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Int J Sports Med 2013; 34(12): 1106-1111
DOI: 10.1055/s-0033-1341437
Behavioural Sciences
© Georg Thieme Verlag KG Stuttgart · New York

Brain Activity in Predictive Sensorimotor Control for Landings: an EEG Pilot Study

J. Baumeister
1   Exercise & Brain Laboratory, Institute of Sports Medicine, University of Paderborn, Germany
,
S. von Detten
2   Division of Physiotherapy, Faculty of Health Sciences, Stellenbosch University, Cape Town, South Africa
,
S.-M. van Niekerk
3   Department of Health Sciences, Lund University, Lund, Sweden
,
M. Schubert
2   Division of Physiotherapy, Faculty of Health Sciences, Stellenbosch University, Cape Town, South Africa
,
E. Ageberg
3   Department of Health Sciences, Lund University, Lund, Sweden
,
Q. A. Louw
3   Department of Health Sciences, Lund University, Lund, Sweden
› Author Affiliations
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Publication History



accepted after revision 21 February 2013

Publication Date:
05 June 2013 (online)

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Abstract

Landing from a jump is related to predictive sensorimotor control. Frontal, central and parietal brain areas are known to play a role in this process based on online sensory feedback. This can be measured by EEG. However, there is only limited knowledge about brain activity during predictive preparation for drop landings (DL). The purpose is to demonstrate changes in brain activity in preparation for DL in different conditions. After resting, 10 athletes performed a series of DLs and were asked to concentrate on the landing preparation for 10 s before an auditory signal required them to drop land from a 30 cm platform. This task was executed before and after a standardized fatigue protocol. EEG spectral power was calculated during DL preparation. Frontal Theta power was increased during preparation compared to rest. Parietal Alpha-2 power demonstrated higher values in preparation after fatigue condition while lower limb kinematics remained unchanged. Cortical activity in frontal and parietal brain areas is sensitive for predictive sensorimotor control of drop landings. Frontal Theta power demonstrates an increase and is related to higher attentional control. In a fatigued condition the parietal Alpha-2 power increase might be related to a deactivation in the somatosensory brain areas.

Key words

motor - fatigue - preparation - cortical activity
 

  • References

  • 1 Baumeister J, Reinecke K, Weiss M. Changed cortical activity after anterior cruciate ligament reconstruction in a joint position paradigm: an EEG study. Scand J Med Sci Sports 2008; 18: 473-484
    PubMedGoogle Scholar
  • 2 Baumeister J, Reinecke K, Liesen H, Weiss M. Cortical activity of skilled performance in a complex sports related motor task. Eur J Appl Physiol 2008; 104: 625-631
    CrossrefPubMedGoogle Scholar
  • 3 Baumeister J, Reinecke K, Schubert M, Schade J, Weiss M. Effects of induced fatigue on brain activity during sensorimotor control. Eur J Appl Physiol 2012; 112: 2475-2482
    CrossrefPubMedGoogle Scholar
  • 4 Bush G, Luu P, Posner MI. Cognitive and emotional influences in anterior cingulate cortex. Trends Cogn Sci (Regul. Ed.) 2000; 4: 215-222
    CrossrefPubMedGoogle Scholar
  • 5 Dempsey AR, Lloyd DG, Elliott BC, Steele JR, Munro BJ. Changing sidestep cutting technique reduces knee valgus loading. Am J Sports Med 2009; 37: 2194-2200
    CrossrefPubMedGoogle Scholar
  • 6 Donnelly CJ, Elliott BC, Ackland TR, Doyle TL, Beisier TF, Finch CF, Cochrane JL, Dempsey AR, Lloyd DG. An anterior cruciate ligament injury prevention framework: incorporating the recent evidence. Res Sports Med 2012; 20: 239-262
    PubMedGoogle Scholar
  • 7 Doppelmayr M, Finkenzeller T, Sauseng P. Frontal midline theta in the pre-shot phase of rifle shooting: differences between experts and novices. Neuropsychologia 2008; 46: 1463-1467
    CrossrefPubMedGoogle Scholar
  • 8 Gevins A, Smith ME, McEvoy L, Yu D. High-resolution EEG mapping of cortical activation related to working memory: effects of task difficulty, type of processing, and practice. Cereb Cortex 1997; 7: 374-385
    CrossrefPubMedGoogle Scholar
  • 9 Grunwald M, Weiss T, Krause W, Beyer L, Rost R, Gutberlet I, Gert HJ. Theta power in the EEG of humans during ongoing processing in a haptic object recognition task. Brain Res Cogn Brain Res 2001; 11: 33-37
    CrossrefPubMedGoogle Scholar
  • 10 Harriss DJ, Atkinson G. Update – Ethical standards in sport and exercise science research. Int J Sports Med 2011; 32: 819-821
    Article in Thieme ConnectPubMedGoogle Scholar
  • 11 Haufler AJ, Spalding TW, Santa Maria DL, Hatfield BD. Neuro-cognitive activity during a self-paced visuospatial task: comparative EEG profiles in marksmen and novice shooters. Biol Psychol 2000; 53: 131-160
    CrossrefPubMedGoogle Scholar
  • 12 Kawato M, Wolpert D. Internal models for motor control. Novartis Found Symp 1998; 218: 291-304; discussion 304–307
    PubMedGoogle Scholar
  • 13 Miyake A, Shah P. Models of working memory: Mechanisms of active maintenance and executive control. Cambridge, New York: Cambridge University Press; 1999
    CrossrefGoogle Scholar
  • 14 Myer GD, Ford KR, Brent JL, Hewett TE. The effects of plyometric vs. dynamic stabilization and balance training on power, balance, and landing force in female athletes. J Strength Cond Res 2006; 20: 345-353
    PubMedGoogle Scholar
  • 15 Neuper C, Wortz M, Pfurtscheller G. ERD/ERS patterns reflecting sensorimotor activation and deactivation. Prog Brain Res 2006; 159: 211-222
    PubMedGoogle Scholar
  • 16 Niedermeyer E, Lopes da Silva FH. Electroencephalography. 5th ed. Philadelphia: Lippincott Williams & Wilkins; 2005
    Google Scholar
  • 17 Nunez PL, Srinivasan R. Electric fields of the brain: The neurophysics of EEG. 2nd ed. Oxford, New York: Oxford University Press; 2006
    CrossrefGoogle Scholar
  • 18 Oken BS, Chiappa KH. Statistical issues concerning computerized analysis of brainwave topography. Ann Neurol 1986; 19: 493-497
    CrossrefPubMedGoogle Scholar
  • 19 Pfurtscheller G, Stancák A, Neuper C. Event-related synchronization (ERS) in the alpha band – an electrophysiological correlate of cortical idling: a review. Int J Psychophysiol 1996; 24: 39-46
    CrossrefPubMedGoogle Scholar
  • 20 Pivik RT, Broughton RJ, Coppola R, Davidson RJ, Fox N, Nuwer MR. Guidelines for the recording and quantitative analysis of electroencephalographic activity in research contexts. Psychophysiology 1993; 30: 547-558
    CrossrefPubMedGoogle Scholar
  • 21 Posner MI, Dehaene S. Attentional networks. Trends Neurosci 1994; 17: 75- 79
    CrossrefPubMedGoogle Scholar
  • 22 Sauseng P, Klimesch W, Schabus M, Doppelmayr M. Fronto-parietal EEG coherence in theta and upper alpha reflect central executive functions of working memory. Int J Psychophysiol 2005; 57: 97-103
    CrossrefPubMedGoogle Scholar
  • 23 Semlitsch HV, Anderer P, Schuster P, Presslich O. A solution for reliable and valid reduction of occular artifacts, applied to the P300 ERP. Psychophysiology 1986; 23: 695-703
    CrossrefPubMedGoogle Scholar
  • 24 Slobounov SM, Fukada K, Simon R, Rearick M, Ray W. Neurophysiological and behavioral indices of time pressure effects on visuomotor task performance. Brain Res Cogn Brain Res 2000; 9: 287-298
    CrossrefPubMedGoogle Scholar
  • 25 Smith EE, Jonides J. Storage and executive processes in the frontal lobes. Science 1999; 283: 1657-1661
    CrossrefPubMedGoogle Scholar
  • 26 Smith ME, McEvoy LK, Gevins A. Neurophysiological indices of strategy development and skill acquisition. Brain Res Cogn Brain Res 1999; 7: 389-404
    CrossrefPubMedGoogle Scholar
  • 28 Taube W, Leukel C, Gollhofer A. How neurons make us jump: the neural control of stretch-shortening cycle movements. Exerc Sport Sci Rev 2012; 40: 106-115
    CrossrefPubMedGoogle Scholar
  • 28 Tegner Y, Lysholm J. Rating systems in the evaluation of knee ligament injuries. Clin Orthop Relat Res 1985; 43-49
    PubMedGoogle Scholar