Interceptive sports exhibit stronger connectivity strength in the frontoparietal network during rest

2078 

Abstract Submission 

Zai-Fu Yao¹

¹College of Education, National Tsing Hua University, East, Hsinchu

Zai-Fu Yao  
College of Education, National Tsing Hua University
East, Hsinchu

Certain sports, such as badminton and table tennis, are considered "interceptive" and require athletes to have rapid response times and precise motor control, which can lead to unique brain network adaptations. These adaptations can manifest as altered neural network patterns, which can be observed using neuroimaging techniques. Previous studies have indicated that athletes have enhanced neural efficiency, but the relationship between years of training and alterations in resting-state networks (RSNs) has not been extensively studied. Therefore, the aim of this study is to investigate the resting-state brain networks of professional badminton and table tennis players and compare them to healthy controls to understand the neural basis of interceptive sports expertise. We hypothesize that athletes in interceptive sports have distinct resting-state network (RSN) patterns compared to healthy controls, due to their specialized training and sensory-motor demands. Specifically, we expect to see enhanced connectivity within the frontoparietal network, which has a crucial role in attentional processes and motor planning. This enhanced connectivity may be correlated with the athletes' years of training, indicating a dose-response relationship between training duration and neural adaptations. Additionally, we anticipate distinct patterns in dorsal and ventral stream processing, aligning with the two-stream theory of visual processing. By examining these patterns, we hope to gain a deeper understanding of the neural basis of expertise in interceptive sports.

The study included 20 athletes, 10 males and 10 females, with an equal number of players from each sport, and 10 healthy individuals that matched the athletes. Resting-state functional MRI (fMRI) data was collected from all participants to analyze the brain networks involved in motor and visual processing. The initial analysis involved a whole-brain independent component analysis (ICA) used to identify resting-state networks. The ICA identified several resting-state networks, including the default mode network, the dorsal attention network, and the salience network. Subsequently, graph theoretical network metrics were employed to quantify network properties such as connectivity strength, efficiency, and modularity. The analysis used the identified resting-state networks to investigate the topological organization of the brain networks. Effective connectivity, especially dynamic causal modeling, was used to investigate the interaction between different brain networks. The analysis utilized rs-fMRI data, which were collected and preprocessed using standard techniques such as motion correction, spatial smoothing, and normalization. The study focused specifically on the dorsal and ventral streams of visual processing. Network masks derived from brain atlases were used to isolate these streams and compare their connectivity patterns between athletes and controls. Finally, correlational analyses were conducted to determine the relationship between years of training and changes in network metrics.

We observed enhanced connectivity in the frontoparietal network among the athlete group, potentially indicating a neural adaptation to the demands of interceptive sports. This would suggest that interceptive sports expertise is associated with enhanced cognitive control and visuospatial processing capabilities at rest. Differences in the dorsal and ventral stream connectivity also emerged, supporting the two-stream hypothesis in the context of sports expertise.

This study aims to elucidate the neural basis of expertise in interceptive sports. By examining resting-state fMRI data, we anticipate revealing significant differences in brain connectivity patterns between athletes and non-athletes, potentially contributing to our understanding of neural plasticity in response to specialized training.

Connectivity (eg. functional, effective, structural)

fMRI Connectivity and Network Modeling ²

Visuo-Motor Functions ¹

Anatomy and Functional Systems

BOLD fMRI

fMRI CONTRAST MECHANISMS

FUNCTIONAL MRI

Motor

NORMAL HUMAN

Plasticity

Segmentation

Sub-Cortical

Vision