Thoughts

Exercise and cognitive function: A performance boost for gamers?

Regular physical activity is thought to have several benefits to mental health and cognitive performance (1,2,3) and whilst these will undoubtably be of benefit to the long term health and performance of an eSports gamer this essay is primarily concerned with the acute responses to physical exercise - that is, if a gamer has a 'movement break' from game time or takes part in a physical training session will subsequent gaming performance be affected?

In their physical activity guidelines the UK Chief Medical Officers state that long periods of sedentary behaviour (such as gaming) should be broken up with frequent bouts of light exercise (4). This recommendation for 'movement breaks' is mainly focused on the long term health risks of sedentary behaviour and the benefits of physical activity, however they will also have an acute response throughout the day. Bergouigan et al. compared the effects of 6 hours uninterrupted sitting with splitting the sitting time with one bout of 30mins easy walking on a treadmill in the morning and splitting the sitting time with hourly 5min walks and found that whilst the inclusion of exercise in a day increased self-perceived energy and vigour using the microdosing strategy had the added benefits of improved mood, decreased levels of fatigue and reduced food cravings at the end of the day (5). The inclusion of movement breaks during the day did not however affect cognitive function at the end of the day (as assessed by an Eriksen Flanker and a Comprehensive Trail-Making Test (CTMT)), a finding supported by Hunter and Wu who studied the behaviour of 95 office staff across a week at a university (6). Hunter and Wu had hypothesised that according to the effort-recovery model if a worker were to participate in physical activity during a break it would require the use of cognitive resources and therefore blunt recovery of these resources during the break time. During analysis they found no support for this hypothesis, though it should be noted that they examined self-reported variables via questionnaires completed after each break, rather than directly testing cognitive function. What their results did show, was that frequent breaks were the most beneficial to work performance and that there was evidence for a front-loading strategy (more breaks in the morning in order to keep the energy/cognitive resource reserves full for as long as possible). As the breaks in which the subjects participated in 'preferred activities' were the most effective in terms of energy recovery then it is important to factor this in during afternoon breaks, where energy levels are at their lowest and recovery is critical. These points of front-loading frequent breaks and allowing for a gamer's preferential choice of activity should be taken into consideration by coaches looking to implement movement breaks.

If either of the previously discussed studies had performed cognitive performance testing directly after each active/movement break whether or not they would have found any acute cognitive changes remains a matter of debate (7). The question is complicated by the fact that paradigms in cognitive psychology rely on assumptions which are not directly observable and so tests have had to be designed to infer measurement of these variables (such as the CTMT used in the Bergouigan study (5)). Which of these tests is used in a study can affect the outcomes and the ecological validity of the testing. For example Sousa et al. (8) argue that multiplayer online battle arena (MOBA) games, such a League of Legends, in which a gamer's character is placed at the centre of the screen with a large view of the surrounding area creates an environment in which strategising is highly important. In contrast a first-person shooter (FPS) game, such as Overwatch, places a higher relative importance on reaction speed due to the narrower visual perspective and speed of the game. Therefore, if an exercise intervention study were to be performed with an Overwatch player using the CTMT as a measure of cognitive performance it would potentially have less ecological validity than, for example, a choice reaction test (CRT).

It is also common to see contradictory affects on cognitive performance measures following a single bout of exercise, so for example reaction speed may improve but accuracy may decrease (9). These differing responses are due to the different neurocognitive processes involved, and as with all research care should be taken not to overgeneralise when looking at results as there are individualised differences in the neurocognitive processes (10). To use the speed/accuracy trade-off as an example Perri et al. (10) studied the speed and accuracy of subjects performing a CRT and found that, pre-stimulus, those subjects with faster response times had greater Breitenschaft Potentials in the supplementary motor area whilst those with higher accuracy had reduced prefrontal negativity in the right prefrontal cortex. Post-stimulus differences were also found in the brain's extrastriate visual and parietal areas and the anterior Insula. In conclusion they stated that the speed and accuracy systems do interact, but are not totally dependant on each other. This is supported by a meta-analysis of results performed by McMorris et al. (9) which overall found a larger effect size for the positive effect of exercise on reaction time than the effect size for the detrimental effect of exercise on accuracy and given that it is possible to affect one without affecting the other these systems must have some degree of independence and there is not a direct speed-accuracy trade-off.

How different cognitive energetic models assess the effect of steady-state aerobic exercise on cognitive performance (7).

The neuroendocrinological theory may explain some of the exercise-cognition interaction and tie some of these contradictory findings together. The theory was described by McMorris (11) as an endocrinological response to (and indeed anticipatory preparation for) exercise. Initially the hypothalamus triggers the synthesis of catecholamines in the sympathoadrenal system and cortisol via the hypothalamic-pituitary-adrenal axis. As exercise intensity increases dopamine and noradrenaline are synthesised in the brain and noradrenaline from post-ganglionic sites, these hormones playing an important role in up-regulating the cognitive and emotional areas of the brain. Therefore exercise intensities at which brain catecholamines and cortisol concentrations are moderately increased may be optimal for cognitive function. As exercise intensity increases however, the level of cortisol is no longer sufficient to inhibit the synthesis of corticotropin releasing hormone and adrenocorticotropin hormone resulting in a increase in arousal and activation of the limbic system (the limbic system may also be further up-regulated by excess noradrenaline and dopamine). This increase in limbic system activity comes at the expense of the cognitive centres, in particular the prefrontal cortex and, as previously discussed, changes in the right prefrontal cortex are indicative of changes in task accuracy (10). McMorris et al (9) also postulate that increases in the neurotransmitters norepinephrine and dopamine may eventually reach a level where the signal-to-noise ratio in the brain is decreased.

The hormonal changes in the brain are transitory, which would explain the fact that Irwin et al. (15) found a reduction in reaction time during a CRT performed by endurance athletes directly after an hour's cycling and that the reaction times had returned to baseline levels after an hour's rest. It would also mean that Bergouigan et al (5) who only performed cognitive function testing at the beginning and end of the working day may have missed acute responses which occurred following each session on the treadmill.

The exact exercise intensity which will create the greatest improvement in cognitive performance depends on which measure of performance is being tested (12). For example Chmura et al. (13) found improvements in CRT time in subjects cycling both 10% above and 30% below the lactate threshold (with significant differences between the two intensities). In contrast Féry et al. only found changes in their subjects' short term memory performance as the subjects were pushed to exhaustion (12).

McMorris et al. (9) say that complex cognitive tasks, such as gaming, can include an element of stress which elicits a hormonal response similar to that of exercise. Sousa et al. (8) support this as they found comparable changes in physiological parameters such as heart rate and cognitive measures such as accuracy and reaction speed following a competitive gaming session to those seen following exercise. This would suggest that exercise may not be a suitable break activity as the continually elevated arousal and hormone levels wouldn't allow for recharging of cognitive resources, as hypothesised by Hunter and Wu (6). That Hunter and Wu didn't find support for this theory, as previously discussed, may be due to the subject performing self-selected exercise activities and intensities (factors which were not controlled as it was a purely observational study) and as Audifferen and André say that 'effortless' physical activity such as jogging or walking at a self-selected comfortable pace require little attention they would therefore elicit little stress response (14).

In conclusion the evidence seems unequivocal that taking regular breaks throughout the day leads to improvements in attention, levels of fatigue and mood. Using these times to accumulate physical activity can boost physical and mental well being, but care should be taken when programming these movement breaks as the evidence for what is helpful and what is detrimental is less clear. Low levels of exercise may not have any affect on cognitive measures such as accuracy and reaction time, whilst still allowing for cognitive resources to be recharged, hence the decreased fatigue and increased mood seen following a break. As the intensity level of exercise increases it may lead to measurable cognitive function improvements which would be of direct benefit to subsequent gaming performance, however when pushed too far some measures will deteriorate. An example of this would be the deterioration in short term memory function when a subject is pushed to physical exhaustion and whilst this effect may only be short lived, due to the transient nature of hormonal responses, it would directly affect subsequent performance in a MOBA game which relies on higher cognitive processes. Such a change in memory function may not however affect performance on a FPS aim trainer and indeed reaction speed has been shown to improve when working above the lactate threshold, so coaches should consider what is being trained or which game is being played, as well as the fitness levels of the gamer when designing movement breaks.

It would appear to be good practise to allow for several breaks in the morning's game time, even though the gamer may still appear fresh, in order to keep cognitive resources at their highest level for as long as possible. The gamer's preferences for activity and intensity levels should be taken into account, as forcing them to do an activity they do not like will increase stress levels and correspondingly arousal which may counter the desired effects of taking a movement break, this is especially important in the afternoon when attention levels, mood etc. may be dropping.

Whilst low to moderate exercise intensities are the most appropriate for movement breaks during game time due to their acute performance benefits regular exposure to higher intensities is also important in the long term in order to offset the health risks of spending a long time sat in front of a screen. It is up to the skill of the coach to balance these two conflicting needs.

References

1. World Health Organisation. (2020). World Health Organisation guidelines on physical activity and sedentary behaviour. (Link)

2. Biddle, S., & Asare, M. (2011). Physical activity and mental health in children and adolescents: a review of reviews. British Journal of Sports Medicine, 45, 886-895. (Link)

3. Biddle, S., Ciaccioni, S., Thomas, G., & Vergeer, I. (2019). Physical activity and mental health in children and adolescents: An updated review of reviews and an analysis of causality. Psychology of Sport & Exercise, 42, 146-155. (Link)

4. Department of Health and Social Care. (2019). UK Chief Medical Officers' physical activity guidelines. (Link)

5. Bergouignan, A., Legget, K., De Jong, N., Kealey, E., Nikolovski, J., Groppel, J., Jordan, C., O'Day, R., Hill, J., & Beslesen, D. (2016). Effect of frequent interruptions of prolonged sitting on self-perceived levels of energy, mood, food cravings and cognitive function. International Journal of Behavioural Nutrition and Physical activity, 13, 113. (Link)

6. Hunter, E., & Wu, C. (2016). Give me a better break: Choosing workday break activities to maximise resource recovery. Journal of Applied Psychology, 101(2), 302-311. (Link)

7. Audiffren, M. (2009). Acute exercise and psychological functions: A cognitive-energetic approach. In McMorris, T., Tomporowski, P., & Audiffren, M. (Eds). Exercise and Cognitive Function (pp. 3-39). Wiley-Blackwell. (Link)

8. Sousa, A., Ahmad, L., Hassan, T., Yuen, K., Douris, P., Zwibel, H., & Di Francisco-Donoghue, J. (2020). Physiological and cognitive functions following a discrete session of competitive eSports gaming. Frontiers in Psychology, 11, 1030. (Link)

9. McMorris, T., Sproule, J., Turner, A., & Hale, B. (2011). Acute, intermediate intensity exercise, and speed and accuracy in working memory tasks: A meta-analysis comparison of effects. Physiology and Behaviour, 102, 421-428. (Link)

10. Perri, R., Berchicci, M., Spinelli, D., & Di Russo, F. (2014). Individual differences in response speed and accuracy are associated to specific brain activities of two interacting systems. Frontiers in Behavioural Neuroscience, 8,(251), 1-12. (Link)

11. McMorris, M. (2009). Exercise and cognitive function: a neuroendocrinological explanation. In McMorris, T., Tomporowski, P., & Audiffren, M. (Eds). Exercise and Cognitive Function (pp. 41-68). Wiley-Blackwell. (Link)

12. Féry, Y., Ferry, A., vom Hofe, A., & Rieu, M. (1997). Effect of physical exhaustion on Cognitive functioning. Perceptual and motor skills, 84, 291-298. (Link)

13. Chmura, J., Krysztofiak, H., Ziemba, A., Nazar, K., & Kaciuba-Uścilko, H. (1997). Psychomotor performance during prolonged exercise above and below the blood lactate threshold. European Journal of Applied Physiology and Occupational Physiology, 77, 77-80. (Link)

14. Audiffren M., & André, N. (2019), The exercise-cognition relationship: A virtuous circle. Journal of Sport and Health Science, 8(4), 339-347. (Link)

15. Irwin, C., Campagnolo, N., Iudakhina, E., Cox, G., & Desbrow, B. (2018). Effects of acute exercise, dehydration and rehydration on cognitive function in well-trained athletes. Journal of Sports Sciences, 36(3), 247-255. (Link)

Modified sprinting biomechanics

Modified sprinting biomechanics

Fifteen years ago I wrote my BSc dissertation on how carrying a pole-vaulting pole affected an athlete’s sprinting kinematics. As well as pole-vaulters there are many athletes who use a modified sprinting model, for example rugby players carrying a ball or amputees who use prosthetic limbs. Since then there have been a number of papers exploring these topics. The purpose of this blog is to try and solidify some of my thoughts on what I’ve been reading.