Share：
Share this content in WeChat
X
[Chinese][PDF]1624129
• Original Article •
Regional homogeneity of resting state brain functional activities during Tai Chi Chuan learning
WANG Xuefei  YIN Dazhi  LI Lin  XU Guojun  YU Qiurong  ZHAN Shuang  GUO Miao  ZHANG Xiaoyou  FAN Mingxia 

Cite this article as: Wang XF, Yin DZ, Li L, et al. Regional homogeneity of resting state brain functional activities during Tai Chi Chuan learning[J]. Chin J Magn Reson Imaging, 2021, 12(6): 51-56. DOI:10.12015/issn.1674-8034.2021.06.010.


[Abstract] Objective To explore regional homogeneity (ReHo) changes during different learning stages of Tai Chi Chuan (TCC) by using resting-state function magnetic resonance imaging (rs-fMRI). Materials andMethods Within-subject design, 18 TCC novices were performed two repeatedly rs-fMRI at the beginning learning phase of TCC (2 weeks) and 14 weeks of TCC learning, respectively. Then the whole brain ReHo values of the subjects were calculated and the statistical analysis was conducted.Results Compared with 2 weeks of TCC learning, ReHo values of the right fusiform gyrus significantly increased, while ReHo values of the right cerebellum and left superior parietal lobule significantly decreased (P＜0.05, AlphaSim corrected) at 14 weeks of TCC learning; and there was a significant negative correlation between the changed ReHo values in the right cerebellum and the increments of TCC skill scores (r=-0.507, P=0.032). Multiple regression analysis showed that, at 2 weeks of TCC learning, ReHo values of the right middle temporal gyrus and right anterior cingulate were positively correlated with the increments of TCC skill scores (r=0.908, 0.818, P＜0.01, respectively), while ReHo values of the left occipital gyrus and right superior temporal gyrus were negatively correlated with the increments of TCC skill scores (r=-0.474, P＜0.05; r=-0.824, P＜0.01, respctively).Conclusions The results suggest that ReHo of resting state functional activities changed, along with TCC learning skills improvements, reflecting brain plasticity. In addition, the ReHo values of some brain regions in the early stage of TCC learning may possibly have potential role in predicting the learning effects of TCC skills.
[Keywords] Tai Chi Chuan；regional homogeneity；resting-state functional magnetic resonance imaging；multiple regression analysis

WANG Xuefei1   YIN Dazhi2   LI Lin3   XU Guojun1   YU Qiurong1   ZHAN Shuang1   GUO Miao1   ZHANG Xiaoyou3   FAN Mingxia1*  

1 Shanghai Key Laboratory of Magnetic Resonance, Department of Physics, East China Normal University, Shanghai 200062, China

2 School of Psychology and Cognitive science, East China Normal University, Shanghai 200062, China

3 School of Physical Education and Health, East China Normal University, Shanghai 200062, China

Fan MX, E-mail: mxfan@phy.ecnu.edu.cn

Conflicts of interest   None.

This work was part of Key Projects of National Natural Science Foundation of China (No. 11835003).
Received  2021-03-05
Accepted  2021-04-06
DOI: 10.12015/issn.1674-8034.2021.06.010
Cite this article as: Wang XF, Yin DZ, Li L, et al. Regional homogeneity of resting state brain functional activities during Tai Chi Chuan learning[J]. Chin J Magn Reson Imaging, 2021, 12(6): 51-56. DOI:10.12015/issn.1674-8034.2021.06.010.

1
Hu X, Lai Z, Wang L. Effects of Taichi exercise on knee and ankle proprioception among individuals with knee osteoarthritis[J]. Res Sports Med, 2020, 28(2): 268-278. DOI: 10.1080/15438627.2019.1663520.
2
Arienti C, Lazzarini SG, Pollock A, et al. Rehabilitation interventions for improving balance following stroke: An overview of systematic reviews[J]. PLoS One, 2019, 14(7): 1-23. DOI: 10.1371/journal.pone.0219781.
3
Tarsha MS, Park S, Tortora S. Body-centered interventions for psychopathological conditions: A review[J]. Front Psychol, 2020, 10: 2907. DOI: 10.3389/fpsyg.2019.02907.
4
Chang Y. Reorganization and plastic changes of the human brain associated with skill learning and expertise[J]. Front Hum Neurosci, 2014, 8: 35. DOI: 10.3389/fnhum.2014.00035
5
Zang Y, Jiang T, Lu Y, et al. Regional homogeneity approach to fMRI data analysis[J]. Neuroimage, 2004, 22(1): 394-400. DOI: 10.1016/j.neuroimage.2003.12.030.
6
Zhang L, Qiu F, Zhu H, et al. Neural efficiency and acquired motor skills: An fMRI study of expert athletes[J]. Front Psychol, 2019, 10: 2752. DOI: 10.3389/fpsyg.2019.02752.
7
Salvia E, Tissier C, Charron S, et al. The local properties of bold signal fluctuations at rest monitor inhibitory control training in adolescents[J]. Dev Cogn Neurosci, 2019, 38: 100664. DOI: 10.1016/j.dcn.2019.100664.
8
Debarnot U, Sperduti M, Di Rienzo F, et al. Experts bodies, experts minds: How physical and mental training shape the brain[J]. Front Hum Neurosci, 2014, 8(2): 280. DOI: 10.3389/fnhum.2014.00280.
9
Sendhilnathan N, Semework M, Goldberg ME, et al. Neural correlates of reinforcement learning in mid-lateral cerebellum[J]. Neuron, 2020, 106(1): 188-198. DOI: 10.1016/j.neuron.2019.12.032.
10
Ashida R, Cerminara NL, Edwards RJ, et al. Sensorimotor, language, and working memory representation within the human cerebellum[J]. Hum Brain Mapp, 2019, 40(16): 4732-4747. DOI: 10.1002/hbm.24733.
11
Bernard JA, Seidler RD. Cerebellar contributions to visuomotor adaptation and motor sequence learning: an ALE meta-analysis[J]. Front Hum Neurosci, 2013, 7(1): 27. DOI: 10.3389/fnhum.2013.00027.
12
Doyon J, Song AW, Karni A, et al. Experience-dependent changes in cerebellar contributions to motor sequence learning[J]. Proc Natl Acad Sci U S A, 2002, 99(2): 1017-1022. DOI: 10.1073/pnas.022615199.
13
Cantou P, Platel H, Desgranges B, et al. How motor, cognitive and musical expertise shapes the brain: Focus on fMRI and EEG resting-state functional connectivity[J]. J Chem Neuroanat, 2018, 89: 60-68. DOI: 10.1016/j.jchemneu.2017.08.003.
14
Berlot E, Popp NJ, Diedrichsen J. A critical re-evaluation of fMRI signatures of motor sequence learning[J]. Elife, 2020, 9: 1-24. DOI: 10.7554/eLife.55241.
15
Brown RM, Penhune VB. Efficacy of auditory versus motor learning for skilled and novice performers[J]. J Cogn Neurosci, 2018, 30(11): 1657-1682. DOI: 10.1162/jocn_a_01309.
16
Jung D, Park JW, Kim YH, et al. Neuroplastic and motor behavioral changes after intermanual transfer training of non-dominant hand: A prospective fMRI study[J]. NeuroRehabilitation, 2019, 44(1): 25-35. DOI: 10.3233/NRE-182550.
17
Brams S, Ziv G, Levin O, et al. The relationship between gaze behavior, expertise, and performance: A systematic review[J]. Psychol Bull, 2019, 145(10): 980-1027. DOI: 10.1037/bul0000207.
18
Gauthier I, Skudlarski P, Gore JC, et al. Expertise for cars and birds recruits brain areas involved in face recognition[J]. Nat Neurosci, 2000, 3(2): 191-197. DOI: 10.1038/72140.
19
Wong AC, Palmeri TJ, Rogers BP, et al. Beyond shape: how you learn about objects affects how they are represented in visual cortex[J]. PLoS One, 2009, 4(12): 1-7. DOI: 10.1371/journal.pone.0008405.
20
Apps MA, Balsters JH, Ramnani N. The anterior cingulate cortex: monitoring the outcomes of others' decisions[J]. Soc Neurosci, 2012, 7(4): 424-435. DOI: 10.1080/17470919.2011.638799.
21
Bush G, Luu P, Posner MI. Cognitive and emotional influences in anterior cingulate cortex[J]. Trends Cogn Sci, 2000, 4(6): 215-222. DOI: 10.1016/s1364-6613(00)01483-2.
22
Brewer JA, Worhunsky PD, Gray JR, et al. Meditation experience is associated with differences in default mode network activity and connectivity[J]. Proc Natl Acad Sci U S A, 2011, 108(50): 20254-20259. DOI: 10.1073/pnas.1112029108.
23
Visser M, Jefferies E, Embleton KV, et al.Both the middle temporal gyrus and the ventral anterior temporal area are crucial for multimodal semantic processing: distortion-corrected fMRI evidence for a double gradient of information convergence in the temporal lobes[J]. J Cogn Neurosci, 2012, 24(8):1766-1778. DOI: 10.1162/jocn_a_00244.
24
Karpati FJ, Giacosa C, Foster NE, et al. Dance and the brain: a review[J]. Ann N Y Acad Sci, 2015, 1337: 140-146. DOI: 10.1111/nyas.12632.
25
Ono Y, Nomoto Y, Tanaka S, et al. Frontotemporal oxyhemoglobin dynamics predict performance accuracy of dance simulation gameplay: temporal characteristics of top-down and bottom-up cortical activities[J]. Neuroimage, 2014, 85(1): 461-470. DOI: 10.1016/j.neuroimage.2013.05.071.
26
Gallivan JP, Goodale MA. The dorsal "action" pathway[J]. Handb Clin Neurol, 2018, 151: 449-466. DOI: 10.1016/B978-0-444-63622-5.00023-1.
27
Raichlen DA, Bharadwaj PK, Fitzhugh MC, et al. Differences in resting state functional connectivity between young adult endurance athletes and healthy controls[J]. Front Hum Neurosci, 2016, 10: 610. DOI: 10.3389/fnhum.2016.00610.

PREV Changes of positive and negative network connectivity related to hand knob area after stroke: A rs-fMRI study
NEXT Abnormal brain network topology during non-rapid eye movement sleep and its correlation with cognitive behavioral abnormalities in narcolepsy type 1
  


LINK


Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn