Enhancement or Skill Acquisition? Investigating the Contradiction of Combining Motor and Cognitive Challenges in sport training sessions

Enhancement or Skill Acquisition? 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Investigating the Contradiction of Combining Motor and Cognitive Challenges in sport training sessions Mohammadreza Ghasemian, Maedeh Hosseinalizade, Davoud Fazeli This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5359053/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study aimed to investigate the effect of combining cognitive challenges with table tennis training on executive functions and forehand skill acquisition. To do so, 36 beginners were randomly divided into three groups of high cognitive load, low cognitive load, and a control group. Participants were asked to perform the forehand task according to a certain practice designed for each group. Then, variables of inhibition, working memory, mental representation, and forehand accuracy were measured. The results showed that both experimental groups performed better than the control group in terms of inhibition; however, only the high cognitive load group had a significant improvement in terms of working memory and the low cognitive load group had a more structured mental representation than the other two groups. Moreover, the two experimental groups with high and low cognitive load performed more accurate forehand test than the control group. Our results show that practice with different cognitive loads can have different effects on improving cognitive functions and skill acquisition. Hence, the improvement of skill acquisition in both groups and the improvement of mental representation only in the group with low cognitive load could indicate that in the group with high cognitive load, attention has moved away from the skill performance procedure due to the working memory involvement during the practice; also, the participants had improved skill performance although no structured knowledge of the skill has been formed in their memory, which can be considered as a characteristic of the implicit learning style. executive functions skill acquisition cognitive load Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction The primary goals of incorporating physical activities are to improve physical and mental health and enhance skill acquisition. Thus, research in sports science and motor learning usually deal with these two issues separately and in different paradigms. Some experts seek to optimize training methods for better acquisition of movement skills so that individuals can implement these skills better in sports and rehabilitation fields 1 . However, other researchers seek to optimize training methods to improve cognitive and brain functions 2 . Finding ways to increase cognitive and brain health has received increasing attention. In this regard, one of the concepts that can be assessed jointly in these two areas is the role of working memory as it is believed to be the basis for other important human cognitive functions 3 , 4 . Previous studies on cognitive empowerment indicate the effectiveness of physical practice on brain functions, based on which different types of exercises have been investigated. For example, it was demonstrated that physical practice increases blood flow, oxygen supply to the brain, the volume of the hippocampus, and BDNF (neurotrophic factor) in the brain 5 – 7 . However, the approach of quantitative exercises versus qualitative exercises is a challenge. Studies show that although the quantitative exercise design approach can cause changes at the neurophysiological level, they do not necessarily lead to the improvement of executive functions 8 , 9 . In addition, research shows that aerobic sports interventions (with low cognitive demand) and resistance exercises have the weakest results for improving executive functions as compared to qualitative methods 8 , 9 . Accordingly, researchers believe that performing merely physical exercises may not improve executive functions, and if accompanied by cognitive challenges, it will exert further effects on improving executive functions 8 . Some studies have supported the effectiveness of combining cognitive and physical exercises to improve cognitive functions 10 , 11 . However, the new challenge is possibly related to the types of physical exercises and cognitive paradigms that should be combined. In this regard, table tennis is a perceptual-motor skill and has a time limit for decision-making and skill execution, in which a person must recognize the ball speed and location in the minimum time and make a decision. On the other hand, working memory is considered as the core of cognitive training 12 . Therefore, in the present study, table tennis exercises were combined with cognitive paradigms as well as working memory paradigms to answer the question whether combined cognitive and motor exercises could improve executive functions such as working memory and inhibition. On the other hand, studies in the field of motor skills acquisition demonstrate that the lower engagement of working memory during motor skills training, the better the motor skills acquisition 13 – 15 . Thus, the methods of teaching motor skills according to the use of working memory are placed at a point of a continuum, one end of which is explicit learning and the other is implicit learning. Explicit learning is a form of voluntary learning that requires the involvement of working memory and conscious effort of the learner 16 . This process is done using working memory resources and leads to the storage of declarative knowledge. Individuals can access such knowledge by retrieving information stored in the working memory and then can manipulate this information in the working memory to consciously execute movements 13 , described as reinvestment. In reinvestment, long-term memory sources are used to retrieve declarative knowledge, and the information retrieved by manipulating the working memory is used to consciously control movements 17 . Reinvestment can be detrimental to motor performance in certain conditions because it interferes with motor control mechanisms that usually operate automatically 18 . In contrary to explicit learning, implicit learning is expected to minimize the accumulation of movement-related knowledge or prevent the conscious access to this knowledge; in both cases, conscious thinking processes have less opportunity in destabilizing performance through efforts to consciously process movements. According to this, implicit learning paradigms suppress working memory activity during motor skill acquisition, thereby limiting access to cognitive resources for explicit learning 13 , 17 , 19 . Research has shown that implicit learning may benefit from higher neural efficiency than explicit learning under stress, pressure, and fatigue conditions, which is due to their limited dependence on the working memory and explicit knowledge, which in turn prevents the disruption of automatic performance and reinvestment 19 , 20 . The challenge is how to reduce access to working memory during skill training and use the benefits of implicit learning. Previous studies have proposed several methods to direct the learning style towards implicit learning. These paradigms reduce the role of awareness in learning, and operate with minimal dependence on working memory resources 16 . Researchers have introduced implicit motor learning paradigms using approaches such as training with secondary task 21 , errorless learning 22 , inhibition of working memory using tDCS 15 , analogy learning 23 , and cognitive fatigue 13 . Each of these methods suppresses working memory activity and indirectly uses different behavioural interventions and directs learning towards implicit learning. In this regard, the present study seeks to find out whether the combination of table tennis skill training with cognitive training paradigms can direct the acquisition of motor skills to implicit learning. Accordingly, it is assumed that when table tennis skill training is combined with cognitive paradigms, the person becomes less aware of how to perform the skill because the working memory is involved in making decisions about cognitive training challenges; as a result, this leads to implicit learning. On the other hand, it is assumed that with more cognitive involvement or higher complexity, the involvement and sensitivity of the person about skill execution increase and remove this effect. Therefore, the present study sought to investigate the dual challenge in skill acquisition versus cognitive empowerment, whether different types of table tennis exercises with high and low cognitive loads have a similar effect on cognitive empowerment and table tennis skills acquisition, or whether these two goals have a conflict of interest. Thus, to assess the effect of these exercises on cognitive empowerment, cognitive tests were used, and skills test was used to assess its effect on skill acquisition. Furthermore, the mental representation test was used to assess the knowledge of skill execution. Materials and Methods Participants The present study was implemented with a 3 (group) × 2 (test phase) design; 36 males within the age range of 12 to 15 years were randomly divided into three training groups with high cognitive load (n = 12), low cognitive load (n = 12), and a control group (n = 12). They had no previous experience or training about table tennis skills. The task was table tennis forehand on balls sent to the end of the table. Materials N-back test To evaluate the effect of exercises on working memory, N-back test was used in pre-test and post-test. The N-back test was performed using a computer software. In the computerized version of the N-back test, a sequence of visual stimuli appears on the screen step by step and randomly. The participant must check whether the currently presented stimulus is the same as stimulus n of the previous step. In the present study, the condition (n = 2) was used; if the presented stimulus is similar to the two previous stimuli, the participant should press the specified key. Reaction time, omission, and commission error components were evaluated as the variables of this test 24 . Go/no-go test This test is widely used to measure attentional inhibition and includes two categories of stimuli. Participants must respond to one group of stimuli (go) and refrain from responding to the other group (no-go). Since the number of "go" stimuli is usually more than "no-go" stimuli, the individual is more prepared to respond. In this test, the "go" stimulus is the letters of the alphabet that the participant must quickly press the space key after seeing each letter. It should be noted that if he sees the letter "p", he should give no answer. In the beginning, several attempts are presented in the form of a training so that the participant becomes completely familiar with the test and the answer key, and then he enters the 5-minute test phase. At the end, all responses and reaction time of the participants are recorded and reported as commission error score (should not have responded but did respond), omission error (failure to make a response when presenting the target stimulus), and reaction time 25 . Representation test To measure mental representation, the structural-dimensional analysis software of mental representation was used. In order to analyze mental representation, the initial step involved breaking down the desired task into separate components. Each of these components were labeled as basic action concepts. These concepts were the basis of subsequent analyses. The concepts were basically pieces of information of an action that form the memory structure of each action. In this study, these concepts included 16 action concepts, and each concept was placed in one stage of movement. The concepts were selected based on the source books of table tennis training and were approved by three experienced coaches. The structural-dimensional analysis of mental representation includes four steps. In the first step, a special split procedure is used to determine the Euclidean distance between the basic concepts of the action. In the split stage, a basic action concept is shown at the top of the screen and the person must compare it with all other basic action concepts one by one, and determine whether these concepts are related in the process of executing the movement. After comparing all the basic action concepts with the anchor concept (the concept displayed at the top of the screen), the anchor concept is changed and the individual must compare all the basic action concepts again with the new anchor concept, and determine whether they are related or not. This process will continue until all the basic action concepts are compared with each other. In this study, the examiner initially introduced the separation task to the participants. At first, the participants are provided with a random list of 16 basic concepts of forehand drive action. The examiner explains the meaning of each basic concept to the participant to make sure that he understood them well. Then, the participants are provided with the instructions above and asked to decide, according to the explanations, whether the basic concepts of the action are related when performing the movement or not. Then, the participants perform the separation task to determine the structure of their initial mental representation of the forehand task. In the second step, a hierarchical cluster analysis is used to determine the structure of the basic concepts of action (concepts categorization). Then, in the third step, a factor analysis determines different dimensions within the concepts (the dimensions in the specified categories are determined). In the last step, cluster solutions are tested for invariance within groups 26 , 27 . Skill test To evaluate the level of acquisition and the type of learning, a test different from training was used in the pre-test and post-test, where the person had to hit his forehand drives to circular targets, in which the accuracy of the hit was considered as a performance score. The circular targets were drawn on the bottom half of the table and included five nested circles, which were given scores 5, 4, 3, 2 and 1 from the innermost circle, according to the inner area and difficulty index of each, respectively. Each person had to hit the desired goals, and his total scores from 15 forehand hits were recorded as the performance accuracy in the pre-test and post-test 28 . Procedure At first, the participants were familiarized with the task performance separately. They performed required tests and tasks in six separate days to participate in different stages of the study. In the first session, a video was played on how to perform the forehand skill, but no verbal instructions were provided. To ensure the effectiveness of the intervention, before starting the intervention, tests related to cognitive functions (N-back and go/no-go), mental representation, and forehand skill were administered. Through the second to the fifth session, the participants in each group practiced the task. For example, in the training group with low cognitive load, the forehand hit was taught as usual, and the participants practiced it in a constant manner of 30 blocks (10 trials each). In this training method, first, the tennis table was divided into six zones 29 , and the participants consistently hit the ball to one of these zones in every 5 blocks and then aimed at another zone in the next 5 training blocks. On the other hand, in the training group with high cognitive load, after teaching the forehand skill, the participants performed forehand hits in 30 block (10 trials each) in combination with working memory paradigms (digits forward and backward, switching task and Updating task). In this method, the participants in each block should hit each of these six areas according to the type of cognitive paradigms. For example, in digits forward and backward paradigms, participants must keep the goals in their memory and hit towards the targets in 1–6 (digits forward) or 6 − 1 (digits backward), or for instance, in switching paradigm, participants should hit toward zones 2 and 6 in the first two trials and hit zones 5 and 1 in the next two trials; changing the targets were continued until the end of the 10 trials. During the training sessions, the level of cognitive loads gradually increased over time. Finally, in the last session, they went through exactly the same level performed on day 1 (pre-test). Figure 1 shows the research protocol. To analyze the effectiveness of the training program on the core executive functions and acquisition of forehand skills, the covariance analyses were used. Results At first, to examine the normality of the data, the Shapiro-Wilk test was used. The results showed that the data of the groups had a normal distribution in different stages of the test (P < 0.05). Descriptive statistics of the N-back and Go noGo tests in different groups and test stages are presented in Table 1 . Table 1. Descriptive Statistics of cognitive test Go no go test According to the finding obtained from the go no go test, the covariance analysis showed no significant difference in the reaction time between the groups ( \(\:{F}_{2و35}\) =1.23, P = 0.31, \(\:{}^{2}\) =0.071). Moreover, the results in omission error also indicated no significant difference between the groups \(\:{(F}_{2و35}\) =0.92, P= 0.41, \(\:{}^{2}\) =0.054). However, the covariance analysis on commission error in the go no go test showed a significant difference between the groups \(\:{(F}_{2و35}\) =6.27, P=0.005, \(\:{}^{2}\) =0.28). Bonferroni post hoc test on commission error showed a difference between the control group with low cognitive load (P= 0.032) and high cognitive load (P = 0.007), and these two groups had significantly improved as compared to the control group (P>0.05). N-back test The analysis of covariance in the N-back test showed no significant difference in the reaction time between the groups ( \(\:{F}_{2و35}\) =0.99, P = 0.38, \(\:{}^{2}\) =0.059). These results were also found in the omission error in the N-back test ( \(\:{F}_{2و35}\) =2. 3, P= 0.12, \(\:{}^{2}\) =0.13). Although the results of commission error analysis in the N-back test showed a significant difference between the groups ( \(\:{F}_{2و35}\) =3.99, P= 0.02, \(\:{}^{2}\) =0.20), the Bonferroni post hoc test showed a significant difference only between the control group and the high cognitive group (P=0.025). Performance accuracy The analysis of covariance regarding the performance accuracy of table tennis showed a significant difference between the groups ( \(\:{F}_{2و35}\) =7.57, P = 0.002, \(\:{}^{2}\) =0.32). As expected, the Bonferroni post hoc test showed a significant difference between the control group with the high cognitive (P=0.005) and low cognitive groups (P = 0.005). In other words, both groups learned more than the control group. It is noteworthy that no significant difference was observed between groups with high and low cognitive loads (P>0.05). Figure 1 depicts the pre-test and post-test changes in accuracy of hits in all three groups. Changes in the mental representation structure To evaluate the mental representation structure, a mean group dendrograms was calculated. Then, for cluster analysis, the significance level was set at P = 0.05, resulting in (d crit =3.4). Links between BACs higher than this value were considered statistically irrelevant while BACs linked under this critical value were considered as statistically relevant. No significant structure in the mental representation of the groups was observed during the pre-test. However, in the post-test, the mental representation structure of the group with low cognitive load showed three significant clusters. Invariance analysis showed a significant change in the mental representation structure of this group in the post-test as compared with the pre-test (λ < 0.68). However, no significant clusters were observed in the mental representation structure of other groups. The mental representation structure of the groups in the post-test is presented in the diagram below. Discussion and Conclusion The present study delved into the effect of engaging in sports training with different levels of cognitive loads on cognitive improvement and skill acquisition. The results revealed that, regarding the improvement of cognitive performance, both groups with high and low cognitive loads performed better than the control group in the go/no-go test (inhibition), but the group with high cognitive load performed better in the N-back test (working memory). These results can be explained from two perspectives. First, both exercises can improve the cognitive function of inhibition. However, it has been stated that physical exercises will have more effects on executive functions only if they are accompanied by cognitive challenges 8 , 10 . On the contrary, the cognitive tests generally showed that the group with low cognitive load also experienced an improvement in inhibitory control. This finding is in line with studies that show the perceptual-motor training model used in this study, the forehand hit, could improve inhibition, regardless of the cognitive load level 30 , 31 . Furthermore, the current findings could be considered in line with the studies in which physical exercises could improve inhibitory control 32 – 34 . Researcher in a review study stated that even if sports exercises are performed with low cognitive load could improve executive functions such as inhibition due to their impact on the brain structures that are effective on cognitive performance 35 . In the table tennis training, participant should pay attention to the perception of the speed and location of the ball landing and should predict the time and location of the interception. Besides, participants should hit the ball with appropriate timing; in addition, they should hit the ball to the desired area by controlling the force or applying force with appropriate level; these factors need further attention 31 . On the other hand, the joy of these exercises can usually double its positive effects 30 . Furthermore, the difference observed between the groups regarding effectiveness on two different types of cognitive functions can be examined according to the type of cognitive test used in this study. It seems that the positive effects of high cognitive load exercises on the n-back test may be due to the similarity of their cognitive loads. The high cognitive load exercises were mainly based on maintaining and updating information, while the N-back test mainly emphasized on the ability to manipulate or update information. In general, the results of the two cognitive tests imply that training with high cognitive load led to greater progress in the cognitive functions in this study. These results align with the findings that demonstrate physical exercises in combination with cognitive paradigms can have greater beneficial effects on enhancing executive functions 8 , 9 , 36 . The present findings regarding skill acquisition showed that both training groups with high and low cognitive load showed improvement in the table tennis forehand skills. Accordingly, both training styles significantly improved skill performance compared with the control group and had a similar effect on performance although the exercise group with low cognitive load had more structured representations than other groups. This can be explained from the point of view of the role of working memory during exercises 3 , and also the relationship between mental representation and actual performance 37 . The improvement of skill performance in both groups, and the improvement of mental representation only in the low cognitive load group indicate that no working memory is left for focusing on skill performance in the high cognitive load group due to the allocation of working memory capacity to cognitive paradigms used in the exercises. In other words, attention has moved away from skill performance. As a result, although individuals progressed in performing skills, a structured representation of the task was not formed in their memory. It is believed that mental representation is the underlying structure of skill execution 38 , but evidence shows that people with a stronger mental representation structure do not necessarily perform better and may in some cases perform weaker 37 , 39 . This result can be examined from the perspective of explicit learning versus implicit learning. Based on these concepts, the greater the contribution of implicit components, the weaker the role of working memory and consequently the reprocessing process; that is, individuals may perform the task better, and effectively respond to environmental pressures 13 , 16 . In different implicit approaches, individuals make the least use of working memory resources to focus on skills execution 16 . The method used in the exercise designed for the high cognitive load group creates effects similar to implicit learning conditions through the secondary task 21 . As a result, the present study aimed to eliminate or reduce the conscious part of movements, relying on this approach and combining movement exercises with cognitive challenges, and focusing on implicit learning using the secondary task approach. The present exercises have created a mechanism similar to the dual task paradigm although there were some differences. Thus, the paradigms of dual tasks in sports skills are often artificial, while the cognitive loads added in the current exercises are in the form of instructions put into a single task through performing the skill and not two separate tasks. The paradigms used in the current study somehow simulate technical and tactical strategies that the player should keep in mind during the game and make decisions based on environmental stimuli and use them. Also, the main purpose of using dual task paradigms is not to improve cognitive functions, but the present exercises were designed to promote cognitive functions. Therefore, these exercises can be considered as a design to promote implicit learning and cognitive empowerment. There is an old idea in skill learning, known as "Specificity of learning ". According to this principle, the transfer between the training condition and the subsequent performance in the real environment depend on the similarity between the elements of the training condition and the real-world performance 40 . In the present study, although the type of test used was more similar to the exercises of the group with lower cognitive load due to the need for less cognitive load, the results revealed that the exercise group with high cognitive load had similar performance in the transfer test, indicating generalizability or transfer of acquisition in this training method due to similar processing processes 41 . One possible explanation for the better mental representation structure of the group with low cognitive load is the nature of the exercise used in this group in which the working memory is probably less occupied, resulting in more active processing of information related to the representation structure. To support this argument, a direct relationship has been found between the capacity of the working memory and the mental representation structure of actions 37 . The weaker mental representation structure of the group with high cognitive load can be due to an additional load created on the working memory. Probably, the capacity of the working memory has been negatively filled by cognitive tasks during the execution of motor task and no space is left for processing sensory information related to the mental representation structure. The mental representation structure is not necessarily equivalent to the movement program, to be only a high-level cognitive component. But, the mental representation structure contains sensory information of movement stored in the mind as memory fragments 26 . Thus, if a variable disrupts the sensory processes caused by the action consequences during training, it may negatively affect the mental representation structure. It is worth considering that although some researchers assume learning movements as a result of the formation of a clear representation of actions in the mind of a person 26 , 27 , however, based on the current findings, performance improvement as a result of exercise is not always accompanied by improved mental representation. These results are in line with a study which showed that the analogy instructions group was not different in performance from the explicit group, but the explicit group had more knowledge as compared with skill implementation 42 . The results are in contrast with the previous results, showing that both groups of analogical and explicit instructions could improve both skill performance and mental representation of tennis 26 . Accordingly, although analogy learning does not provide clear instructions, it can focus on skill execution due to the freedom of working memory sources. Earlier studies used the tDCS technique and observed characteristics of learning similar to implicit learning when they reduced the performance of the parts related to verbal processing 15 . In the current method, although behaviour manipulation was used, there is possibly no working memory space left for processing of the skill performance. On the other hand, the participants in Shak and Frank’s study (2020) were at the intermediate level, or in other words, in the associative learning stage 26 , while participants were beginners in the present study. Therefore, according to the bottom-up learning theory, people may also benefit from explicit knowledge after learning implicitly during the progress stages 43 . As a result, further experience of the participants can lead to a distinct mental representation. Hence, based on the progression-regression theory and the possibility of referring to the early stages of learning under pressure 17 , it seems necessary to start learning with minimal access to explicit information. Generally, the findings support the effectiveness of combined cognitive and physical exercises on improving cognitive functions, especially inhibition, working memory, and forehand skills acquisition. Thus, by increasing the cognitive load, there may be an improvement in cognitive functions as well as skill acquisition through benefiting the implicit learning. In this regard, it seems necessary to mention a few points. The present findings manifest that although the effectiveness of these types of exercises has been proven on cognitive and skill acquisition components, according to the "challenge point framework" theory 44 , these exercises can benefit the most when this principle has been considered and the difficulty and complexity level of cognitive and motor challenges are proportional to the skill level of people. Therefore, future research should evaluate the optimal level of cognitive load to cognitively empower skill acquisition in different sport tasks with different cognitive needs and also in people with different levels of skill and cognitive ability. Declarations Ethics approval and consent to participate All procedures were approved by the Research Ethics Committees of Allameh Tabataba'i University (code: IR.ATU.REC.1399.042). After giving the initial instruction about the study, informed written consent was obtained from all participants. All of them participated in this study voluntarily. Consent for publication Not applicable Availability of data and materials Not applicable Competing interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding This project has been supported by the “Iranian Cognitive Sciences and Technologies Council Vise-Presidency for Science and Technology” Authors' contributions MG and DF contributed to the development of the protocol and preparation of the manuscript as well as reviewing and editing and data analysis. MH contributed to the data collection and proposal. Acknowledgments The authors are grateful to all participants, and trainers who cooperated in this study. References Williams, A. M. & Hodges, N. J. Effective practice and instruction: A skill acquisition framework for excellence. Journal of Sports Sciences 41 , 833-849 (2023). Mandolesi, L. et al. 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Mental Health and Physical Activity 15 , 34-39 (2018). Hillman, C. H., McAuley, E., Erickson, K. I., Liu-Ambrose, T. & Kramer, A. F. On mindful and mindless physical activity and executive function: A response to Diamond and Ling (2016). Developmental cognitive neuroscience 37 (2019). Lauenroth, A., Ioannidis, A. E. & Teichmann, B. Influence of combined physical and cognitive training on cognition: a systematic review. BMC geriatrics 16 , 1-14 (2016). Kim, T., Park, H. & Schack, T. A functional link between mental representation in long-term memory and cognitive performance in working memory. Advances in Cognitive Psychology 15 , 11 (2019). Schack, T. The cognitive architecture of complex movement. International journal of sport and exercise psychology 2 , 403-438 (2004). Frank, C., Land, W. M. & Schack, T. Perceptual-cognitive changes during motor learning: The influence of mental and physical practice on mental representation, gaze behavior, and performance of a complex action. Frontiers in psychology 6 , 1981 (2016). Schmidt, R. & Lee, T. Motor learning and performance 6th edition with web study guide-loose-leaf edition: From principles to application . (Human Kinetics Publishers, 2019). Grierson, L. E. Information processing, specificity of practice, and the transfer of learning: considerations for reconsidering fidelity. Advances in Health Sciences Education 19 , 281-289 (2014). Schlapkohl, N., Hohmann, T. & Raab, M. Effects of instructions on performance outcome and movement patterns for novices and experts in table tennis. International Journal of Sport Psychology 43 , 522-541 (2012). Hodges, N. & Williams, A. M. M. Skill acquisition in sport . (Taylor & Francis, 2012). Guadagnoli, M. A. & Lee, T. D. Challenge point: a framework for conceptualizing the effects of various practice conditions in motor learning. Journal of motor behavior 36 , 212-224 (2004). Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5359053","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":376737221,"identity":"33b3efeb-af9b-46a5-b5dd-0441dec72ad5","order_by":0,"name":"Mohammadreza Ghasemian","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYBACgwNAgrGBAUpWwMVxa7FE1XKGQYKgFnuEFhCjDaYFDzA73vuA8esOO3t+scONnwvn2dUZHGB++IGh4B5uLWeOGzDLnklOnDk7sVl65rZkCYMDbMYSDAbFuLXcSGNglmxjTjC4ndggzbuNGaiFwQzolwScWgwgWurt7W8nNv/mnVMP1ML+jaAWxo9thxk3SCe2SfM2HAZq4SFgy5ljDIcZ244nzrid2GbNc+y45MzDPMUSCfi0HG9jfPizrdqef3b649s8NdX8fMfbN3748Ae3FhA4zIPCZQZi/BqAEfiDgIJRMApGwSgY4QAAfepSpX9ayHoAAAAASUVORK5CYII=","orcid":"","institution":"Allameh Tabataba'i University","correspondingAuthor":true,"prefix":"","firstName":"Mohammadreza","middleName":"","lastName":"Ghasemian","suffix":""},{"id":376737222,"identity":"9214f1cf-20fd-4559-8bbf-b76826930c42","order_by":1,"name":"Maedeh Hosseinalizade","email":"","orcid":"","institution":"Allameh Tabataba'i University","correspondingAuthor":false,"prefix":"","firstName":"Maedeh","middleName":"","lastName":"Hosseinalizade","suffix":""},{"id":376737224,"identity":"0a0496ae-d6d1-4595-b959-e82afed78ef0","order_by":2,"name":"Davoud Fazeli","email":"","orcid":"","institution":"Shiraz University","correspondingAuthor":false,"prefix":"","firstName":"Davoud","middleName":"","lastName":"Fazeli","suffix":""}],"badges":[],"createdAt":"2024-10-30 07:08:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5359053/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5359053/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":69449174,"identity":"c6999c6b-c184-490c-b9b9-b10722fec396","added_by":"auto","created_at":"2024-11-20 12:29:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":306195,"visible":true,"origin":"","legend":"\u003cp\u003eThe research protocol\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5359053/v1/4e98ed3b9d6cdf9818eb5634.png"},{"id":69449173,"identity":"a6987383-0380-498b-9223-dd2a0d4b7eb8","added_by":"auto","created_at":"2024-11-20 12:29:05","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":10660,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 1. Changes in table tennis performance\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-5359053/v1/299f959ff4f8742edb8398ab.png"},{"id":69449719,"identity":"3ec67791-9a3a-401d-b218-bdc9a08178b5","added_by":"auto","created_at":"2024-11-20 12:37:05","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":47809,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 2. The mental representation structure of the pre-test\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5359053/v1/5365c37388a44c1d2db7350d.png"},{"id":69449176,"identity":"752399a9-2b25-40cf-83fa-05291c9cc8d6","added_by":"auto","created_at":"2024-11-20 12:29:05","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":46716,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 3. The mental representation structure of the post-test\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-5359053/v1/8f860ccb7b6584f7980830c3.png"},{"id":71648713,"identity":"e7a159cc-3277-4da9-a18b-587d864e407b","added_by":"auto","created_at":"2024-12-17 11:55:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":890272,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5359053/v1/89ef911e-01cd-43e8-9698-0b79a0b32507.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Enhancement or Skill Acquisition? Investigating the Contradiction of Combining Motor and Cognitive Challenges in sport training sessions","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe primary goals of incorporating physical activities are to improve physical and mental health and enhance skill acquisition. Thus, research in sports science and motor learning usually deal with these two issues separately and in different paradigms. Some experts seek to optimize training methods for better acquisition of movement skills so that individuals can implement these skills better in sports and rehabilitation fields \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. However, other researchers seek to optimize training methods to improve cognitive and brain functions \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Finding ways to increase cognitive and brain health has received increasing attention. In this regard, one of the concepts that can be assessed jointly in these two areas is the role of working memory as it is believed to be the basis for other important human cognitive functions \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePrevious studies on cognitive empowerment indicate the effectiveness of physical practice on brain functions, based on which different types of exercises have been investigated. For example, it was demonstrated that physical practice increases blood flow, oxygen supply to the brain, the volume of the hippocampus, and BDNF (neurotrophic factor) in the brain \u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. However, the approach of quantitative exercises versus qualitative exercises is a challenge. Studies show that although the quantitative exercise design approach can cause changes at the neurophysiological level, they do not necessarily lead to the improvement of executive functions \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. In addition, research shows that aerobic sports interventions (with low cognitive demand) and resistance exercises have the weakest results for improving executive functions as compared to qualitative methods \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Accordingly, researchers believe that performing merely physical exercises may not improve executive functions, and if accompanied by cognitive challenges, it will exert further effects on improving executive functions \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Some studies have supported the effectiveness of combining cognitive and physical exercises to improve cognitive functions \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. However, the new challenge is possibly related to the types of physical exercises and cognitive paradigms that should be combined. In this regard, table tennis is a perceptual-motor skill and has a time limit for decision-making and skill execution, in which a person must recognize the ball speed and location in the minimum time and make a decision. On the other hand, working memory is considered as the core of cognitive training \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Therefore, in the present study, table tennis exercises were combined with cognitive paradigms as well as working memory paradigms to answer the question whether combined cognitive and motor exercises could improve executive functions such as working memory and inhibition.\u003c/p\u003e \u003cp\u003eOn the other hand, studies in the field of motor skills acquisition demonstrate that the lower engagement of working memory during motor skills training, the better the motor skills acquisition \u003csup\u003e\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Thus, the methods of teaching motor skills according to the use of working memory are placed at a point of a continuum, one end of which is explicit learning and the other is implicit learning. Explicit learning is a form of voluntary learning that requires the involvement of working memory and conscious effort of the learner \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. This process is done using working memory resources and leads to the storage of declarative knowledge. Individuals can access such knowledge by retrieving information stored in the working memory and then can manipulate this information in the working memory to consciously execute movements \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, described as reinvestment. In reinvestment, long-term memory sources are used to retrieve declarative knowledge, and the information retrieved by manipulating the working memory is used to consciously control movements \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Reinvestment can be detrimental to motor performance in certain conditions because it interferes with motor control mechanisms that usually operate automatically \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. In contrary to explicit learning, implicit learning is expected to minimize the accumulation of movement-related knowledge or prevent the conscious access to this knowledge; in both cases, conscious thinking processes have less opportunity in destabilizing performance through efforts to consciously process movements. According to this, implicit learning paradigms suppress working memory activity during motor skill acquisition, thereby limiting access to cognitive resources for explicit learning \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Research has shown that implicit learning may benefit from higher neural efficiency than explicit learning under stress, pressure, and fatigue conditions, which is due to their limited dependence on the working memory and explicit knowledge, which in turn prevents the disruption of automatic performance and reinvestment \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The challenge is how to reduce access to working memory during skill training and use the benefits of implicit learning. Previous studies have proposed several methods to direct the learning style towards implicit learning. These paradigms reduce the role of awareness in learning, and operate with minimal dependence on working memory resources \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Researchers have introduced implicit motor learning paradigms using approaches such as training with secondary task \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, errorless learning \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, inhibition of working memory using tDCS \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, analogy learning \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, and cognitive fatigue \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Each of these methods suppresses working memory activity and indirectly uses different behavioural interventions and directs learning towards implicit learning.\u003c/p\u003e \u003cp\u003eIn this regard, the present study seeks to find out whether the combination of table tennis skill training with cognitive training paradigms can direct the acquisition of motor skills to implicit learning. Accordingly, it is assumed that when table tennis skill training is combined with cognitive paradigms, the person becomes less aware of how to perform the skill because the working memory is involved in making decisions about cognitive training challenges; as a result, this leads to implicit learning. On the other hand, it is assumed that with more cognitive involvement or higher complexity, the involvement and sensitivity of the person about skill execution increase and remove this effect. Therefore, the present study sought to investigate the dual challenge in skill acquisition versus cognitive empowerment, whether different types of table tennis exercises with high and low cognitive loads have a similar effect on cognitive empowerment and table tennis skills acquisition, or whether these two goals have a conflict of interest. Thus, to assess the effect of these exercises on cognitive empowerment, cognitive tests were used, and skills test was used to assess its effect on skill acquisition. Furthermore, the mental representation test was used to assess the knowledge of skill execution.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eThe present study was implemented with a 3 (group) \u0026times; 2 (test phase) design; 36 males within the age range of 12 to 15 years were randomly divided into three training groups with high cognitive load (n\u0026thinsp;=\u0026thinsp;12), low cognitive load (n\u0026thinsp;=\u0026thinsp;12), and a control group (n\u0026thinsp;=\u0026thinsp;12). They had no previous experience or training about table tennis skills. The task was table tennis forehand on balls sent to the end of the table.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMaterials\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eN-back test\u003c/h2\u003e \u003cp\u003eTo evaluate the effect of exercises on working memory, N-back test was used in pre-test and post-test. The N-back test was performed using a computer software. In the computerized version of the N-back test, a sequence of visual stimuli appears on the screen step by step and randomly. The participant must check whether the currently presented stimulus is the same as stimulus \u003cem\u003en\u003c/em\u003e of the previous step. In the present study, the condition (n\u0026thinsp;=\u0026thinsp;2) was used; if the presented stimulus is similar to the two previous stimuli, the participant should press the specified key. Reaction time, omission, and commission error components were evaluated as the variables of this test \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGo/no-go test\u003c/h3\u003e\n\u003cp\u003eThis test is widely used to measure attentional inhibition and includes two categories of stimuli. Participants must respond to one group of stimuli (go) and refrain from responding to the other group (no-go). Since the number of \"go\" stimuli is usually more than \"no-go\" stimuli, the individual is more prepared to respond. In this test, the \"go\" stimulus is the letters of the alphabet that the participant must quickly press the space key after seeing each letter. It should be noted that if he sees the letter \"p\", he should give no answer. In the beginning, several attempts are presented in the form of a training so that the participant becomes completely familiar with the test and the answer key, and then he enters the 5-minute test phase. At the end, all responses and reaction time of the participants are recorded and reported as commission error score (should not have responded but did respond), omission error (failure to make a response when presenting the target stimulus), and reaction time \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eRepresentation test\u003c/h3\u003e\n\u003cp\u003eTo measure mental representation, the structural-dimensional analysis software of mental representation was used. In order to analyze mental representation, the initial step involved breaking down the desired task into separate components. Each of these components were labeled as basic action concepts. These concepts were the basis of subsequent analyses. The concepts were basically pieces of information of an action that form the memory structure of each action. In this study, these concepts included 16 action concepts, and each concept was placed in one stage of movement. The concepts were selected based on the source books of table tennis training and were approved by three experienced coaches. The structural-dimensional analysis of mental representation includes four steps. In the first step, a special split procedure is used to determine the Euclidean distance between the basic concepts of the action. In the split stage, a basic action concept is shown at the top of the screen and the person must compare it with all other basic action concepts one by one, and determine whether these concepts are related in the process of executing the movement. After comparing all the basic action concepts with the anchor concept (the concept displayed at the top of the screen), the anchor concept is changed and the individual must compare all the basic action concepts again with the new anchor concept, and determine whether they are related or not. This process will continue until all the basic action concepts are compared with each other. In this study, the examiner initially introduced the separation task to the participants. At first, the participants are provided with a random list of 16 basic concepts of forehand drive action. The examiner explains the meaning of each basic concept to the participant to make sure that he understood them well. Then, the participants are provided with the instructions above and asked to decide, according to the explanations, whether the basic concepts of the action are related when performing the movement or not. Then, the participants perform the separation task to determine the structure of their initial mental representation of the forehand task. In the second step, a hierarchical cluster analysis is used to determine the structure of the basic concepts of action (concepts categorization). Then, in the third step, a factor analysis determines different dimensions within the concepts (the dimensions in the specified categories are determined). In the last step, cluster solutions are tested for invariance within groups \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSkill test\u003c/h2\u003e \u003cp\u003eTo evaluate the level of acquisition and the type of learning, a test different from training was used in the pre-test and post-test, where the person had to hit his forehand drives to circular targets, in which the accuracy of the hit was considered as a performance score. The circular targets were drawn on the bottom half of the table and included five nested circles, which were given scores 5, 4, 3, 2 and 1 from the innermost circle, according to the inner area and difficulty index of each, respectively. Each person had to hit the desired goals, and his total scores from 15 forehand hits were recorded as the performance accuracy in the pre-test and post-test \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eProcedure\u003c/h3\u003e\n\u003cp\u003e At first, the participants were familiarized with the task performance separately. They performed required tests and tasks in six separate days to participate in different stages of the study. In the first session, a video was played on how to perform the forehand skill, but no verbal instructions were provided. To ensure the effectiveness of the intervention, before starting the intervention, tests related to cognitive functions (N-back and go/no-go), mental representation, and forehand skill were administered. Through the second to the fifth session, the participants in each group practiced the task. For example, in the training group with low cognitive load, the forehand hit was taught as usual, and the participants practiced it in a constant manner of 30 blocks (10 trials each). In this training method, first, the tennis table was divided into six zones \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, and the participants consistently hit the ball to one of these zones in every 5 blocks and then aimed at another zone in the next 5 training blocks. On the other hand, in the training group with high cognitive load, after teaching the forehand skill, the participants performed forehand hits in 30 block (10 trials each) in combination with working memory paradigms (digits forward and backward, switching task and Updating task). In this method, the participants in each block should hit each of these six areas according to the type of cognitive paradigms. For example, in digits forward and backward paradigms, participants must keep the goals in their memory and hit towards the targets in 1\u0026ndash;6 (digits forward) or 6\u0026thinsp;\u0026minus;\u0026thinsp;1 (digits backward), or for instance, in switching paradigm, participants should hit toward zones 2 and 6 in the first two trials and hit zones 5 and 1 in the next two trials; changing the targets were continued until the end of the 10 trials. During the training sessions, the level of cognitive loads gradually increased over time. Finally, in the last session, they went through exactly the same level performed on day 1 (pre-test). Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the research protocol.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo analyze the effectiveness of the training program on the core executive functions and acquisition of forehand skills, the covariance analyses were used.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eAt first, to examine the normality of the data, the Shapiro-Wilk test was used. The results showed that the data of the groups had a normal distribution in different stages of the test (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Descriptive statistics of the N-back and Go noGo tests in different groups and test stages are presented in Table\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv\u003e\n \u003cdiv align=\"left\"\u003eTable 1. Descriptive Statistics of cognitive test\u003c/div\u003e\n \u003cdiv align=\"left\"\u003e\u003cimg src=\"https://myfiles.space/user_files/122228_c8a1650c59388082/122228_custom_files/img1731501227.png\"\u003e\u003cbr\u003e\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003eGo no go test\u003c/h2\u003e\n \u003cp\u003eAccording to the finding obtained from the go no go test, the covariance analysis showed no significant difference in the reaction time between the groups (\u003cspan\u003e\u003cspan\u003e\\(\\:{F}_{2و35}\\)\u003c/span\u003e\u003c/span\u003e=1.23, P\u0026thinsp;=\u0026thinsp;0.31, \u003cspan\u003e\u003cspan\u003e\\(\\:{}^{2}\\)\u003c/span\u003e\u003c/span\u003e=0.071). Moreover, the results in omission error also indicated no significant difference between the groups \u003cspan\u003e\u003cspan\u003e\\(\\:{(F}_{2و35}\\)\u003c/span\u003e\u003c/span\u003e=0.92, P= 0.41, \u003cspan\u003e\u003cspan\u003e\\(\\:{}^{2}\\)\u003c/span\u003e\u003c/span\u003e=0.054). However, the covariance analysis on commission error in the go no go test showed a significant difference between the groups\u003cspan\u003e\u003cspan\u003e\\(\\:{(F}_{2و35}\\)\u003c/span\u003e\u003c/span\u003e=6.27, P=0.005, \u003cspan\u003e\u003cspan\u003e\\(\\:{}^{2}\\)\u003c/span\u003e\u003c/span\u003e=0.28). Bonferroni post hoc test on commission error showed a difference between the control group with low cognitive load (P= 0.032) and high cognitive load (P\u0026thinsp;=\u0026thinsp;0.007), and these two groups had significantly improved as compared to the control group (P\u0026gt;0.05).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\"\u003e\n \u003ch2\u003eN-back test\u003c/h2\u003e\n \u003cp\u003eThe analysis of covariance in the N-back test showed no significant difference in the reaction time between the groups (\u003cspan\u003e\u003cspan\u003e\\(\\:{F}_{2و35}\\)\u003c/span\u003e\u003c/span\u003e=0.99, P\u0026thinsp;=\u0026thinsp;0.38, \u003cspan\u003e\u003cspan\u003e\\(\\:{}^{2}\\)\u003c/span\u003e\u003c/span\u003e=0.059). These results were also found in the omission error in the N-back test (\u003cspan\u003e\u003cspan\u003e\\(\\:{F}_{2و35}\\)\u003c/span\u003e\u003c/span\u003e=2. 3, P= 0.12, \u003cspan\u003e\u003cspan\u003e\\(\\:{}^{2}\\)\u003c/span\u003e\u003c/span\u003e=0.13). Although the results of commission error analysis in the N-back test showed a significant difference between the groups (\u003cspan\u003e\u003cspan\u003e\\(\\:{F}_{2و35}\\)\u003c/span\u003e\u003c/span\u003e=3.99, P= 0.02, \u003cspan\u003e\u003cspan\u003e\\(\\:{}^{2}\\)\u003c/span\u003e\u003c/span\u003e=0.20), the Bonferroni post hoc test showed a significant difference only between the control group and the high cognitive group (P=0.025).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\"\u003e\n \u003ch2\u003ePerformance accuracy\u003c/h2\u003e\n \u003cp\u003eThe analysis of covariance regarding the performance accuracy of table tennis showed a significant difference between the groups (\u003cspan\u003e\u003cspan\u003e\\(\\:{F}_{2و35}\\)\u003c/span\u003e\u003c/span\u003e=7.57, P\u0026thinsp;=\u0026thinsp;0.002, \u003cspan\u003e\u003cspan\u003e\\(\\:{}^{2}\\)\u003c/span\u003e\u003c/span\u003e=0.32). As expected, the Bonferroni post hoc test showed a significant difference between the control group with the high cognitive (P=0.005) and low cognitive groups (P\u0026thinsp;=\u0026thinsp;0.005). In other words, both groups learned more than the control group. It is noteworthy that no significant difference was observed between groups with high and low cognitive loads (P\u0026gt;0.05). Figure\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e depicts the pre-test and post-test changes in accuracy of hits in all three groups.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\"\u003e\n \u003ch2\u003eChanges in the mental representation structure\u003c/h2\u003e\n \u003cp\u003eTo evaluate the mental representation structure, a mean group dendrograms was calculated. Then, for cluster analysis, the significance level was set at P\u0026thinsp;=\u0026thinsp;0.05, resulting in (d\u003csub\u003ecrit\u003c/sub\u003e=3.4). Links between BACs higher than this value were considered statistically irrelevant while BACs linked under this critical value were considered as statistically relevant. No significant structure in the mental representation of the groups was observed during the pre-test.\u003c/p\u003e\n \u003cp\u003eHowever, in the post-test, the mental representation structure of the group with low cognitive load showed three significant clusters. Invariance analysis showed a significant change in the mental representation structure of this group in the post-test as compared with the pre-test (\u0026lambda;\u0026thinsp;\u0026lt;\u0026thinsp;0.68). However, no significant clusters were observed in the mental representation structure of other groups. The mental representation structure of the groups in the post-test is presented in the diagram below.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion and Conclusion","content":"\u003cp\u003eThe present study delved into the effect of engaging in sports training with different levels of cognitive loads on cognitive improvement and skill acquisition. The results revealed that, regarding the improvement of cognitive performance, both groups with high and low cognitive loads performed better than the control group in the go/no-go test (inhibition), but the group with high cognitive load performed better in the N-back test (working memory). These results can be explained from two perspectives. First, both exercises can improve the cognitive function of inhibition. However, it has been stated that physical exercises will have more effects on executive functions only if they are accompanied by cognitive challenges \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. On the contrary, the cognitive tests generally showed that the group with low cognitive load also experienced an improvement in inhibitory control. This finding is in line with studies that show the perceptual-motor training model used in this study, the forehand hit, could improve inhibition, regardless of the cognitive load level \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Furthermore, the current findings could be considered in line with the studies in which physical exercises could improve inhibitory control \u003csup\u003e\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e–\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Researcher in a review study stated that even if sports exercises are performed with low cognitive load could improve executive functions such as inhibition due to their impact on the brain structures that are effective on cognitive performance \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. In the table tennis training, participant should pay attention to the perception of the speed and location of the ball landing and should predict the time and location of the interception. Besides, participants should hit the ball with appropriate timing; in addition, they should hit the ball to the desired area by controlling the force or applying force with appropriate level; these factors need further attention \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. On the other hand, the joy of these exercises can usually double its positive effects \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Furthermore, the difference observed between the groups regarding effectiveness on two different types of cognitive functions can be examined according to the type of cognitive test used in this study. It seems that the positive effects of high cognitive load exercises on the n-back test may be due to the similarity of their cognitive loads. The high cognitive load exercises were mainly based on maintaining and updating information, while the N-back test mainly emphasized on the ability to manipulate or update information. In general, the results of the two cognitive tests imply that training with high cognitive load led to greater progress in the cognitive functions in this study. These results align with the findings that demonstrate physical exercises in combination with cognitive paradigms can have greater beneficial effects on enhancing executive functions \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe present findings regarding skill acquisition showed that both training groups with high and low cognitive load showed improvement in the table tennis forehand skills. Accordingly, both training styles significantly improved skill performance compared with the control group and had a similar effect on performance although the exercise group with low cognitive load had more structured representations than other groups. This can be explained from the point of view of the role of working memory during exercises \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, and also the relationship between mental representation and actual performance \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. The improvement of skill performance in both groups, and the improvement of mental representation only in the low cognitive load group indicate that no working memory is left for focusing on skill performance in the high cognitive load group due to the allocation of working memory capacity to cognitive paradigms used in the exercises. In other words, attention has moved away from skill performance. As a result, although individuals progressed in performing skills, a structured representation of the task was not formed in their memory. It is believed that mental representation is the underlying structure of skill execution \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, but evidence shows that people with a stronger mental representation structure do not necessarily perform better and may in some cases perform weaker \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. This result can be examined from the perspective of explicit learning versus implicit learning. Based on these concepts, the greater the contribution of implicit components, the weaker the role of working memory and consequently the reprocessing process; that is, individuals may perform the task better, and effectively respond to environmental pressures \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. In different implicit approaches, individuals make the least use of working memory resources to focus on skills execution \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. The method used in the exercise designed for the high cognitive load group creates effects similar to implicit learning conditions through the secondary task \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. As a result, the present study aimed to eliminate or reduce the conscious part of movements, relying on this approach and combining movement exercises with cognitive challenges, and focusing on implicit learning using the secondary task approach. The present exercises have created a mechanism similar to the dual task paradigm although there were some differences. Thus, the paradigms of dual tasks in sports skills are often artificial, while the cognitive loads added in the current exercises are in the form of instructions put into a single task through performing the skill and not two separate tasks. The paradigms used in the current study somehow simulate technical and tactical strategies that the player should keep in mind during the game and make decisions based on environmental stimuli and use them. Also, the main purpose of using dual task paradigms is not to improve cognitive functions, but the present exercises were designed to promote cognitive functions. Therefore, these exercises can be considered as a design to promote implicit learning and cognitive empowerment. There is an old idea in skill learning, known as \"Specificity of learning \". According to this principle, the transfer between the training condition and the subsequent performance in the real environment depend on the similarity between the elements of the training condition and the real-world performance \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. In the present study, although the type of test used was more similar to the exercises of the group with lower cognitive load due to the need for less cognitive load, the results revealed that the exercise group with high cognitive load had similar performance in the transfer test, indicating generalizability or transfer of acquisition in this training method due to similar processing processes \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e .\u003c/p\u003e\u003cp\u003eOne possible explanation for the better mental representation structure of the group with low cognitive load is the nature of the exercise used in this group in which the working memory is probably less occupied, resulting in more active processing of information related to the representation structure. To support this argument, a direct relationship has been found between the capacity of the working memory and the mental representation structure of actions \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. The weaker mental representation structure of the group with high cognitive load can be due to an additional load created on the working memory. Probably, the capacity of the working memory has been negatively filled by cognitive tasks during the execution of motor task and no space is left for processing sensory information related to the mental representation structure. The mental representation structure is not necessarily equivalent to the movement program, to be only a high-level cognitive component. But, the mental representation structure contains sensory information of movement stored in the mind as memory fragments \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Thus, if a variable disrupts the sensory processes caused by the action consequences during training, it may negatively affect the mental representation structure. It is worth considering that although some researchers assume learning movements as a result of the formation of a clear representation of actions in the mind of a person \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, however, based on the current findings, performance improvement as a result of exercise is not always accompanied by improved mental representation. These results are in line with a study which showed that the analogy instructions group was not different in performance from the explicit group, but the explicit group had more knowledge as compared with skill implementation \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. The results are in contrast with the previous results, showing that both groups of analogical and explicit instructions could improve both skill performance and mental representation of tennis \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Accordingly, although analogy learning does not provide clear instructions, it can focus on skill execution due to the freedom of working memory sources. Earlier studies used the tDCS technique and observed characteristics of learning similar to implicit learning when they reduced the performance of the parts related to verbal processing \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. In the current method, although behaviour manipulation was used, there is possibly no working memory space left for processing of the skill performance. On the other hand, the participants in Shak and Frank’s study (2020) were at the intermediate level, or in other words, in the associative learning stage \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, while participants were beginners in the present study. Therefore, according to the bottom-up learning theory, people may also benefit from explicit knowledge after learning implicitly during the progress stages \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. As a result, further experience of the participants can lead to a distinct mental representation. Hence, based on the progression-regression theory and the possibility of referring to the early stages of learning under pressure \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, it seems necessary to start learning with minimal access to explicit information.\u003c/p\u003e\u003cp\u003eGenerally, the findings support the effectiveness of combined cognitive and physical exercises on improving cognitive functions, especially inhibition, working memory, and forehand skills acquisition. Thus, by increasing the cognitive load, there may be an improvement in cognitive functions as well as skill acquisition through benefiting the implicit learning. In this regard, it seems necessary to mention a few points. The present findings manifest that although the effectiveness of these types of exercises has been proven on cognitive and skill acquisition components, according to the \"challenge point framework\" theory \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e, these exercises can benefit the most when this principle has been considered and the difficulty and complexity level of cognitive and motor challenges are proportional to the skill level of people. Therefore, future research should evaluate the optimal level of cognitive load to cognitively empower skill acquisition in different sport tasks with different cognitive needs and also in people with different levels of skill and cognitive ability.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll\u0026nbsp;procedures were approved by the Research Ethics Committees of\u0026nbsp;Allameh Tabataba\u0026apos;i University\u0026nbsp;(code: IR.ATU.REC.1399.042). After giving the initial instruction about the study, informed written consent was obtained from all participants. All of them participated in this study voluntarily.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project has been supported by the \u0026ldquo;Iranian Cognitive Sciences and Technologies Council Vise-Presidency for Science and Technology\u0026rdquo;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMG and DF contributed to the development of the protocol and preparation of the manuscript as well as reviewing and editing and data analysis. MH contributed to the data collection and proposal.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are grateful to all participants, and trainers who cooperated in this study.\u003c/p\u003e\n\u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWilliams, A. M. \u0026amp; Hodges, N. J. 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Challenge point: a framework for conceptualizing the effects of various practice conditions in motor learning. \u003cem\u003eJournal of motor behavior\u003c/em\u003e \u003cstrong\u003e36\u003c/strong\u003e, 212-224 (2004).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"executive functions, skill acquisition, cognitive load","lastPublishedDoi":"10.21203/rs.3.rs-5359053/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5359053/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study aimed to investigate the effect of combining cognitive challenges with table tennis training on executive functions and forehand skill acquisition. To do so, 36 beginners were randomly divided into three groups of high cognitive load, low cognitive load, and a control group. Participants were asked to perform the forehand task according to a certain practice designed for each group. Then, variables of inhibition, working memory, mental representation, and forehand accuracy were measured. The results showed that both experimental groups performed better than the control group in terms of inhibition; however, only the high cognitive load group had a significant improvement in terms of working memory and the low cognitive load group had a more structured mental representation than the other two groups. Moreover, the two experimental groups with high and low cognitive load performed more accurate forehand test than the control group. Our results show that practice with different cognitive loads can have different effects on improving cognitive functions and skill acquisition. Hence, the improvement of skill acquisition in both groups and the improvement of mental representation only in the group with low cognitive load could indicate that in the group with high cognitive load, attention has moved away from the skill performance procedure due to the working memory involvement during the practice; also, the participants had improved skill performance although no structured knowledge of the skill has been formed in their memory, which can be considered as a characteristic of the implicit learning style.\u003c/p\u003e","manuscriptTitle":"Enhancement or Skill Acquisition? Investigating the Contradiction of Combining Motor and Cognitive Challenges in sport training sessions","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-20 12:29:00","doi":"10.21203/rs.3.rs-5359053/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"69e13f38-0e45-4672-aff2-d753ccbd3106","owner":[],"postedDate":"November 20th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-12-17T11:54:36+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-20 12:29:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5359053","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5359053","identity":"rs-5359053","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}