![]() The Potential for Change Did you know that with regular practice of activities aimed at training the brain, it is possible to improve working memory (Klingberg, 2010), visual processing (Willis et al., 2006), control of attentional resources (Burge et al., 2013), and stress-response resiliency (Witt, 1980)? Brain training or cognitive training (CT), is typically used in medical settings for improving cognitive functioning in traumatic brain injury patients for example. However, CT is being used in other settings, such as sports. Sports Performance is Cognitively Demanding Playing any sport requires a high demand of cognitive functioning including, but not limited to, decision making, working memory, visual and perceptual processing, motor functioning, and divided attention. In moments of normal gameplay, the amount of brain processing needed to evaluate, act, and perform optimally for every possible situation is astronomical. Moreover, players frequently encounter high-pressure situations where stress-response regulation can be crucial to performance outcomes (Eysenck and Wilson, 2016). With this in mind (no pun intended), take a moment and try to place yourself inside the head of a competitive soccer player; say Lionel Messi for example. At all moments in time on the field, Messi must be aware of his positioning relative to the current and projected state of the ball, his teammates, and the position of his opponents. This is only the start of the mental juggling act needed to be an effective player. Of course, Messi must also act on these thought-processes repeatedly, which requires precise split-second decision-making. In fact, one judgment error or slight hesitation can be a catalyst to a domino effect of miscalculations likely leading to an opponent goal or missed offensive opportunity. So, when it comes to training, the traditional practice paradigm may be enough to improve a player’s physical performance and technical skills, but there’s clearly a mental facet to the game that needs to be considered. Current CT Applications in the Sports Field There are several companies producing commercial CT solutions aimed at specifically improving sports performance, such as Axon Sports, FITLIGHT, and NeuroTracker, to name a few. Interestingly, the utilization of CT in the professional sports realm is very present. For instance, NeuroTracker, has an extensive clientele list with teams from the NFL and Premier league bought in, with research supporting their efficacy. One such study used a 3-dimensional multiple object tracking (3D-MOT) task which required participants to track and recall multiple moving objects in a changing visual field (Romeas, Guldner, and Faubert, 2016). The concept behind this task is that it may actually simulate the cognitive processing occurring in Messi’s head when he’s evaluating his surroundings on the field. In the study, the effects of training for 19 male soccer players were examined across the three groups (3D-MOT, passive, and active control). The 3D-MOT group trained twice per week for 5 weeks, whereas the active control watched 3D soccer videos and partook in engaging interviews, and the passive control received no treatment for the evaluations. Interestingly, the 3D-MOT trained group improved by 15% in a measure of on-field passing decision-making. However, there were no improvements in shooting or passing accuracy, which underscores the potential lack of transfer effect to similar yet different tasks (Walton et al., 2018). Moreover, another study found that while participants improved significantly in the training task post-training, no evidence was found for near transfer (to another object tracking task) or for a far transfer task (a driving task that required recalling specific locations) (Harris et al., 2020). This concept of transferring training to the specific performance task is a major talking-point in terms of the efficacy of CT applications. Transfer of training refers to the generalization of skills attained from training which are then applied to different tasks and domains. One way transfer tasks are categorized is by how near or far they are from the training task, in other words, the closer the transfer task resembles the training task the nearer the transfer. Unsurprisingly, the likelihood of transfer effects is directly related to the degree to which the transfer task resembles the training task, thus near transfer is much more commonly seen (Sala et al., 2019). Sport-based CT is no exception to this phenomenon. The far transfer of CT on sports performance is especially difficult given that sports are highly variable with many factors that ultimately contribute to the success or demise of a player (e.g., natural performance variances, nutrition, emotional state, sleep deprivation, etc.) (Walton et al., 2018). For example, measuring win/loss ratios (e.g., season performance) may be an appealing metric for CT transfer, but again there are so many factors that play into a team's success it’s difficult to single out CT as the affective variable. What Do You Think? Put yourself in the mind of a coach (yes, I’m sorry, you are officially no longer Messi). Now, consider the following: Would you pay for a CT product that may or may not transfer successfully to the pitch? If it were me, I just might, as it’s a pretty neat concept. That said, I think it’s clear that researchers in the field of CT and developers of these systems should continue to make collaborative efforts to better understand and evaluate the transfer effects of training tasks to real-world performance outcomes. Eventually, with the advent of innovative training designs and accurate ways to determine their effectiveness, I believe CT will not only hold its own in the sports realm, but also in a variety of other settings. Sources
Burge, W. K., Ross, L. A., Amthor, F. R., Mitchell, W. G., Zotov, A., & Visscher, K. M. (2013). Processing speed training increases the efficiency of attentional resource allocation in young adults. Frontiers in Human Neuroscience, 7, 684. De Witt, D. J. (1980). Cognitive and biofeedback training for stress reduction with university athletes. Journal of Sport and Exercise Psychology, 2(4), 288-294. Eysenck, M. W., & Wilson, M. R. (2016). Sporting performance, pressure and cognition 14. An introduction to applied cognitive psychology. Harris, D. J., Wilson, M. R., Smith, S. J., Meder, N., & Vine, S. J. (2020). Testing the Effects of 3D Multiple Object Tracking Training on Near, Mid and Far Transfer. Frontiers in Psychology, 11, 196. Klingberg, T. (2010). Training and plasticity of working memory. Trends in cognitive sciences, 14(7), 317-324. Perceptual-Cognitive Training Solution. (2020, March 27). Retrieved June 26, 2020, from https://neurotracker.net/ Ping, J., Liu, Y., & Weng, D. (2019, March). Comparison in depth perception between Virtual Reality and Augmented Reality systems. In 2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR) (pp. 1124-1125). IEEE. Romeas, T., Guldner, A., & Faubert, J. (2016). 3D-Multiple Object Tracking training task improves passing decision-making accuracy in soccer players. Psychology of Sport and Exercise, 22, 1-9. Sala, G., Aksayli, N. D., Tatlidil, K. S., Tatsumi, T., Gondo, Y., & Gobet, F. (2019). Near and far transfer in cognitive training: A second-order meta-analysis. Collabra: Psychology, 5(1). Simons, D. J., Boot, W. R., Charness, N., Gathercole, S. E., Chabris, C. F., Hambrick, D. Z., & Stine-Morrow, E. A. (2016). Do “brain-training” programs work?. Psychological Science in the Public Interest, 17(3), 103-186. Walton, C. C., Keegan, R. J., Martin, M., & Hallock, H. (2018). The potential role for cognitive training in sport: more research needed. Frontiers in psychology, 9, 1121. Willis, S. L., Tennstedt, S. L., Marsiske, M., Ball, K., Elias, J., Koepke, K. M., ... & Wright, E. (2006). Long-term effects of cognitive training on everyday functional outcomes in older adults. Jama, 296(23), 2805-2814.
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