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Editorial

Cognition and Motion: Sensory Processing and Motor Skill Performance in Athletic Training and Rehabilitation

1
Department of Biological and Medical Sciences, Faculty of Physical Education and Sport, Comenius University Bratislava, 814 69 Bratislava, Slovakia
2
Faculty of Health Sciences, University of Ss. Cyril and Methodius in Trnava, 917 01 Trnava, Slovakia
Submission received: 20 August 2022 / Accepted: 8 October 2022 / Published: 14 October 2022

1. Introduction

Recently, the role of exercise in improving executive functioning skills has been highlighted by researchers and conditioning specialists. However, their importance in sport remains widely unknown, and it is unclear if the measurement and training of executive functions are justifiable to help predict and develop talented individuals [1].
The evidence supports the benefits of both acute and long-term exercise for improvements in cognitive functions. In particular, working memory [2], the attention window and multiple object tracking [3,4] are trainable cognitive functions. Consequently, cognitive exercises included in the training routine may contribute to the enhancement of athletic performance [5,6,7,8], as well as to the prevention of injuries [9,10]. Nevertheless, there are only a few studies that demonstrate the relationship between basic cognitive functions and sport-specific motor skills. For instance, the diagonal attention window is positively associated with dribbling skills, which indicates that a broader attention window could be beneficial for highly demanding motor skills in soccer players [11]. Working memory capacity is positively related to dribbling, ball control and ball juggling [11]. Additionally, the cumulative score of cognitive tests is positively related to the cumulative motor test score, which supports the interplay of physical and psychological skills [11]. In particular, executive functions represent fundamental associations with game intelligence and game time in soccer players [12]. Furthermore, there is a large positive correlation of the cumulative score summarizing cognitive functions with the cumulative score summarizing sport-specific physical performance in volleyball players [13]. Small-to-medium correlations also occur between cognitive and motor skills [13]. This indicates that volleyball players with superior basic cognitive functions present better sport-specific physical performance [13]. In particular, fast and accurate decision making may determine success in many team and combat sports [14].
A recent literature analysis revealed a lack of research investigating the acute effect of fatigue on reactive agility, along with cognitive functions such as memory or learning [15]. Prolonged exercise causes a decline in the decision-making, attention and perception abilities of players. However, an alteration in players’ cognitive performance depends on the intensity and duration of fatigue-inducing tasks. Both exercise and mental fatigue can cause the accuracy of sport-specific tasks involving cognitive components to deteriorate. For example, mental fatigue and the consequent deterioration of decision making can be triggered by at least 30 min of a Stroop color-word task or smartphone application exposure. Taking into account possible negative effects of fatiguing exercise or mentally demanding tasks on human cognition, future research should consider the examination of different types and intensities of exercise on players’ cognitive performance.
However, a systematic review by Harris et al. [16] showed a limited support for the transfer of benefits from commercial cognitive training devices to sporting tasks, mainly because studies did not target the sporting environment. The evidence for sporting benefits is currently limited by the paucity of representative transfer tests and a focus on populations with health conditions. Therefore, cognitive tests should be integrated into testing batteries for athletes in order to scout and optimize their development [17]. In practice, reactive agility tests that address both perception and decision making (cognitive processing) and the physical component (i.e., change of direction speed) are frequently used for this purpose.

2. Assessing Sensory Processing and Motor Skill Performance of Reactive Agility

For many years, agility has been classified as the ability to execute rapid movements and the capacity to stop and restart quickly. As a result, the majority of agility research was devoted to pre-planned and change of direction speed tests. Eventually, agility tests that combined cognitive measures and change of direction speed have been developed. As a result, agility has been redefined as a rapid whole-body movement with change in velocity or direction in response to a stimulus [18]. This definition implies three basic components, i.e., stimulus perception, response selection, and movement execution.
Reactive agility tests provide information on agility time which includes both choice reaction time and movement time. However, it seems to be of practical importance to estimate their contribution to agility performance in athletes. The agility test complemented with measurements of simple reaction time and multi-choice reaction time as indicators of the speed and effectiveness of decision making, and movement time or movement velocity provides additional information on agility performance in athletes with different demands on their agility skills. Assessing the contribution of these components to agility performance in conditions that are similar to the demands of the sport of interest is useful in distinguishing within- and between-group differences, revealing exercise-induced changes and long-term adaptation during sport-specific training. The Agility Index is highly useful in helping to estimate the contribution of sensory and motor components to agility performance [19].

2.1. Within and Between-Group Differences in Sensory and Motor Skills

By comparing simple reaction time, multi-choice reaction time and movement time it is possible to estimate the contribution of sensory processing and change of direction speed to agility performance [20,21]. For instance, simple reaction time, multi-choice reaction time and agility time (representing both choice reaction time and movement time) in two athletes with different demands on their agility skills was compared [22]. Subject A, with both longer simple and choice reaction times, was able to achieve shorter agility time than subject B. Subject A was able to initiate his/her foot responses more rapidly due to the fact that he/she was an elite karate-kata competitor who does not usually respond to any stimuli but must be able to move a short distance very quickly. On the other hand, subject B, in spite of shorter simple and choice reaction times, was not able to transfer this capability into better agility time. This may be ascribed to the genetic disposition (fast reaction time in subject B) and adaptations to sport-specific training (fast movement time in subject A).
Furthermore, simple and two-choice reaction time was found to be significantly shorter in karate-kumite than the karate-kata competitors. This most likely contributed to shorter agility time (travelling distance of 0.8 m), as there were no significant differences in movement velocity between these groups. Simple and two-choice reaction time was also significantly shorter in both hockeyball and soccer goalies than players. In contrast, movement velocity was significantly higher in both hockeyball and soccer players than in goalies. Faster movement time most likely contributed to significantly shorter agility time in both hockeyball players (travelling distance of 1.6 m) and soccer players (travelling distance of 3.2 m) than in goalies. These findings were corroborated by a higher Agility Index in karate-kumite than karate-kata competitors and in hockeyball and soccer goalies than in players. Its higher values signify the predominant contribution of a sensory component to agility performance. Longer travelling distances make higher demands on change-of-direction speed and anaerobic/aerobic capabilities of players. While the motor component of agility performance seems to be predominant in players in terms of faster movement execution, in goalies it is the sensory component which allow them faster decision making. These findings indicate that both speed of decision making and change of direction speed contribute to agility performance in athletes, although to a different extent [20,21].

2.2. Exercise-Induced Changes and Training Adaptations in Sensory and Motor Skills

Likewise, the effect of exercise-induced fatigue on sensory processing and motor skill performance and their changes during athletic training can be estimated.
With respect to acute response to exercise, agility time significantly increased at a travelling distance of 0.8 m but not at a longer distance of 1.5 m [23]. However, there were no significant changes in the speed of step initiation. This indicates that soccer match induced fatigue affects the sensory rather than the motor component of agility performance.
With respect to training-induced adaptive changes, a 6-week program of balance exercises performed simultaneously with reaction tasks (4–5 sessions per week in duration of 30 min in a form of reaction tasks similar to game-like situations on unstable wobble boards) significantly reduced both simple and two-choice agility times and increased the speed of step initiation, whilst there were no significant changes in simple and two-choice reaction time in basketball players [24]. Taking into account no significant changes in reaction time, it is most likely that faster movement execution contributed to enhanced agility performance. This assumption was corroborated by a significant correlation between the reduction in agility time and an increase in movement speed after the training. So, it is obvious that a combined reaction-balance training improves the motor rather than the sensory component of agility performance. Training in competitive athletes may be insufficient to improve the perception and decision stage of agility skills. Therefore, more specific exercises should be implemented into training programs in order to improve visual reaction time.
A similar approach can be applied for interpreting changes in sensory processing and motor skill performance in recreationally active people as well as those of older age [25]. Attempting two tasks at the same time (e.g., responding to visual stimuli concurrently with balancing on an unstable support surface), both of which require controlled processing, can have a varied impact on a person’s performance depending on the task specificity. For example, reaction time increases while balancing on a wobble board, whereas sway velocity declines when concurrently performing reaction tasks. However, balance exercises performed simultaneously with reaction tasks for a period of 8 weeks (one 30 min session a week) represent an effective training for the improvement of dynamic balance, as well as for reduction of multi-choice reaction time in untrained individuals. Specific forms of training (e.g., serial mechanical proprioceptive stimulation) also enhance agility performance, as well as body balance and strength, in older people.
Furthermore, the agility training and testing in the form of competition may be used for children and young athletes to enhance their attention level and motivation. However, one has to be aware that competitive agility training improves agility time under competitive conditions only, and it fails to affect other reaction and speed abilities [26]. To evaluate the efficiency of such training, the Agility Test performed under simulated competitive conditions can be applied. In such a case, agility time is better when the Agility Test is performed in simulated competitive than in non-competitive conditions [27].

3. The Role of Sensory Processing and Motor Skill Performance in Reactive Agility

In 2002, Young et al. [28] suggested a model determining the main factors of agility. It consists of two main components, i.e., perceptual and decision-making factors and change of decision speed. The first component includes visual scanning (ability to process visual information in competitive games), anticipation (prediction of an event in a game that influences the movements of a player in a game), pattern recognition (the ability to reorganize patterns of play by an opposing team or player), and knowledge of situations (knowledge of the probable movements of other players, based on previous experience of the game). The second component includes technique (foot placement, adjustment of strides to accelerate and decelerate, body lean and posture), straight sprinting speed, and leg muscle qualities (strength, power, and reactive strength).
Later on, this model has been modified by Young et al. [29], as follows. A model of agility in invasion sports consists of three components, which are cognitive, physical, and technical. The first component includes decision making speed and accuracy (visual scanning, anticipation, pattern recognition, and knowledge of situations). The second component includes leg muscle qualities (strength, power, and reactive strength), core strength, and straight speed. The third component includes feet placement, adjustment of steps to accelerate, body lean and posture.
For example, a significant correlation between the time in the Y-shaped agility test and the 20 m sprint time, the 505 Agility test time, and RSI was found, whilst there was no relationship with parameters pertaining to reaction speed in handball players [30]. However, Reactive Agility Test (RAT) performance was not associated with RSI, the 505 Agility test time, squat jump height, 20 m sprint time, and reaction time to fast generated visual stimuli in spite of a seemingly large effect. It appears that the contribution of sensory and motor components depends on the structure of the agility test. While the Y-shaped agility test is mainly determined by the linear sprint speed, the change of direction speed, and reactive strength, there is a tendency for RAT to be determined by reactive strength, change of direction speed, explosive strength, and visual reaction time. This indicates that running speed and muscle strength are critical factors of agility performance in handball players. However, perceptual and decision-making processes play an important role in reactive agility. Therefore, more attention should also be paid to the improvement of cognitive skills in handball players. Exercises involving running with changes of direction in reaction to visual stimuli rather than pre-planned change-of-direction (COD) movements should be included in their training programs.
In this regard, Young et al. [31] reported that COD ability is an example of an isolated component of agility in which movement and perception are decoupled, and therefore, COD tests can lack ecological validity. The movement techniques and strength qualities that are important in many COD movements do not necessarily apply to agility in invasion sports [31]. The authors encourage researchers to study agility in a more naturalistic setting that can be expected to transfer to on-field performance.
A recent scoping review revealed that the change-of-direction speed (CODS) is associated with sprint time for 10 m, 20 m, and 30 m but not for a shorter distance of 5 m [32]. The CODS also correlates with maximal leg strength, both explosive and reactive [32]. However, the strength of this relationship depends on the type of CODS test, its structure (total running distance, number of changes in direction), and parameters analyzed (peak and mean values of power, velocity, and so forth) [32]. Moreover, one should be aware that the time in the curved sprint test is neither associated with the time in the repeated straight sprint test nor with the time in the repeated sprint test involving changes of direction in soccer players [33]. The non-significant relationship between these abilities implies that they are independent of each other and may have to be tested and trained complementarily. Future research should focus on selection of tests and their parameters that are close to the fitness demands of particular sports.

4. Conclusions

Training and rehabilitation programs for the improvement of sensory processing and motor skill performance represent an integral part of research in kinesiology, health and sport science. However, the effect of exercise on the motor component of performance is usually the aspect investigated, whereas lesser attention has been paid to the sensory component. Although designed to improve sensory functions, training programs usually consist of exercises which also involve motor tasks. Consequently, an enhancement in performance is often ascribed to an improvement in sensory function; however, it can equally be ascribed to an improvement in motor function. Therefore, the relative contribution of each of these components to an improvement in physical performance has to be more deeply investigated. In particular, the relationship between exercise and cognitive processes in the general non-athletic and athletic population should be further investigated in order to better understand their changes during training and rehabilitation programs.

Funding

This work was supported by the Scientific Grant Agency of the Ministry of Education, Science, Research and Sport of the Slovak Republic and the Slovak Academy of Sciences (No. 1/0089/20).

Conflicts of Interest

The author declares no conflict of interest.

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Zemková, E. Cognition and Motion: Sensory Processing and Motor Skill Performance in Athletic Training and Rehabilitation. Appl. Sci. 2022, 12, 10345. https://0-doi-org.brum.beds.ac.uk/10.3390/app122010345

AMA Style

Zemková E. Cognition and Motion: Sensory Processing and Motor Skill Performance in Athletic Training and Rehabilitation. Applied Sciences. 2022; 12(20):10345. https://0-doi-org.brum.beds.ac.uk/10.3390/app122010345

Chicago/Turabian Style

Zemková, Erika. 2022. "Cognition and Motion: Sensory Processing and Motor Skill Performance in Athletic Training and Rehabilitation" Applied Sciences 12, no. 20: 10345. https://0-doi-org.brum.beds.ac.uk/10.3390/app122010345

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