Brain network activation patterns during a working memory task in basketball athletes
Poster No:
865
Submission Type:
Abstract Submission
Authors:
Yapeng Qi1, Yihan Wang1, Xinwei Li1, Wenxuan Fang1, Xiaoxia Du1
Institutions:
1Shanghai University of Sport, Shanghai, Shanghai
First Author:
Co-Author(s):
Introduction:
Working memory (WM) is a core cognitive function affecting academic and occupational performance. Long-term regular physical activity positively impacts WM in individuals with normal cognitive function and those with cognitive impairment (De Greeff et al., 2018; Deng et al., 2024; Rathore & Lom, 2017). Different sports have different requirements for cognition, and the impact of different types of sports on WM seems to be different as well (Ludyga et al., 2022; Yongtawee et al., 2022). However, how long-term specific exercise training affects WM is still unclear. WM relies on the coordinated activity of multiple brain regions, particularly the dynamic interaction between the task-positive network (TPN) and the default mode network (DMN)(Ishihara et al., 2020; Gordon et al., 2014). We propose the hypothesis that basketball athletes enhance the efficiency of WM by increasing the activation of the TPN and improving cerebellar regulation of the core brain regions associated with working memory.
Methods:
To test this hypothesis, we used an N-back task combined with functional magnetic resonance imaging (fMRI) to investigate brain activity data from 55 college basketball athletes and 55 control subjects matched by age, gender, and education level during a working memory task.
Results:
In terms of behavioral outcomes, basketball players showed faster reaction times, but lower accuracy was lower during 2 back (Figure 1), indicating favoring speed over precision in the speed-accuracy trade-off. Our findings also revealed that during the task, basketball players showed increased activation in TPN areas such as the dorsolateral prefrontal cortex and inferior parietal lobule, alongside reduced inhibitory activity in DMN like the middle temporal gyrus (MTG) and angular gyrus (Figure 2). Notably, the activity intensity in the left MTG of athletes was negatively correlated with their working memory performance. Dynamic causal modeling analysis further demonstrated that athletes exhibited stronger effective connectivity within the TPN, along with an increase in the inhibitory influence of the DMN on the TPN. It is worth highlighting that the cerebellum contributed significantly to the increased activity of the TPN, playing a crucial role in modulating neural network dynamics (Boven et al., 2023).
·Figure 1 Behavior results of N-back task. RT: reaction time; ACC: accuracy; EFF: efficiency of response (ACC/RT).
·Figure 2 Panels A, B, and C show the results of group comparisons under the 0-back, 2-back, and 2-back minus 0-back conditions, respectively.
Conclusions:
Based on our research, long-term basketball training has a distinct impact on working memory. This impact reshaped the athletes' behavior and brain function within working memory. These adaptive changes may help individuals better adapt to the fast pace of basketball games.
Higher Cognitive Functions:
Executive Function, Cognitive Control and Decision Making
Learning and Memory:
Working Memory 1
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI) 2
Novel Imaging Acquisition Methods:
BOLD fMRI
Keywords:
Cognition
FUNCTIONAL MRI
Memory
1|2Indicates the priority used for review
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Provide references using APA citation style.
De Greeff, J. W., Bosker, R. J., Oosterlaan, J., Visscher, C., & Hartman, E. (2018). Effects of physical activity on executive functions, attention and academic performance in preadolescent children: A meta-analysis. Journal of Science and Medicine in Sport, 21(5), 501–507. https://doi.org/10.1016/j.jsams.2017.09.595
Deng, J., Wang, H., Fu, T., Xu, C., Zhu, Q., Guo, L., & Zhu, Y. (2024). Physical activity improves the visual-spatial working memory of individuals with mild cognitive impairment or Alzheimer’s disease: A systematic review and network meta-analysis. Frontiers in Public Health, 12, 1365589. https://doi.org/10.3389/fpubh.2024.1365589
Gordon, E. M., Breeden, A. L., Bean, S. E., & Vaidya, C. J. (2014). Working memory‐related changes in functional connectivity persist beyond task disengagement. Human Brain Mapping, 35(3), 1004–1017. https://doi.org/10.1002/hbm.22230
Ishihara, T., Miyazaki, A., Tanaka, H., & Matsuda, T. (2020). Identification of the brain networks that contribute to the interaction between physical function and working memory: An fMRI investigation with over 1,000 healthy adults. NeuroImage, 221, 117152. https://doi.org/10.1016/j.neuroimage.2020.117152
Ludyga, S., Gerber, M., & Kamijo, K. (2022). Exercise types and working memory components during development. Trends in Cognitive Sciences, 26(3), 191–203. https://doi.org/10.1016/j.tics.2021.12.004
Rathore, A., & Lom, B. (2017). The effects of chronic and acute physical activity on working memory performance in healthy participants: A systematic review with meta-analysis of randomized controlled trials. Systematic Reviews, 6(1), 124. https://doi.org/10.1186/s13643-017-0514-7
Yongtawee, A., Park, J., Kim, Y., & Woo, M. (2022). Athletes have different dominant cognitive functions depending on type of sport. International Journal of Sport and Exercise Psychology, 20(1), 1–15. https://doi.org/10.1080/1612197X.2021.1956570