Experimental Brain Research

, Volume 191, Issue 2, pp 221–236

Decrease in cortical activation during learning of a multi-joint discrete motor task

Research Article

Abstract

Understanding how the brain learns motor skills remains a very challenging task. To elucidate the neural mechanism underlying motor learning, we assessed brain activation changes on a trial-by-trial basis during learning of a multi-joint discrete motor task (kendama task). We used multi-channel near-infrared spectroscopy (NIRS) while simultaneously measuring upper limb movement changes by using a 3D motion capture system. Fourteen right-handed participants performed the task using their right upper limb while sitting a chair. The task involved tossing a ball connected by a string to the kendama stick (picking up movement) and catching the ball in the cup attached to the stick (catching movement). Participants performed a trial every 20 s for 90 trials. We measured the hemodynamic responses [oxygenated hemoglobin (oxy-Hb) and deoxygenated hemoglobin (deoxy-Hb) signals] around the predicted location of the sensorimotor cortices on both hemispheres. Analysis of the NIRS data revealed that the magnitudes of the event-related oxy-Hb responses to each trial decreased significantly as learning progressed. Analysis of movement data revealed that integrated upper limb muscle torques decreased significantly only for the picking up movements as learning progressed, irrespective of the outcome of the trials. In contrast, dispersion of the movement patterns decreased significantly only for the catching movements in the unsuccessful trials. Furthermore, we found significant positive correlations between the changes in the magnitudes of the oxy-Hb responses and those of the integrated upper limb muscle torques during learning. Our results suggest that the decrease in cortical activation in the sensorimotor cortex reflects changes in motor commands during learning of a multi-joint discrete movement.

Keywords

NIRS Motor learning Multi-joint movements Discrete movements 

References

  1. Ae M, Tang H, Yokoi T (1992) Estimation of inertia properties of the body segments in Japanese athletes (in Japanese with English abstract). In: Biomechanisms 11 (eds) Society of Biomechanisms Japan, Tokyo Daigaku Shuppan-Kai, pp 23–33Google Scholar
  2. Ashe J, Lungu OV, Basford AT, Lu X (2006) Cortical control of motor sequences. Curr Opin Neurobiol 16:213–221PubMedCrossRefGoogle Scholar
  3. Berns GS, Cohen JD, Mintun MA (1997) Brain regions responsive to novelty in the absence of awareness. Science 276:1272–1275PubMedCrossRefGoogle Scholar
  4. Chance B, Zhuang Z, Unah C, Alter C, Lipton L (1993) Cognition-activated low-frequency modulation of light absorption in human brain. Proc Natl Acad Sci USA 90:3770–3774PubMedCrossRefGoogle Scholar
  5. Colier WNJM, Quaresima V, Oeseburg B, Ferrari M (1999) Human motor-cortex oxygenation changes induced by cyclic coupled movements of hand and foot. Exp Brain Res 129:457–461PubMedCrossRefGoogle Scholar
  6. Debaere F, Wenderoth N, Sunaert S, Van Hecke P, Swinnen SP (2004) Changes in brain activation during the acquisition of a new bimanual coordination task. Neuropsychologia 42:855–867PubMedCrossRefGoogle Scholar
  7. Dettmers C, Fink GR, Lemon RN, Stephan KM, Passingham RE, Silbersweig D, Holmes A, Ridding MC, Brooks DJ, Frackowiak RSJ (1995) Relation between cerebral activity and force in the motor areas of the human brain. J Neurophysiol 74:802–815PubMedGoogle Scholar
  8. Donchin O, Francis JT, Shadmehr R (2003) Quantifying generalization from trial-by-trial behavior of adaptive systems that learn with basis function: theory and experiments in human motor control. J Neurosci 23:9032–9045PubMedGoogle Scholar
  9. Dounskaia N (2005) The internal model and the leading joint hypothesis: implications for control of multi-joint movements. Exp Brain Res 166:1–16PubMedCrossRefGoogle Scholar
  10. Doyon J, Penhune V, Ungerleider LG (2003) Distinct contribution of the cortico-striatal and cortico-cerebellar systems to motor skill learning. Neuropsychologia 41:252–262PubMedCrossRefGoogle Scholar
  11. Floyer-Lea A, Matthews PM (2004) Changing brain networks for visuomotor control with increased movement automaticity. J Neurophysiol 92:2405–2412PubMedCrossRefGoogle Scholar
  12. Franceschini MA, Fantini S, Thompson JH, Culver JP, Boas DA (2003) Hemodynamic evoked response of the sensorimotor cortex measured noninvasively with near-infrared optical imaging. Psychophysiology 40:548–560PubMedCrossRefGoogle Scholar
  13. Galloway JC, Koshland GF (2002) General coodination of shoulder, elbow and wrist dynamics during multijoint arm movements. Exp Brain Res 142:163–180PubMedCrossRefGoogle Scholar
  14. Galloway JC, Bhat A, Heathcock JC, Manal K (2004) Shoulder and elbow joint power differ as a general feature of vertical arm movements. Exp Brain Res 157:391–396PubMedCrossRefGoogle Scholar
  15. Grafton ST, Mazziotta JC, Presty S, Friston KJ, Frackowiak RSJ, Phelps ME (1992) Functional anatomy of human procedual learning determined with regional cerebral blood flow and PET. J Neurosci 12:2542–2548PubMedGoogle Scholar
  16. Grafton ST, Woods RP, Mike T (1994) Functional imaging of procedural motor learning: relating cerebral blood flow with individual subject performance. Hum Brain Mapp 1:221–234CrossRefGoogle Scholar
  17. Grafton ST, Hazeltine E, Ivry RB (1998) Abstract and effector-specific representations of motor sequences identified with PET. J Neurosci 18:9420–9428PubMedGoogle Scholar
  18. Grafton ST, Schmitt P, Van Horn J, Diedrichsen J (2008) Neural substrates of visuomotor learning based on improved feedback control and prediction. Neuroimage 39:1383–1395PubMedCrossRefGoogle Scholar
  19. Grill-Spector K, Henson R, Martin A (2006) Repetition and the brain: neural models of stimulus-specific effects. Trends Cogn Sci 10:14–23PubMedCrossRefGoogle Scholar
  20. Hatakenaka M, Miyai I, Mihara M, Sakoda S, Kubota K (2007) Frontal regions involved in learning of motor skill—a functional NIRS study. Neuroimage 34:109–116PubMedCrossRefGoogle Scholar
  21. Hikosaka O, Nakahara H, Rand MK, Sakai K, Lu X, Nakamura K, Miyachi S, Doya K (1999) Parallel neural networks for learning sequential procedures. Trends Neurosci 22:464–471PubMedCrossRefGoogle Scholar
  22. Hikosaka O, Nakamura K, Sakai K, Nakahara H (2002) Central mechanisms of motor skill learning. Curr Opin Neurobiol 12:217–222PubMedCrossRefGoogle Scholar
  23. Hirashima M, Kudo K, Watarai K, Ohtsuki T (2007) Control of 3D limb dynamics in unconstrained overarm throws of different speeds performed by skilled baseball player. J Neurophysiol 97:680–691PubMedCrossRefGoogle Scholar
  24. Hirth C, Obrig H, Villringer K, Thiel A, Bernarding J, Mühlnickel W, Flor H, Dirnagl U, Villinger A (1996) Non-invasive functional mapping of the human motor cortex using near-infrared spectroscopy. Neuroreport 7:1977–1981PubMedCrossRefGoogle Scholar
  25. Hirth C, Obrig H, Valdueza J, Dirnagl U, Villinger A (1997) Simultaneous assessment of cerebral oxygenation and hemodynamics during a motor task. a combined near infrared and transcranial doppler sonography study. Adv Exp Med Biol 411:461–469PubMedGoogle Scholar
  26. Hluštík P, Solodkin A, Noll DC, Small SL (2004) Cortical plasticity during three-week motor skill learning. J Clin Neurophysiol 21:180–191PubMedCrossRefGoogle Scholar
  27. Hogan N, Sternad D (2007) On rhythmic and discrete movements: reflections, definitions and implications for motor control. Exp Brain Res 181:13–30PubMedCrossRefGoogle Scholar
  28. Honda M, Deiber M-P, Ibáñez V, Pascual-Leone A, Zhuang P, Hallett M (1998) Dynamic cortical involvement in implicit and explicit motor sequence learning. Brain 121:2159–2173PubMedCrossRefGoogle Scholar
  29. Hoshi Y, Tamura M (1993) Detection of dynamic changes in cerebral oxygenation coupled to neuronal function during mental work in man. Neurosci Lett 150:5–8PubMedCrossRefGoogle Scholar
  30. Huppert TJ, Hoge RD, Diamond SG, Franceschini MA, Boas DA (2006) A temporal comparison of BOLD, ASL, and NIRS hemodynamic responses to motor stimuli in adult humans. Neuroimage 29:368–382PubMedCrossRefGoogle Scholar
  31. Imamizu H, Miyauchi S, Tamada T, Sasaki Y, Takino R, Pütz B, Yoshioka T, Kawato M (2000) Human cerebellar activity reflecting an acquired internal model of a new tool. Nature 403:192–195PubMedCrossRefGoogle Scholar
  32. Jasdzewski G, Strangman G, Wagner J, Kwong KK, Poldrack PA, Boas DA (2003) Differences in the hemodynamic response to event-related motor and visual paradigms as measured by near-infrared spectroscopy. Neuroimage 20:479–488PubMedCrossRefGoogle Scholar
  33. Jenkins IH, Brooks DJ, Nixon PD, Frackowiak RSJ, Passingham RE (1994) Motor sequence learning: a study with positron emission tomography. J Neurosci 14:3775–3790PubMedGoogle Scholar
  34. Jöbsis FF (1977) Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters. Science 198:1264–1267PubMedCrossRefGoogle Scholar
  35. Jueptner M, Frith CD, Brooks DJ, Frackowiak RSJ, Passingham RE (1997a) Anatomy of motor learning. II. subcortical structures and learning by trial and error. J Neurophysiol 77:1325–1337PubMedGoogle Scholar
  36. Jueptner M, Stephan KM, Frith CD, Brooks DJ, Frackowiak RSJ (1997b) Anatomy of motor learning. I. Frontal cortex and attention to action. J Neurophysiol 77:1313–1324PubMedGoogle Scholar
  37. Kato T, Kamei A, Takashima S, Ozaki T (1993) Human visual cortical function during photic stimulation monitoring by means of near-infrared spectroscopy. J Cereb Blood Flow Metab 13:516–520PubMedGoogle Scholar
  38. Karni A, Meyer G, Jezzard P, Adams MM, Turner R, Ungerleider LG (1995) Functional MRI evidence for adult motor cortex plasticity during motor skill learning. Nature 377:155–158PubMedCrossRefGoogle Scholar
  39. Karni A, Meyer G, Rey-Hipolito C, Jezzard P, Adams MM, Turner R, Ungerleider LG (1998) The acquisition of skilled motor performance: fast and slow experience-driven changes in primary motor cortex. Proc Natl Acad Sci USA 95:861–868PubMedCrossRefGoogle Scholar
  40. Kelly AMC, Garavan H (2005) Human functional neuroimaging of brain changes associated with practice. Cereb Cortex 15:1089–1102PubMedCrossRefGoogle Scholar
  41. Kleinschmit A, Obrig H, Requart M, Merboldt K-D, Dirnagl U, Villringer A, Frahm J (1996) Simultaneous recording of cerebral blood oxygenation changes during human brain activation by magnetic resonance imaging and near-infrared spectroscopy. J Cereb Blood Flow Metab 16:817–826CrossRefGoogle Scholar
  42. Maki A, Yamashita Y, Ito Y, Watanabe E, Mayanagi Y, Koizumi H (1995) Spatial and temporal analysis of human motor activity using noninvasive NIR topography. Med Phys 22:1997–2005PubMedCrossRefGoogle Scholar
  43. Miyai I, Tanabe HC, Sase I, Eda H, Oda I, Konishi I, Tsunazawa Y, Suzuki T, Yanagida T, Kubota K (2001) Cortical mapping of gait in humans: a near-infrared spectroscopic topography study. Neuroimage 14:1186–1192PubMedCrossRefGoogle Scholar
  44. van Mourik AM, Beek PJ (2004) Discrete and cyclical movements: unified dynamics or separate control? Acta Psychol 117:121–138CrossRefGoogle Scholar
  45. Müller R-A, Kleinhans N, Pierce K, Kemmotsu N, Courchesne E (2002) Functional MRI of motor sequence acquisition: effects of learning stage and performance. Cogn Brain Res 14:277–293CrossRefGoogle Scholar
  46. Obrig H, Villringer A (2003) Beyond the visble-imaging the human brain with light. J Cereb Blood Flow Metab 23:1–18PubMedCrossRefGoogle Scholar
  47. Obrig H, Hirth C, Junge-Hülsing JG, Döge C, Wolf T, Dirnagl U, Villringer A (1996) Cerebral oxygenation changes in response to motor stimulation. J Appl Physiol 81:1174–1183PubMedGoogle Scholar
  48. Okamoto M, Dan H, Sakamoto K, Takeo K, Shimizu K, Kohno S, Oda I, Isobe S, Suzuki T, Kohyama K, Dan I (2004a) Three-dimensional probabilistic anatomical cranio-cerebral correlation via the international 10–20 system oriented for transcranial functional brain mapping. Neuroimage 21:99–111PubMedCrossRefGoogle Scholar
  49. Okamoto M, Dan H, Shimizu K, Takeo K, Amita T, Oda I, Konishi I, Sakamoto K, Isobe S, Suzuki T, Kohyama K, Dan I (2004b) Multimodal assessment of cortical activation during apple peeling by NIRS and fMRI. Neuroimage 21:1275–1288PubMedCrossRefGoogle Scholar
  50. Pascual-Leone A, Grafman J, Hallett M (1994) Modulation of cortical motor output maps during development of implicit and explicit knowledge. Science 263:1287–1289PubMedCrossRefGoogle Scholar
  51. Petersen SE, van Mier H, Fiez JA, Raichle ME (1998) The effects of practice on the functional anatomy of task performance. Proc Natl Acad Sci USA 95:853–860PubMedCrossRefGoogle Scholar
  52. Poldrack RA (2000) Imaging Brain Plasticity: conceptual and methodological issues-a theoretical review. Neuroimage 12:1–13PubMedCrossRefGoogle Scholar
  53. Puttemans V, Wenderoth N, Swinnen SP (2005) Changes in brain activation during the acquisition of a multifrequency bimanual coordination task: from the cognitive stage to advanced levels of automaticity. J Neurosci 25:4270–4278PubMedCrossRefGoogle Scholar
  54. Sakai K, Hikosaka O, Miyauchi S, Takino R, Sasaki Y, Pütz B (1998) Transition of brain activation from frontal to parietal areas in visuomotor sequence learning. J Neurosci 18:1827–1840PubMedGoogle Scholar
  55. Sanes JN (2003) Neocortical mechanisms in motor learning. Curr Opin Neurobiol 13:225–231PubMedCrossRefGoogle Scholar
  56. Sato H, Fuchino Y, Kiguchi M, Katura T, Maki A, Yoro T, Koizumi H (2005) Intersubject variability of near-infrared spectroscopy signals during sensorimotor cortex activation. J Biomed Opt 10:044001CrossRefGoogle Scholar
  57. Sato H, Kiguchi M, Maki A, Fuchino Y, Obata A, Yoro T, Koizumi H (2006) Within-subject reproducibility of near-infrared spectroscopy signals in sensorimotor activation after 6 months. J Biomed Opt 11:014021PubMedCrossRefGoogle Scholar
  58. Schaal S, Sternad D, Osu R, Kawato M (2004) Rhythmic arm movement is not discrete. Nat Neurosci 7:1137–1144Google Scholar
  59. Schneider K, Zernicke RF, Schmidt RA, Hart TJ (1989) Changes in limb dynamics during the practice of rapid arm movements. J Biomechanics 22:805–817CrossRefGoogle Scholar
  60. Seitz RJ, Roland PE, Bohm C, Greitz T, Stone-Elander S (1990) Motor learning in man: a positron emission tomographic study. Neuroreport 1:57–60PubMedCrossRefGoogle Scholar
  61. Shadmehr R, Holcomb HH (1997) Neural correlates of motor memory consolidation. Science 277:821–825PubMedCrossRefGoogle Scholar
  62. Shimada S, Hiraki K, Matsuda G, Oda I (2004) Decrease in prefrontal hemoglobin oxygenation during reaching tasks with delayed visual feedback: a near-infrared spectroscopy study. Cogn Brain Res 20:480–490CrossRefGoogle Scholar
  63. Suzuki M, Miyai I, Ono T, Oda I, Konishi I, Kochiyama T, Kubota K (2004) Prefrontal and premotor cortices are involved in adapting walking and running speed on the treadmill: an optical imaging study. Neuroimage 23:1020–1026PubMedCrossRefGoogle Scholar
  64. Taga G, Asakawa K (2007) Selectivity and localization of cortical response to auditory and visual stimulation in awake infants aged 2 to 4 months. Neuroimage 36:1246–1252PubMedCrossRefGoogle Scholar
  65. Taga G, Asakawa K, Maki A, Konishi Y, Koizumi H (2003) Brain imaging in awake infants by near-infrared optical topography. Proc Natl Acad Sci USA 100:10722–10727PubMedCrossRefGoogle Scholar
  66. Thoroughman KA, Shadmehr R (2000) Learning of action through adaptive combination of motor primitives. Nature 407:742–747PubMedCrossRefGoogle Scholar
  67. Toni I, Krams M, Turner R, Passingham RE (1998) The time course of changes during motor sequence learning: a whole-brain fMRI study. Neuroimage 8:50–61PubMedCrossRefGoogle Scholar
  68. Villringer A, Chance B (1997) Non-invasive optical spectroscopy and imaging of human brain function. Trends Neurosci 20:435–442PubMedCrossRefGoogle Scholar
  69. Villringer A, Planck J, Hock C, Schleinkofer L, Dirnagl U (1993) Near infrared spectroscopy (NIRS): a new tool to study hemodynamic changes during activation of brain function in human adults. Neurosci Lett 154:101–104PubMedCrossRefGoogle Scholar
  70. Watanabe E, Yamashita Y, Maki A, Ito Y, Koizumi H (1996) Non-invasive functional mapping with multi-channel near infra-red spectroscopic topography in humans. Neurosci Lett 205:41–44PubMedCrossRefGoogle Scholar
  71. Wolf M, Wolf U, Toronov V, Michalos A, Paunescu A, Choi JH, Gratton E (2002) Different time evolution of oxyhemoglobin and deoxyhemoglobin concentration changes in the visual and motor cortices during functional stimulation: a near-infrared spectroscopy study. Neuroimage 16:704–712PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  1. 1.Graduate School of EducationUniversity of TokyoTokyoJapan
  2. 2.CREST, Japan Science and Technology AgencySaitamaJapan

Personalised recommendations