Change of Cerebral Structural Plasticity of Track Athletes Based on Magnetic Resonance Imaging

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1 Change of Cerebral Structural Plasticity of Track Athletes Based on Magnetic Resonance Imaging Jianping Hu 1, Hongbin Jiang 2, Huawei Liang 1*, Haibing Yang 1 ABSTRACT To understand the influence of athletes' exercise expertise on the brain functions and structures. Using MRI technology, based on voxel morphometry, the differences in brain grey matter structure among 13 badminton players, 13 track athletes and 16 non-athletes were compared. The athletes' volume of grey matter in the bilateral precentral gyrus, left inferior parietal lobe, postcentral gyrus, orbital frontal gyrus, and superior temporal gyrus was significantly greater than those of non-athletes. Compared with track athletes, badminton athletes have significantly increased grey matter volume in the left inferior frontal gyrus, left superior parietal lobe, and left precuneus; Compared with badminton players, track athletes have obvious differences in the volume of grey matter in the inferior temporal gyrus, left middle frontal gyrus, left inferior frontal gyrus, middle part of cingulate gyrus, and the insula, indicating that the cerebral structure of athletes in different sports shows specificity in different sports. Key Words: Plasticity, Voxel Morphology, Sports Items, Cerebral Structure DOI Number: /nq NeuroQuantology 2018; 16(6): Introduction Sport not only requires athletes to have a good sport skill level, but also requires good cognitive abilities. Studies have shown that elite athletes have better cognitive abilities than non-athletes, and that good athletes' good performance is closely related to their cognitive abilities. To understand the differences in the structure and function of the brain between elite athletes and non-athletes in long-term exercise training (Jensen et al., 2001), the development of functional magnetic resonance imaging technology (hereinafter as MRI ) provides us with a tool for measuring the brain structures, so that we can find out that long-term exercise training changes the plasticity of the athlete's brain (Dunn et al., 2001). The human brain is malleable, and its structure changes adaptively as the environment changes. A large number of neuroimaging studies show that the learning of new skills and highintensity exercise training induce changes in the brain structure, even short-term movement learning, such as the 7-day juggling training would cause significant grey matter density changes in brain regions including frontal attention network, middle temporal and hippocampus (Haggard, 2005). For professionals who had went through long-term sport skill exercises, such as athletes and musicians, had all changed obviously in their brain regions (Zhu et al., 2010). For ballet dancers, the grey matter changes in their sensorimotor area and premotor cortex area; compared to the control group, divers increased in their grey matter density in the thalamus and precentral gyrus; high-level golfers have bigger grey matter volume in their prefrontal lobe-parietal lobe network, including premotor cortex area and parietal lobe (Grossman et al., 2001). However, few people have studied the changes Corresponding author: Huawei Liang Address: 1 Henan Polytechnic University, Jiaozuo , 2 China Anyang Institute of Technology, Anyang , China huaweiliang18263@aliyun.com Relevant conflicts of interest/financial disclosures: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Received: 6 March 2018; Accepted: 7 May 2018

2 in brain plasticity caused by experience in the track athletes. Therefore, this study focuses on the differences in the grey matter structure between track athletes and non-athletes. At present, more and more attention has been paid to the influence of athletes' exercise expertise on the function and structure of their brain. Because athletes usually take long term training since they were little, therefore, their brains provide researchers with the opportunity to study the neural structural plasticity of the brain (Hamilton et al., 2006). Research shows that long-term exercise training can cause adaptive changes in the brain's structure. For example, some studies have shown that athletes and nonathletes do not have significant differences in total cerebral volume and cerebellum volume, but longterm training would result in greater cerebellar vermian lobules VI-VII, compared with control group, it s found that divers have obvious increase grey matter density in their thalamus and precentral gyrus. Skilled golfers have a larger grey matter volume in the prefrontal lobe-parietal lobe network, including brain regions in the premotor cortex area and parietal lobe. The influence of different sport types (single confrontation or group confrontation) on brain structure has received less concern (Massidda et al., 2011). On the one hand, both the single-confrontation and group-confrontation programs have high requirements on the athletes' sport skills and visual perception, long-term sports training can cause the athlete's brain to produce similar plasticity changes and have commonalities; on the other hand, since single-confrontation and groupconfrontation sports have different sports environment, their requirements for cognitive ability and cognitive style are also different, longterm training will result in different brain structures of different types of athletes. This hypothesis suggests that the brain structure of different types of sports athletes is both commonality and specificity, and these two should be grasped during exercise training to improve scientific training. Methods Goals 13 national level-2 track athletes, 13 national level-2 badminton players and 13 age-matched non-athletes participated in the study. All subjects were right-handed men (Kuang KSC et al., 2005). The athletes were recruited from the track team and badminton team of Shanghai University of Sport. The average age of the track athletes was 19.6±1.3 years, the average training period was 6.4±1.9 years, the average age of the badminton players was 20.2±1.0 years, and the average training period was 7.8±2.4 years. Non-athletes were all ordinary college students of Shanghai University of Sport, they did not receive professional training in track and field, badminton or other programs, their average age was 19.3±1.8 years. All subjects were healthy and had normal vison or corrected vision. This experiment was a single-blind experiment. The test procedure was approved by the ethics committee of the school. The ethical committee charter of the school was consistent with the ethical standards of the Helsinki Declaration of All subjects signed informed consent forms. Equipment This experiment was completed in the functional magnetic resonance imaging center of East China Normal University. Using Siemens 3.0T whole body MRI system, the brain structures of three groups of subjects were collected. The scan sequence is a T1-weighted 3-dimensional gradient echo sequence with scan parameters: TR=2530ms; TE=2.34ms; FA=7 ; FOV=100mm; pixel matrix= Structure image preprocessing The structure image was analyzed using VBM technology. With this technology, we can perform full-automatic calculation and analysis of global or local brain grey matter volume differences. This study uses the SPM8-based VBM8 toolkit to preprocess the structure images under the MATLAB platform. The pretreatment process includes: 1) Matching the original image to the standard template of the Montreal Neurological Institute (MNI), and then cutting the standardized image into 3 kinds: grey matter, white matter and cerebrospinal fluid according to the template. The grey matter, white matter, and cerebrospinal fluid images of all subjects were averaged to form new grey matter, white matter, and cerebrospinal fluid templates. 2) According to the grey matter, white matter, and cerebrospinal fluid templates created in the previous step, the original image is again standardized. In this way, the entry of extracerebral voxels is avoided so that optimal spatial standardization of grey matter and white matter can be achieved. After the standardization is completed, according to the template, continue the image cutting to form images of grey matter, 759

3 Table 1. Study of the difference of grey matter between the 3 groups of badminton players, track athletes and non-athletes Orbital frontal gyrus (BA11) R Midline gyrus (BA25) L Lower frontal gyrus (BA47) R Lower frontal gyrus (BA47) L Anterior wedge (BA47) L Table 2. Study of grey matter difference between badminton players and non-athletes Precentral gyrus (BA11) R Orbital frontal gyrus (BA25) L Upper frontal gyrus (BA47) R Inferior parietal lobule/superior temporal gyrus (BA47) L Anterior wedge (BA47) L white matter, and cerebrospinal fluid. 3) The segmented grey matter image is smoothed, and the parameter is FWHM (Full Width Half Maximum) =6mm. After VBM preprocessing, highresolution anatomical images (voxel size, 1 mm3) were obtained, so that the local variance analysis can be conducted to the grey matter in the whole brain. Statistical analysis By the single factor analysis of variance in SPM8, we can compare the differences in grey matter volume between the three groups (P<0.001, Voxel>10, uncorrected), and then compare each two of the three groups of subjects separately to find local grey matter differences between each two groups (P<0.001, Voxel>10, uncorrected), then joint analysis was used to find out the common activation brain regions of badminton players> non-athletes and track athletes> nonathletes, so as to reflect the similar influence of long-term badminton sport or field sport on the brain structures of the athletes. The selection criterion is: in the above two comparisons, the brain regions with P<0.01 and Voxel>10 are selected, and the statistical results are finally displayed on the 3D image of the standard space (MNI). Results and discussion Variance of brain structures differences of the 3 groups of badminton players, track athletes and non-athletes The results showed that there was a significant difference in grey matter volume in the brain regions of the right orbital frontal gyrus, left midline frontal gyrus, bilateral inferior frontal gyrus, and the left cuneus in the 3 groups of subjects (Table 1, Figure 1). Main differences in the grey matter between badminton players and non-athletes The each-two comparison between the badminton players and non-athletes shows that, compared to non-athletes, badminton players have obvious increase in the grey matter volume in the right precentral gyrus, right orbit frontal gyrus, left superior frontal gyrus, left inferior parietal lobe, and left precuneus (Table 2, Figure 2). Figure 1. a Schematic diagram of grey matter differences between 3 groups of badminton players, Track players and non-athletes Figure 2. a Schematic diagram of grey matter difference between badminton players and non-athletes 760

4 Table 3. A list of grey matter differences between track athletes and non-athletes Orbital frontal gyrus (BA11) R Inferior lobule/insula (BA25) L Superior temporal gyrus (BA47) R Precentral gyrus (BA47) L Anterior wedge (BA47) L Main differences in grey matter between athletes and non-athletes Further, in the full-factor analysis, the difference in grey matter between track athletes and nonathletes was compared. It was found that the athlete's grey matter volume in the right orbital frontal gyrus, left inferior parietal lobe, left superior temporal gyrus, left precentral gyrus and left insula (Table 3, Figure 3). Figure 3. Sketch map of grey matter difference between track athletes and non-athletes Experimental results The results showed that the volume of grey matter in the left and right cerebellum and left and right inferior frontal gyrus of the track athletes was significantly higher than that of nonathletes (p<0.001, k>10 voxels). Studies have shown that the cerebellum plays an important role in the process of skill learning, including hand-eye coordination and two-hand coordination. There are also studies that demonstrate the link between the practice of complex motor skills and the cerebellar plasticity. Musicians have a larger cerebellum volume than non-musicians, and the size of the cerebellum volume is positively related to the time of music practice. Research on basketball players and badminton players also shows that basketball players and badminton players have larger cerebellar grey matter than non-athletes. In the track and field sport, it requires athletes to have high limb coordination abilities. Conclusion and outlook The purpose of this study is to explore the common parts of brain structure differences between athletes of different sports relative to the general population, and the difference in brain structure between athletes of different sports, so as to find out the plasticity changes that the longterm sports training produces for the athletes' brains. The main findings of this study were as follows: 1: compared with non-athletes, the badminton group has significant increase in the volume of grey matter in the right precentral gyrus, orbit frontal gyrus, left superior frontal gyrus, left inferior parietal lobe, and left precuneus; compared with non-athletes, the track athlete group has a significant increase in the volume of grey matter in the right orbital frontal gyrus, left inferior parietal lobe, left middle temporal gyrus, left precentral gyrus and left insula. Through the analysis, the common activation brain regions of badminton players> non-athletes and track athletes> non-athletes were found, and it s found that, in the bilateral precentral gyrus, left inferior parietal lobe, right postcentral gyrus, right orbital frontal gyrus, and left superior temporal gyrus, the volume of grey matter obviously increases. 2: Compared to the track athlete group, the badminton player group has obvious increase in the grey matter in the left inferior frontal gyrus, left superior parietal lobe, and left precuneus; compared to the badminton players, the track athletes have significant difference in the grey matter volume in the inferior temporal gyrus, left middle frontal gyrus, and insula. Acknowledgements Boosting plan for innovative team in the field of philosophy and social sciences in Henan institutions of higher learning(2017-cxtd-03) References Dunn AR, Dmochowski IJ, Bilwes AM, Gray HB, Crane BR. Probing the open state of cytochrome P450cam with ruthenium-linker substrates. Proceedings of the National Academy of Science 2001; 98(22): Grossman E, Blake R. Brain activity evoked by inverted and imagined motion. Vision Res 2001; 41(10-11): Haggard P. Conscious intention and motor cognition. Trends in Cognitive Sciences 2005: 9(6):

5 Hamilton AF, Grafton ST. Goal representation in human anterior intraparietal sulcus. Journal of Neuroscience 2006; 26(4): Jensen EJ, Pfister L, Ackerman AS, Tabazadeh A, Toon OB. A conceptual model of the dehydration of air due to freezedrying by optically thin, laminar cirrus rising slowly across the tropical tropopause. Journal of Geophysical Research Atmospheres 2001; 106(D15): Kuang KSC, Zhang L, Cantwell WJ, Bennion I. Process monitoring of aluminum-foam sandwich structures based on thermoplastic fibre metal laminates using fibre Bragg gratings. Composites Science & Technology 2005: 65(3 4): Massidda M, Vona G, Calo CM. Lack of association between ACE gene insertion/deletion polymorphism and elite artistic gymnastic performance of Italian gymnasts. European Journal of Sport Science 2011; 11(3): Zhu Y, Murali S, Cai W, Li X, Suk JW. Graphene and Graphene Oxide: Synthesis, Properties, and Applications. Advanced Materials 2010; 22(45):