The Journal of Korean Physical Therapy

  • 제22권5호
  • /
  • Pages.109-115
  • /
  • 2010
  • /
  • 1229-0475(pISSN)
  • /
  • 2287-156X(eISSN)
대한물리치료학회 (The Korean Society of Physical Therapy)
권호 표지

운동학습에 의한 왼쪽 하전두영역의 분할비등방성의 변화

Change of Fractional Anisotropy in the Left Inferior Frontal Area after Motor Learning

  • 박지원 (대구가톨릭대학교 의료과학대학 물리치료학과) ;
  • 남기석 (영남이공대학 물리치료과)
  • Park, Ji-Won (Department of Physical Therapy, College of Medical Science, Catholic University of Daegu) ;
  • Nam, Ki-Seok (Department of Physical Therapy, Yeungnam College of Science & Technology)
  • 투고 : 2010.06.10
  • 심사 : 2010.09.26
  • 발행 : 2010.10.25
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

Purpose: This study was to delineate the structural change of neural pathway after sequential motor learning using diffusion tensor imaging (DTI). Methods: The participants were 16 healthy subjects, which were divided by training (n=8) and control (n=8) group. The task for the training was the Serial Reaction Time Task (SRTT) which was designed by Superlab program. When the 'asterisk' shows up in the 4 partition spaces on the monitor, the subject presses the correct response button as soon as possible. The training group participated in the training program of motor learning with SRTT composed of 24 digits pattern in one hour per daily through 10 days during 2 weeks. Results: In the behavioral results the training group showed significant changes in the increase of response number and the reduction of response time than those of the control group. There was significant difference in the left inferior frontal area in the fractional anisotropy (FA) map of the training group in DTI analysis. Conclusion: Motor sequential learning as like SRTT may be needed to the learning of language and visuospatial processing and may be induced for the experience-dependent structural plasticity during short period.

키워드

참고문헌

  1. Nissen MJ, Bullemer P. Attentional requirements of learning: Evidence from performance measurs. Cogn Psychol. 1987; 19:1-32. https://doi.org/10.1016/0010-0285(87)90002-8
  2. Eliassen JC, Souza T, Sanes JN. Human brain activation accompanying explicitly directed movement sequence learning. Exp Brain Res. 2001;141(3):269-80. https://doi.org/10.1007/s002210100822
  3. Green RE, Shanks DR. On the existence of independent explicit and implicit learning systems: An examination of some evidence. Mem Cognit. 1993;21(3):304-17. https://doi.org/10.3758/BF03208263
  4. Rosenbaum DA, Carlson RA, Gilmore RO. Acquisition of intellectual and perceptual-motor skills. Annu Rev Psychol. 2001;52:453-70. https://doi.org/10.1146/annurev.psych.52.1.453
  5. Honda M, Deiber MP, Ibanez V et al. Dynamic cortical involvement in implicit and explicit motor sequence learning. A pet study. Brain. 1998;121 (Pt 11):2159-73. https://doi.org/10.1093/brain/121.11.2159
  6. Boyd LA, Winstein CJ. Implicit motor-sequence learning in humans following unilateral stroke: The impact of practice and explicit knowledge. Neurosci Lett. 2001;298(1):65-9. https://doi.org/10.1016/S0304-3940(00)01734-1
  7. Doyon J, Benali H. Reorganization and plasticity in the adult brain during learning of motor skills. Current Opinion in Neurobiology. 2005;15(2):161-7. https://doi.org/10.1016/j.conb.2005.03.004
  8. Hikosaka O, Nakamura K, Sakai K et al. Central mechanisms of motor skill learning. Current Opinion in Neurobiology. 2002;12(2):217-22. https://doi.org/10.1016/S0959-4388(02)00307-0
  9. Sanes JN. Neocortical mechanisms in motor learning. Curr Opin Neurobiol. 2003;13(2):225-31. https://doi.org/10.1016/S0959-4388(03)00046-1
  10. Rossini PM, Dal Forno G. Integrated technology for evaluation of brain function and neural plasticity. Phys Med Rehabil Clin N Am. 2004;15(1):263-306. https://doi.org/10.1016/S1047-9651(03)00124-4
  11. Tuch DS, Salat DH, Wisco JJ et al. Choice reaction time performance correlates with diffusion anisotropy in white matter pathways supporting visuospatial attention. Proc Natl Acad Sci USA. 2005;102(34):12212-7. https://doi.org/10.1073/pnas.0407259102
  12. Han Y, Yang H, Lv YT et al. Gray matter density and white matter integrity in pianists' brain: A combined structural and diffusion tensor MRI study. Neurosci Lett. 2009; 459(1):3-6. https://doi.org/10.1016/j.neulet.2008.07.056
  13. Schmithorst VJ, Wilke M. Differences in white matter architecture between musicians and non-musicians: A diffusion tensor imaging study. Neurosci Lett. 2002;321(1-2): 57-60. https://doi.org/10.1016/S0304-3940(02)00054-X
  14. Guye M, Parker GJM, Symms M et al. Combined functional MRI and tractography to demonstrate the connectivity of the human primary motor cortex in vivo. NeuroImage. 2003;19(4):1349-60. https://doi.org/10.1016/S1053-8119(03)00165-4
  15. Shinoura N, Suzuki Y, Yamada R et al. Fibers connecting the primary motor and sensory areas play a role in grasp stability of the hand. NeuroImage. 2005;25(3):936-41. https://doi.org/10.1016/j.neuroimage.2004.12.060
  16. Imfeld A, Oechslin MS, Meyer M et al. White matter plasticity in the corticospinal tract of musicians: A diffusion tensor imaging study. Neuroimage. 2009;46(3):600-7. https://doi.org/10.1016/j.neuroimage.2009.02.025
  17. Kwon YH, Jang SH, Kim CS. Changes of cortical activation pattern induced by motor learning with serial reaction time task. J Kor Soc Phys Ther. 2009;21(1):65-72. https://doi.org/10.1589/jpts.21.65
  18. Park JW, Jang SH. The difference of cortical activation pattern according to motor learning in dominant and non‐dominant hand: An fmri case study. J Kor Soc Phys Ther. 2009;21(1): 81-8. https://doi.org/10.1589/jpts.21.81
  19. Pascual-Leone A, Grafman J, Hallett M. Modulation of cortical motor output maps during development of implicit and explicit knowledge. Science. 1994;263(5151):1287-9. https://doi.org/10.1126/science.8122113
  20. Muller RA, Kleinhans N, Pierce K et al. Functional mri of motor sequence acquisition: Effects of learning stage and performance. Brain Res Cogn Brain Res. 2002;14(2):277-93. https://doi.org/10.1016/S0926-6410(02)00131-3
  21. Molinari M, Leggio MG, Solida A et al. Cerebellum and procedural learning: Evidence from focal cerebellar lesions. Brain. 1997;120(Pt 10):1753-62. https://doi.org/10.1093/brain/120.10.1753
  22. Willingham DB, Salidis J, Gabrieli JD. Direct comparison of neural systems mediating conscious and unconscious skill learning. J Neurophysiol. 2002;88(3):1451-60.
  23. Elliott R, Friston KJ, Dolan RJ. Dissociable neural responses in human reward systems. J Neurosci. 2000;20(16):6159-65.
  24. Sanfey AG, Rilling JK, Aronson JA et al. The neural basis of economic decision-making in the ultimatum game. Science. 2003;300(5626):1755-8. https://doi.org/10.1126/science.1082976
  25. Daw ND, Kakade S, Dayan P. Opponent interactions between serotonin and dopamine. Neural Netw. 2002; 15(4-6):603-16. https://doi.org/10.1016/S0893-6080(02)00052-7
  26. Seymour B, O'Doherty JP, Dayan P et al. Temporal difference models describe higher-order learning in humans. Nature. 2004;429(6992):664-7. https://doi.org/10.1038/nature02581
  27. Swick D, Ashley V, Turken AU. Left inferior frontal gyrus is critical for response inhibition. BMC Neurosci. 2008; 9:102. https://doi.org/10.1186/1471-2202-9-102
  28. Draganski B, Gaser C, Busch V et al. Neuroplasticity: Changes in grey matter induced by training. Nature. 2004; 427(6972): 311-2. https://doi.org/10.1038/427311a
  29. Hulshoff Pol HE, Schnack HG, Posthuma D et al. Genetic contributions to human brain morphology and intelligence. J Neurosci. 2006;26(40):10235-42. https://doi.org/10.1523/JNEUROSCI.1312-06.2006
  30. Mechelli A, Crinion JT, Noppeney U et al. Neurolinguistics: Structural plasticity in the bilingual brain. Nature. 2004; 431(7010):757. https://doi.org/10.1038/431757a
  31. Draganski B, Gaser C, Kempermann G et al. Temporal and spatial dynamics of brain structure changes during extensive learning. J Neurosci. 2006;26(23):6314-7. https://doi.org/10.1523/JNEUROSCI.4628-05.2006
  32. May A, Gaser C. Magnetic resonance-based morphometry: A window into structural plasticity of the brain. Curr Opin Neurol. 2006;19(4):407-11. https://doi.org/10.1097/01.wco.0000236622.91495.21
  33. Munte TF, Altenmuller E, Jancke L. The musician's brain as a model of neuroplasticity. Nat Rev Neurosci. 2002;3(6): 473-8.
  34. Gaser C, Schlaug G. Brain structures differ between musicians and non-musicians. J Neurosci. 2003;23(27):9240-5.
  35. Sluming V, Barrick T, Howard M et al. Voxel-based morphometry reveals increased gray matter density in broca's area in male symphony orchestra musicians. Neuroimage. 2002;17(3):1613-22. https://doi.org/10.1006/nimg.2002.1288
  36. May A, Hajak G, Ganssbauer S et al. Structural brain alterations following 5 days of intervention: Dynamic aspects of neuroplasticity. Cereb Cortex. 2007;17(1):205-10.
  37. Aydin K, Ucar A, Oguz KK et al. Increased gray matter density in the parietal cortex of mathematicians: A voxel-based morphometry study. AJNR Am J Neuroradiol. 2007;28(10): 1859-64. https://doi.org/10.3174/ajnr.A0696
  38. Scholz J, Klein MC, Behrens TE et al. Training induces changes in white-matter architecture. Nat Neurosci. 2009; 12(11):1370-1. https://doi.org/10.1038/nn.2412