جفت کردن حرکت با تصویر سازی (تصویرسازی حرکتی پویا) به عنوان یک افق جدید برای تمرین تصویر سازی حرکتی و تاثیر آن بر یادگیری و عملکرد، مطالعه موردی: شوت فوتبال

نوع مقاله : مطالعه پژوهشی اصیل

نویسندگان

1 کارشناسی ارشد یادگیری و کنترل حرکتی دانشگاه ارومیه، ارومیه، ایران

2 گروه یادگیری و کنترل حرکتی دانشکده علوم ورزشی دانشگاه ارومیه، ارومیه، ایران

چکیده

هدف: مطالعه حاضر با هدف تعیین تاثیر تصویرسازی حرکتی پویا بر تناسب زمانی، یادگیری و عملکرد مهارت شوت فوتبال اجرا شد.
مواد و روش ها: روش پژوهش نیمه تجربی و از نوع طرح پیش آزمون ـ پس آزمون و آزمون یادداری با گروه کنترل بود. بدین‌منظور، 45 پسر دانشجوی دانشگاه ارومیه به روش نمونه دسترس و براساس معیارهای ورود، به‌صورت هدفمند انتخاب شدند. سپس به تعداد مساوی در سه گروه تمرین جسمانی (کنترل)، تصویرسازی حرکتی ایستا (sMI) و تصویرسازی حرکتی پویا (dMI) قرار گرفتند. مداخله به‌ مدت 12 جلسه (4 جلسه در هفته و هر جلسه 2 ساعت) اجرا شد. گروه تمرین جسمانی بر اساس پروتکل فقط مهارت شوت را بصورت فیزیکی تمرین کرد، گروه تصویرسازی حرکتی ایستا بعد انجام فیزیکی مهارت بعد از آرام سازی بصورت ایستاده به تصویرسازی ذهنی پرداختند و در نهایت گروه تصویرسازی حرکتی پویا بعد انجام مهارت شوت بصورت جسمانی و آرام سازی بصورت ایستاده و در حالی که درجا پاهای خود را تکان می دادند، به تصویرسازی پرداختند، برای ارزیابی مهارت دریبل از آزمون مهارت شوت فوتبال مور-کریستین و برای ارزیابی توانایی تصویرسازی حرکتی از پرسشنامه تجدید نظر شده MIQ-R استفاد شد.
یافته ها:  نتایج نشان داد کیفیت شوت و زمانبندی کلی MI  با تمرین فیزیکی متناسب می گردد، افزایش روی عملکرد و یادگیری dMI  نسبت به sMI درسطح معناداری گزارش شد و  همبستگی مثبتی وجود دارد.
نتیجه گیری:  . در نهایت با در نظر داشتن یافته‌های پژوهش می‌توان نتیجه گرفت استفاده از dMI نسبت به sMI در محیط های آموزشی و ورزشی توصیه می گردد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Pairing Movement with Imagery (Dynamic Motor Imagery) as a New Horizon for Movement Imagery Practice and its Impact on Learning and Performance, Case Study: Soccer Shot

نویسندگان [English]

  • saeed naghizadeh 1
  • hassan Mohammadzadeh 2
1 Master's degree in Motor Learning and Control, Faculty of Sports Sciences, Urmia University, Urmia, Iran.
2 Department of Motor Learning and Control, Faculty of Sports Sciences, Urmia University, Urmia, Iran
چکیده [English]

Background and Purpose
Motor imagery (MI) is the mental representation of an action without physically performing the corresponding movement. Experimental data have shown that motor imagery helps improve motor performance in both sports motor skills and daily life motor skills (Schuster, 2011; O'Shea and Moran, 2017). MI and physical exercise use a similar neural substrate, although the respective neural networks do not completely overlap, thus supporting the principle of functional balance (Lutze and Halsband, 2006; Guillot, 2008). This study aimed to determine whether dynamic motor imagery (dMI) affects movement learning and performance to a greater extent than static motor imagery (sMI), and to achieve a temporal fit between MI and practice, emphasizing physicality, learning, and movement performance.
Materials and Methods
A sample of male amateur football player students was selected for the experiment. Forty-five healthy right-footed amateur athletes aged 18 to 20 years (mean age: 19 ± 0.7 years) participated in this research, approved by the research ethics committee of the faculty. All athletes had been playing soccer as amateurs for 6 to 8 years. They had no injuries and were examined by the Pathology and Corrective Movement Association of the faculty for any skeletal abnormalities, especially in the legs, and were found to be normal. They were then divided into three groups: physical training (PP), sMI, and dMI using the MIQ-R questionnaire. Weight, age, and motor imaging strength were homogeneous and normal. The football shooting training protocol used was the Moore-Christian test.
 
Figure 1: Moore-Christian soccer shot test
All subjects participated in a 3-week training period with 4 sessions per week. All groups underwent a pre-test, and their scores were recorded. During the training period, the PP group practiced the training protocol only. The sMI group, after training and relaxation, stood behind the starting line and started imaging. The dMI group, after training and relaxation, jumped up and ran towards the hitting line, standing as if they were shooting, and then started to visualize. After completing the training period, subjects participated in a post-test and a retention test after 24 hours, with scores recorded. Performance during these tests was evaluated by two judges using video recordings, who were blinded to the training conditions and study purpose.
Results
Results showed that the quality of shots and overall timing of MI aligns proportionally with physical exercise, with a significant increase in performance and learning reported for dMI compared to sMI at a meaningful level, and a positive correlation was found.
Conclusion
The results of this study support the benefits of using dMI compared to sMI, showing an increased impact on performance and learning at a significant level with a positive correlation. The findings provide evidence that associating MI with actual movements, as in dMI, results in a better temporal fit between MI and physical action than imagery without movement, indicating greater temporal accuracy. Fusco et al. (2021) investigated the effects of dMI in athletes with vision differences and confirmed the superiority of dMI over sMI in terms of temporal characteristics. dMI provides time cues that likely enhance the preparation phase before execution. This temporal precision results from mentally reproducing movement subsequences associated with temporal cues, providing athletes with a temporal fit essential for performance. The study also showed that pairing MI with real motion leads to a higher rate of successful shots compared to MI without motion. Expert ratings on shot quality support the benefits of the dMI condition, confirming that MI is useful for skills requiring simple movements like shooting. The findings also suggest that MI can enhance internalization and adjustment of approach, critical for performance. The judges' reports indicated that shot quality and timing with MI were proportional to physical training.
Funding
This study has not received any financial support from funding organizations in the public, commercial, or non-profit sectors.
Authors' contributions
The authors have equally contributed to all the study sections.
Conflicts of Interest
The authors declared no conflict of interest.
 
 
 

کلیدواژه‌ها [English]

  • dynamic motor imagery (dMI)
  • static motor imagery (sMI)
  • Moore-Christian soccer shot test
  1. Boschker MSJ, Bakker FC, Rietberg MB. (2000). Retroactive interference effects of mentally imagined movement speed. J Sports Sci, 18:593–603. https://doi.org/10.1080/02640410050082305
  2. Callow N, Roberts R, Fawkes JZ. (2006). Effects of dynamic and static imagery on the vividness of imagery, skiing performance and confidence. J Im Res Sport Phys Act, 1:1–13. https://doi.org/10.2202/1932-0191.1001
  3. Chu M, Kita S. (2011). The nature of gestures’ beneficial role in spatial problem solving. J Exp Psychol Gen, 140:102–116. https://doi.org/10.1037/a0021790
  4. Collet C, Guillot A, Lebon F, MacIntyre T, Moran A. (2011). Measuring motor imagery using psychometric, behavioral, and psychophysiological tools. Exerc Sport Sci Rev, 39:85–92 https://doi.org/10.1097/jes.0b013e31820ac5e0
  5. Collet C, Guillot A. (2009). Peripheral responses elicited by motor imagery: a window on central and peripheral nervous system relationships related to motor inhibition. In Cognitive Psychology Research Developments. Edited by Penat HO, Weingarten SP. New York: Nova Science Publisher; 245–259
  6. Collet, C., Hajj, M. E., Chaker, R., Bui-Xuan, B., Lehot, J. J., & Hoyek, N. (2021). Effect of motor imagery and actual practice on learning professional medical skills. BMC Medical Education, 21(1), 59. https://doi.org/10.1186/s12909-020-02424-7
  7. Dodakian, L., Stewart, J. C., & Cramer, S. C. (2014). Motor imagery during movement activates the brain more than movement alone after stroke: A pilot study. Journal of Rehabilitation Medicine, 46(9), 843–848. https://doi.org/10.2340/16501977-1844
  8. Driskell, J. E., Copper, C., & Moran, A. (1994). Does mental practice enhance performance? Journal of Applied Psychology, 79(4), 481–492. https://doi.org/10.1037/0021-9010.79.4.481
  9. Fourkas AD, Ionta S, Aglioti SM. (2006). Influence of imagined posture and imagery modality on corticospinal excitability. Behav Brain Res, 168:190–196. https://doi.org/10.1016/j.bbr.2005.10.015
  10. Frank, C., & Schack, T. (2017). The representation of motor (inter)action, states of action, and learning: Three perspectives on motor learning by way of imagery and execution. Frontiers in Psychology, 8, 678. https://doi.org/10.3389/fpsyg.2017.00678
  11. Frank, C., Bekemeier, K., & Menze-Sonneck, A. (2021). Imagery training in school-based physical education improves the performance and the mental representation of a complex action in comprehensive school students. Psychology of Sport and Exercise, 56, 101972. https://doi.org/10.1016/j.psychsport.2021.101972
  12. Fusco A, Iosa M, Gallotta MC, Paolucci S, Baldari C, Guidetti L. (2014). Different performances in static and dynamic imagery and real locomotion. An exploratory trial. Frontiers in human neuroscience. 8:760. https://doi.org/10.3389/fnhum.2014.00760
  13. Fusco, A., Iosa, M., Tucci, L., Morone, G., Coraci, D., Padua, L., Gallotta, M., Guidetti, L., & Baldari, C. (2021). Dynamic locomotor imagery in athletes with severe visual impairments. New Ideas in Psychology, 62, 100855. https://doi.org/10.1016/j.newideapsych.2021.100855
  14. Glover, S., & Baran, M. (2017). The motor-cognitive model of motor imagery: Evidence from timing errors in simulated reaching and grasping. Journal of Experimental Psychology: Human Perception and Performance, 43(7), 1359–1375. https://doi.org/10.1037/xhp0000389
  15. Gould D, Damarjian N. (1996). Imagery training for peak performance. In Exploring Sport and Exercise Psychology. Edited by Brewer BW, Van Raalte JL. Washington DC: American Psychological Association; 25–50
  16. Guillot A, Collet C, Dittmar A. (2005). Influence of environmental context on motor imagery quality. Biol Sport, 22:215–226.
  17. Guillot A, Collet C, Nguyen VA, Malouin F, Richards C, Doyon J. (2008). Functional neuroanatomical networks associated with expertise in motor imagery ability. Neuroimage, 41:1471–1483.
  18. Guillot A, Di Rienzo F, Frankb C , Debarnot U, MacIntyred E. (2021). From simulation to motor execution: a review of the impact of dynamic motor imagery on performance. International review of sport and exercise psychology. 17(1), 420–439. https://doi.org/10.1080/1750984X.2021.2007539
  19. Guillot A, Hoyek N, Louis M, Collet C. (2012). Understanding the timing of motor imagery: recent findings and future directions. Int Rev Sport Exerc Psychol, 5:3–22. https://doi.org/10.1080/1750984x.2011.623787
  20. Guillot A, Lebon F, Rouffet D, Champely S, Doyon J, Collet C. (2007). Muscular responses during motor imagery as a function of muscle contraction types. Int J Psychophysiol, 66:18–27. https://doi.org/10.1016/j.ijpsycho.2007.05.009
  21. Guillot, A., & Collet, C. (2008). Construction of the motor imagery integrative model in sport: A review and theoretical investigation of motor imagery use. International Review of Sport and Exercise Psychology, 1(1), 31–44. https://doi.org/10.1080/17509840701823139
  22. Guillot, A., Moschberger, K., & Collet, C. (2013). Coupling movement with imagery as a new perspective for motor imagery practice. Behavioral and Brain Functions, 9(1), 8. https://doi.org/10.1186/1744-9081-9-8
  23. Hamilton SJC: Mental practice with motor imagery in stroke recovery:
  24. Ietswaart M, Johnston M, Dijkerman HC, Joice S, Scott CL, MacWalter RS, Hamilton SJC. (2011). Mental practice with motor imagery in stroke recovery: randomized controlled trial of efficacy. Brain, 134:1373–1386. https://doi.org/10.1093/brain/awr077
  25. Ietswaart M, Johnston M, Dijkerman HC, Joice S, Scott CL, MacWalter RS, Jackson PL, Lafleur MF, Malouin F, Richards C, Doyon J. (2001). Potential role of mental practice using motor imagery in neurologic rehabilitation. Arch Phys Med Rehab, 82:1133–1141. https://doi.org/10.1053/apmr.2001.24286
  26. Jeannerod M. (2006). Motor Cognition. New York: Oxford University Press.
  27. Koch, I., Keller, P. E., & Prinz, W. (2004). The ideomotor approach to action control: Implications for skilled performance. International Journal of Sport and Exercise Psychology, 2(4), 362–375. https://doi.org/10.1080/1612197X.2004.9671751
  28. Lebon F, Guillot A, Rouffet D, Collet C. (2008). EMG correlates different types of muscular contraction during motor imagery. Neurosci Let, 435:181–185. https://doi.org/10.1016/j.neulet.2008.02.033
  29. Li-Wei, Z., Qi-Wei, M., Orlick, T., & Zitzelsberger, L. (1992). The effect of mental-imagery training on performance enhancement with 7–10-year-old children. The Sport Psychologist, 6(3), 230–241. https://doi.org/10.1123/tsp.6.3.230
  30. Lotze M, Halsband U. (2006). Motor imagery. J Physiol Paris, 99:386–395
  31. Lotze M, Zentgraf K. (2010). Contribution of the primary motor cortex to motor imagery. In The neurophysiological foundations of mental and motor imagery. Edited by Collet C, Guillot A. New-York: Oxford University Press; 31–46. https://doi.org/10.1093/acprof:oso/9780199546251.003.0003
  32. MacIntyre T, Moran A. (2010). Meta-imagery processes among elite sports performers. In The neurophysiological foundations of mental and motor imagery. Edited by Collet C, Guillot A. New-York: Oxford University Press; 227–244. https://doi.org/10.1093/acprof:oso/9780199546251.003.0016
  33. Malouin F, Richards C, Durand A, Doyon J. (2008). Reliability of mental chronometry for assessing motor imagery ability after stroke. Arch Phys Med Rehab, 89:311–319. https://doi.org/10.1016/j.apmr.2007.11.006
  34. Malouin F, Richards CL, Desrosiers J, Doyon J. (2004). Bilateral slowing of mentally simulated actions after stroke. Neuroreport, 15:1349–1353. https://doi.org/10.1097/01.wnr.0000127465.94899.72
  35. Moran A, Guillot A, MacIntyre T, Collet C. (2011). Re-imagining motor imagery: Building bridges between cognitive neuroscience and sports psychology. Br J Psychol, 103:224–247.

https://doi.org/10.1111/j.2044-8295.2011.02068.x

  1. Nikulin VV, Hohlefeld FU, Jacobs AM, Curio G. (2008). Quasi-movements: A novel motor-cognitive phenomenon. Neuropsychologia, 46:727–742. https://doi.org/10.1016/j.neuropsychologia.2007.10.008
  2. Hall C. (2009). A quantitative analysis of athletes’ use of slowmotion, real time and fast motion images. J Appl Sport Psychol, 21:15–30. https://doi.org/10.1080/10413200802541892
  3. O’Shea, H., & Moran, A. (2017). Does motor simulation theory explain the cognitive mechanisms underlying motor imagery? A critical review. Frontiers in Human Neuroscience, 11, 72. https://doi.org/10.3389/fncom.2017.00072
  4. randomized controlled trial of efficacy. Brain 2011, 134:1373–1386.Robin, N., Toussaint, L., Charles-Charlery, C., & Coudevylle, G. R. (2019). Free throw performance in non-expert basketball players: The effect of dynamic motor imagery combined with action observation. Learning and Motivation, 68, 101595. https://doi.org/10.1016/j.lmot.2019.101595
  5. Roure R, Collet C, Deschaumes-Molinaro C, Delhomme G, Dittmar A, VernetMaury E. (1999). Imagery quality estimated by autonomic response is correlated to sporting performance enhancement. Physiol Behav, 66:63–72.

https://doi.org/10.1016/s0031-9384(99)00026-8

  1. Sacheli, L. M., Zapparoli, L., Bonandrini, R., Preti, M., Pelosi, C., Sconfienza, L. M., Banfi, G., & Paulesu, E. (2020). How aging affects the premotor control of lower limb movements in simulated gait. Human Brain Mapping, 41(7), 1889–1903. https://doi.org/10.1002/hbm.24919
  2. Sacheli, L. M., Zapparoli, L., Preti, M., De Santis, C., Pelosi, C., Ursino, N., Zerbi, A., Stucovitz, E., Banfi, G., & Paulesu, E. (2018). A functional limitation to the lower limbs affects the neural bases of motor imagery of gait. NeuroImage: Clinical, 20, 177–187. https://doi.org/10.1016/j.nicl.2018.07.003
  3. Schuster, C., Hilfiker, R., Amft, O., Scheidhauer, A., Andrews, B., Butler, J., Kischka, U., & Ettlin, T. (2011). Best practice for motor imagery: A systematic literature review on motor imagery training elements in five different disciplines. BMC Medicine, 9(1), 75. https://doi.org/10.1186/1741- 7015-9-75
  4. Schwartz DL, Holton DL: Tool use and the effect of action on the imagination. J Exp Psychol Learn Mem Cogn 2000, 26:1655–1665.
  5. Sirigu A, Duhamel JR, Cohen L, Pillon B, Dubois B, Agid L: The mental representation of hand movements after parietal cortex damage. Science 1996, 273:1564–1568. https://doi.org/10.1126/science.273.5281.1564
  6. Smith D, Wright C, Allsopp A, Westhead H: It’s all in the mind: PETTLEP-based imagery and sports performance. J Appl Sport Psychol 2007, 19:80–92. https://doi.org/10.1080/10413200600944132
  7. Toth, A. J., McNeill, E., Hayes, K., Moran, A., & Campbell, M. (2020). Does mental practice still enhance performance? A 24-year follow-up and meta-analytic replication and extension. Psychology of Sport and Exercise, 48, 101672. https://doi.org/10.1016/j.psychsport.2020.101672
  8. Vargas CD, Olivier E, Craighero L, Fadiga L, Duhamel JR, Sirigu A. (2004). The influence of hand posture on corticospinal excitability during motor imagery: A transcranial magnetic stimulation study. Cereb Cortex, 14:1200–1206. https://doi.org/10.1093/cercor/bhh080
  9. Vergeer E, Roberts J. (2006). Movement and stretching imagery during flexibility training. J Sports Sci, 24:197–208. https://doi.org/10.1080/02640410500131811
  10. Wakefield C, Smith D, Moran AP, Holmes P. (2012). Functional equivalence or behavioural matching? A critical reflection on 15 years of research using the PETTLEP model of motor imagery. Int Rev Sport Exerc Psychol. https://doi.org/10.1080/1750984x.2012.724437
  11. White A, Hardy L: Use of different imagery perspectives on the learning and performance of different motor skills. Br J Psychol 1995, 86:169–180. https://doi.org/10.1111/j.2044-8295.1995.tb02554.x
  12. Williams SE, Cumming J, Balanos GM. The use of imagery to manipulate challenge and threat appraisal States in athletes. Journal of Sport & Exercise Psychology. 2010; 32(3):339–58. https://doi.org/10.1123/jsep.32.3.339
  13. Williams SE, Cumming J. Sport imagery ability predicts trait confidence, and challenge and threat appraisal tendencies. European journal of sport science. 2012; 12(6):499–508. https://doi.org/10.1080/17461391.2011.630102
  1.