the minimum attendance rate was set at three times/week, although they were advised to attend all five sessions/week. For the present study, the final sample of 67 children with overweight/obesity (10.00 ± 1.10 years; 61.2% boys) included in analyses met the perprotocol criteria of: (i) having completed the preand postintervention EEG and both tasks assessments, and (ii) having attended at least 70% of the required three sessions/week (the exercise group). The exercise program was based on physical multigames to favor adherence to the program. The intervention was designed to be ecologically valid. That is, the intervention was designed to engage children in how they would normally play. To that end, it did not isolate aerobic or strength activities, rather it combined multiple exercise modes along with social interactions involving collaboration, competition, etc. The 90min session was structured as follows: (1) a warmup (5– 10 min), (2) an aerobicbased part with 4– 5 moderatetovigorous intensity multigames (60 min), (3) a resistancebased part with muscleand bonestrengthening activities (20 min), and (4) a cooldown part (5– 10 min). The target intensity of the exercise intervention was monitored and controlled individually in all children and in every session of the ActiveBrains program. Every child had their own heart rate monitor (POLAR RS300X, Polar Electro Oy Inc.), programmed individually based on their maximum heart rate achieved during a maximal incremental test, which is described elsewhere.39,40 Target intensity and progress were registered daily and checked weekly by trained personnel, mainly to identify whether any child was training at a lower intensity than intended and also to adapt the intensity according to the specific progress of each participant. This allowed the physical trainers to increase motivation and adapt the intensity of the games when needed. This was done for both the aerobic and resistance components of the program. A description of the characteristics of the program's intensity can be found elsewhere.40 2.3 | Control group The control group participants were requested to maintain their usual lifestyle and activities. A pamphlet with information on nutritional and PA guidelines was given 16000838, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/sms.14486 by University Of Jyväskylä Library, Wiley Online Library on [06/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 6 | MORAGONZALEZ et al. to this group. An ad hoc question was administered to the control group at postintervention to check whether they had generally maintained their usual lifestyle or not: “Did you make any major change in your physical/sport activity participation during the intervention period?” From these data, we detected that one of the children in the control group was enrolled in a swimming club with a heavy training load and competitions. We therefore decided to exclude this one participant from the main analyses. Based on the waitlist strategy explained above, children belonging to the control group participated in the exercise program once the whole project had been completed. 2.4 | Measurements A complete measurement session consisted of an EEG recording during two different executive function tasks (i.e., DNMS and MFT) that lasted 85– 90 min of total duration. The protocol for each child undergoing the measurement was divided into four phases. First, the EEG electrode cap was fit to child's head and electrodes filled with electrode gel for around 20 min. Second, the first executive function task (e.g., DNMS) was conducted. Third, after finishing the first task, evaluators checked the EEG data while the participant rested for approximately 10 min. Fourth, the second task (e.g., MFT) was conducted. The order of the cognitive tasks was counterbalanced across participants. All assessments were conducted by the same trained experimenters. Both tasks were presented centrally on a blue background on a computer screen using EPrime software (Psychology Software Tools). 2.4.1 | Delayed nonmatchedtosample task A version of the DNMS computerized task modified for children was used during EEG recordings to assess working memory.43 A full description of the task and its protocol has been provided elsewhere.44,45 Briefly, a trial had three different phases: encoding phase with the presentation and retention of stimuli (from −9000 to −4000 ms), the maintenance phase (0 ms), and the retrieval phase (0 to 1800 ms). Participants were asked to retain four stimuli that appeared sequentially during the encoding phase that lasted 5000 ms. Then, they were asked to maintain these stimuli memorized for 4000 ms, and finally, they were asked to select between two different stimuli (Pokemon cartoons) which one had not been shown during the encoding phase. The task was comprised of a total of 16 practice trials plus 140 experimental trials, of which 100 trials belonged to the high working memory load condition (i.e., more cognitively demanding) and 40 belonged to the low working memory load condition (i.e., less cognitively demanding). The main difference between these two conditions was that in the low load the four stimuli presented during the encoding phase were all the same, while in the high low load they were all different from each other. The 140 experimental trials were presented across four blocks of 35 trials in a randomized order, with a 3– 5 min rest between blocks. Duration of the task, including instructions prior to task performance, practice trials, and rest between experimental blocks, ranged from 45 to 50 min. For the present study, mean reaction time (RT) (s) and response accuracy (%) were registered. RT was computed from accurate response trials only. 2.4.2 | Modified flanker task A version of the Eriksen flanker task modified for children was used to assess inhibitory control.46 Thus, a trial presented five cows focally presented at a 1.2° visual angle each, and participants had to indicate using a computer mouse, with their dominant hand, whether the centered cow target (i.e., 1.2 cm tall cow) was directed to the right or the left. Participants were instructed to first focus on a central fixation cross (“+”) for 1250 ms, and once it disappeared, a target was presented that afforded the individual a response window of up to 1700 ms to provide a response. The intertrial interval (ITI) ranged from 3682 to 6158 ms (average ITI = 4875 ms). There were two different trial types depending on the directions faced by the flanking nontarget stimuli (i.e., four identical cows). For the congruent condition (i.e., lower inhibitory control demand), all cows faced the same direction (). For the incongruent condition (i.e., higher inhibitory control demand), the targeted cow was positioned in an opposite direction with respect to the flankered cows ( ). The task was comprised of a total of 12 practice trials plus 144 experimental trials (72 per condition) presented randomly across three blocks of 48 trials each. The number of trials is similar to previously modified flanker tasks administered to children that also included EEG.7,42 Total duration of the task ranged from 20 to 25 min including instructions, practice, and rest between blocks. Measures of mean RT (s) and response accuracy (%) were collected. RT was computed from accurate response trials only. 2.4.3 | Neuroelectric activity recording A 64channel Active Two BioSemi EEG system (24bit resolution, BioSemi) was used to assess neuroelectric activity. We based on the International 10– 10 system for EEG 16000838, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/sms.14486 by University Of Jyväskylä Library, Wiley Online Library on [06/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 7 MORAGONZALEZ et al. montage. Further details of this recording can be found in previous research.45 In brief, stimuluslocked epochs were formed from −10 000 to 2000 ms focusing on the retrieval phase of the DNMS task. For the MFT task, a window from −100.0 prior to 1700 ms was conformed after stimulus onset. Baseline correction was applied using the −100.0 to 0 ms prestimulus period. 2.4.4 | Brain source analysis We used sLORETA software to localize and identify neuroelectric activity.28 Validity of sLORETA has been tested against fMRI confirming that this technique can be used to estimate brain current source density (μA/mm2) and the brain areas underneath.28,47 This software allows the representation of brain activity from the spatial– temporal perspective.26 First, we submitted the overall averaged amplitude (μV) of each working memory load condition (i.e., low and high) and each inhibitory control condition (i.e., congruent and incongruent) for every participant at preand postintervention to sLORETA. Second, we computed the current density time course of each of the 6239 voxels of the sLORETA brain map provided by the Montreal Neurological Institute (MNI). Finally, individual voxels' raw sLORETA values were allocated to their corresponding Brodmann areas (BA) and the brain activity at each voxel was computed as the squared standardized magnitude of the estimated current source density (μA/ mm2). 2.5 | Statistical analysis Characteristics of the study sample are presented as means and standard deviations (SD), or percentages, when appropriate. Two analyses were performed in the present study to test the effects of the 20week ActiveBrains program: (i) on working memory and inhibitory control performance, and (ii) on the current source density estimated during these tasks. 2.5.1 | Effects of the ActiveBrains program on working memory and inhibitory control performance The effects of the ActiveBrains exercise program on the outcomes (i.e., RT and response accuracy) for each task (i.e., DNMS and MFT) and each condition of the task (i.e., high and low working memory; incongruent and congruent inhibitory control) were tested with analysis of covariance (ANCOVA). This analysis was formed using postintervention outcomes as dependent variables, group as fixed factor, and preintervention outcomes as covariates. Winsorization was performed with those raw values that needed it to avoid extreme values.48 The zscores for each cognitive outcome (i.e., RT and response accuracy) at postintervention were computed by dividing the difference of the postintervention raw value of each participant from the preintervention mean by the preintervention SD (i.e., [postintervention individual raw value − preintervention mean]/preintervention SD). This computation of zscore outcomes has been previously used in important RCTs focused also on cognitive outcomes.48 The computation of zscores has two main advantages: (1) by proving standardized estimates it allows the comparison between outcomes of different nature; (2) an interpretation of zscore of change as effect size (0.2, 0.5, and 0.8 considered as small, medium, and large effect sizes, respectively),49 that is, how many SD the outcome at postintervention changes from preintervention.48 All the statistical procedures were performed using the SPSS software for Mac (version 20.0, IBM Corporation). A significance difference level of p < 0.05 was set. 2.5.2 | Effects of the ActiveBrains program on current source density The effects of the ActiveBrains program on current source density during DNMS and MFT tasks were tested with an independent group analysis using sLORETA software. Through this test, the postand the preintervention current source densities in the exercise group were compared to those of the control group. Therefore, this test allowed analysis of which group had a greater change in the current source density from preto postintervention. For this purpose, sLORETA estimations of current source densities of every participant in the exercise and control groups were submitted individually for each task condition to a massunivariate t test (5000 random samples). This test controls for multiple comparisons correction by using an approximation to the permutation analysis based on the empirical singlethreshold of the tmax statistic.50,51 3 | RESULTS 3.1 | Effects of the ActiveBrains program on working memory and inhibitory control Table1 shows the preintervention characteristics of the study sample. TableS2 presents the effects of the ActiveBrains program on raw and zscore postintervention working memory and inhibitory control outcomes after 16000838, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/sms.14486 by University Of Jyväskylä Library, Wiley Online Library on [06/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 8 | MORAGONZALEZ et al. adjustment for preintervention values. Overall, the postminus preintervention change between groups was nonsignificant for both DNMS and MFT tasks (p ≥ 0.484). 3.2 | Effects of ActiveBrains program on current source density Table2, Figures2 and 3 present the brain regions for each hemisphere (left, L and right, R) and time frames (TFs) showing the postminus preintervention change in current source density between exercise and control groups during the performance of the working memory DNMS task. In the high working memory load condition, the exercise group, with respect to the control group, showed a higher current source density from preto postintervention in four different TFs during the encoding phase of the task. In the TF from −6547 to −6516 ms (i.e., the time after the presentation of the second stimuli), the current source density change was observed in five BAs (i.e., RBA13, 22, 31, 40, and 41) with peak t values ranging from 3.4 to 3.8 and cluster size (k) ranging from 11 to 39. In the TF from −6027 to −6008 ms (i.e., the time before the presentation of the third stimuli), the current source density change was observed in three BAs, particularly in bilateral BA9 (peak t = 3.9, k = 23 for LBA9; peak t = 3.7, k = 15 for RBA9) and in LBA8 (peak t = 3.8, k = 26). In the TF from −4090 to −4074 ms (i.e., the time during the presentation of the last working memory stimuli), the current source density change between groups was observed in four BAs (i.e., LBA18, 22, 30, and 37) with peak t values ranging from 3.5 to 4.3 and cluster size ranging from 13 to 18. In the TF from −4027 to −3988 ms (i.e., time between the presentation of the last stimuli and the preparation for the maintenance phase), the current source density change between groups was observed in seven BAs (RBA11, 13, 20, 22, 38, 41, and 47) with peak t values ranging from 2.7 to 3.2 and cluster size ranging from 14 to 101. TABLE 1 Descriptive baseline characteristics of the study sample. All Exercise group Control group NMean ± SD NMean ± SD NMean ± SD Sex Girls (n %) 26 38.8% 11 31.4% 15 46.9% Boys (n %) 41 61.2% 24 68.6% 17 53.1% Age (years) 67 10.00 ± 1.10 35 9.95 ± 1.14 32 10.05 ± 1.08 Body mass index (kg/m2) 67 26.58 ± 3.59 35 27.05 ± 4.10 32 26.06 ± 2.88 Wave of participation First (n %) 9 13.4% 6 17.1% 3 9.4% Second (n %) 22 32.8% 11 31.4% 11 34.4% Third (n %) 36 53.7% 18 51.4% 18 56.3% Working memory 61 33 28 Low working memory load Mean reaction time (ms)a897.17 ± 153.52 890.56 ± 150.83 904.95 ± 159.05 Response accuracy (%) 81.35 ± 13.65 82.88 ± 12.63 79.55 ± 14.80 High working memory load Mean reaction time (ms)a885.86 ± 153.54 873.44 ± 150.36 900.49 ± 158.70 Response accuracy (%) 68.22 ± 13.55 70.35 ± 13.07 65.71 ± 13.90 Inhibitory control 67 35 32 Congruent condition Mean reaction time (ms)a803.13 ± 122.39 810.56 ± 120.24 795.00 ± 126.12 Response accuracy (%) 93.82 ± 6.85 94.68 ± 6.13 92.88 ± 7.55 Incongruent condition Mean reaction time (ms)a852.26 ± 144.49 852.25 ± 149.68 852.26 ± 140.98 Response accuracy (%) 85.92 ± 19.15 86.90 ± 18.20 84.85 ± 20.37 Note: Values are expressed as means ± standard deviations (SD), unless otherwise indicated. Working memory was measured by the delayed nonmatchtosample task. Inhibitory control was measured by the modified flanker task. aHigher values indicate lower performance. 16000838, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/sms.14486 by University Of Jyväskylä Library, Wiley Online Library on [06/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 15 MORAGONZALEZ et al. density changes during this task; and (iii) the general use of standardized and validated instruments. 5 | PERSPECTIVE Our results add to the literature on the effects of exercise on brain health by providing support for the effects of a 20week gamebased exercise program on brain activity. Children from the exercise group, to a greater extent than those from the control group, significantly increased the current source density of a broad network of brain areas primarily in the frontal, temporal, and limbic areas during a working memory task. More specifically, these effects were observed during the encoding phase of the high load condition, suggesting that the longterm practice of exercise might enhance the capacity to visually process and store information during working memory processes. On the contrary, children belonging to the exercise group showed a significantly smaller increase in current source density of the frontal lobe during the information processing stream prior to the response during an inhibitory control task. Regardless, an aerobic and resistance exercise program modulates brain activity. However, no effects were observed in working memory and inhibitory control performance, and therefore, our findings showing the effect of exercise on brain activity must be viewed with caution. Finally, we suggest that exercise programs based on aerobic plus resistance training (mainly games), with 3– 5 sessions per week, can induce brain activation changes, although further studies must test whether other types of exercise (e.g., including motor agility) or of longer duration can have a higher impact on executive function as well as brain activity. ACKNO WLE DGE MENTS The present study was supported mainly by Spanish Ministry of Economy and Competitiveness' grants (DEP201347540, DEP201679512R, and DEP201791544EXP), the Alicia Koplowitz Foundation, the European Commission (No 667302), the European Regional Development Fund (ERDF). Also, the Andalusian Operational Programme supported with ERDF (FEDER in Spanish, BCTS355UGR18) funded this project. Additionally, this study was supported by the University of Granada, Plan Propio de Investigación, Visiting Scholar grants and Excellence actions: Units of Excellence; Unit of Excellence on Exercise and Health (UCEES) and by the Junta de Andalucía (Consejería de Conocimiento, Investigación y Universidades) and ERDF (SOMM17/6107/UGR). The SAMID III network, RETICS, funded by the PN I + D + I 20172021 (Spain), and the EXERNET Research Network on Exercise and Health (DEP200500046/ACTI; and by the High Council of Sports, 09/UPB/19) also funded this project. J.MG. was supported by grants from the Spanish Ministry of Science and Innovation (FPU 14/06837) and the Junta de Andalucía (Ref. DOC_00504). IEC was supported by the Spanish Ministry of Science and Innovation (FJCI201419563; IJCI201733642; RYC2019027287I). P.SU was supported by a grant from the National Agency for Research and Development (ANID)/BECAS Chile/72180543. M.RA was supported by the Alicia Koplowitz Foundation. C.CS. was supported by grants from the Spanish Ministry of Science and Innovation (FPIBES2014068829; FJC2018037925I). Funding for open access charge: Universidad de Granada/CBUA. This work is part of a Ph.D. Thesis conducted in the Doctoral Programme in Biomedicine of the University of Granada, Spain. We want to thank children and their families for participating in this clinical trial. CONFLICT OF INTEREST STATEMENT The authors declare no conflicts of interest. DATA AVAILABILITY STATEMENT Participants' consent to share the data was not obtain. Further, this was not included in the IRB protocol. ORCID Jose MoraGonzalez https://orcid. org/0000-0003-2346-8776 Irene EstebanCornejo https://orcid. org/0000-0002-0027-1770 Patricio SolisUrra https://orcid. org/0000-0002-2493-9528 María RodriguezAyllon https://orcid. org/0000-0002-8267-0440 Cristina CadenasSanchez https://orcid. org/0000-0002-4513-9108 Charles H. Hillman https://orcid. org/0000-0002-3722-5612 Francisco B. 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The effects of an exercise intervention on neuroelectric activity and executive function in children with overweight/obesity: The ActiveBrains randomized controlled trial. Scand J Med Sci Sports. 2023;00:1-17. doi:10.1111/sms.14486 16000838, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/sms.14486 by University Of Jyväskylä Library, Wiley Online Library on [06/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License