Advertisement

Non-invasive Functional Brain Biomarkers for Cognitive-Motor Performance Assessment: Towards New Brain Monitoring Applications

  • Rodolphe J. Gentili
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6780)

Abstract

Along with theoretical advances in neuroscience research, recent neurotechnological developments provide portable recording and processing systems that can be employed for real-time assessment in applied military environments. This article provides a brief overview of research related to non-invasive brain biomarkers derived from brain signals that can track brain dynamics during cognitive-motor performance. Potential applications of such brain biomarkers for military personnel such as neurofeedback for accelerated learning as well as brain monitoring for performance assessment and rehabilitation are discussed.

Keywords

Cognitive-motor performance EEG/fNIRS biomarkers alpha power phase synchronization brain monitoring neurofeedback rehabilitation 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Parasuraman, R.: Neuroergonomics: research and practice. Theor. Issues Ergon. Sci. 4, 5–20 (2003)CrossRefGoogle Scholar
  2. 2.
    Kruse, A.: Operational neuroscience: Neurophysiological measures in applied environments. Aviation, Space and Environmental Medicine 78(5), 191–194 (2007)Google Scholar
  3. 3.
    Friedl, K.E., Grate, S.J., Proctor, S.P., Ness, J.W., Lukey, B.J., Kane, R.L.: Army research needs for automated neuropsychological tests: monitoring soldier health and performance status. Arch. Clin. Neuropsychol. 22, 7–14 (2007)CrossRefGoogle Scholar
  4. 4.
    Letz, R.: Continuing challenges for computer-based neuropsychological tests. Neurotoxicology 24, 479–489 (2003)CrossRefGoogle Scholar
  5. 5.
    Coyle, S.M., Ward, T.E., Markham, C.M.: Brain-computer interface using a simplified functional near-infrared spectroscopy system. J. Neural Eng. 4(3), 219–226 (2007)CrossRefGoogle Scholar
  6. 6.
    Deeny, S.P., Haufler, A.J., Saffer, M., Hatfield, B.D.: Electroencephalographic coherence during visuomotor performance:a comparison of cortico-cortical communication in experts and novices. J. Mot. Behav. 41, 106–116 (2009)CrossRefGoogle Scholar
  7. 7.
    Deeny, S.P., Hillman, C.H., Janelle, C.M., Hatfield, B.D.: Cortico–cortical communication and superior performance in skilled marksmen: An EEG coherence analysis. J. Sport and Exercise Psychology 25, 188–204 (2003)CrossRefGoogle Scholar
  8. 8.
    Del Percio, C., Rossini, P.M., Marzano, N., Iacoboni, M., Infarinato, F., et al.: Is there a ”neural efficiency” in athletes? A high-resolution EEG study. Neuroimage 42(4), 1544–1553 (2008)CrossRefGoogle Scholar
  9. 9.
    Gentili, R.J., Bradberry, T.J., Oh, H., Hatfield, B.D., Contreras-Vidal, J.L.: Cerebral cortical dynamics during visuomotor transformation: Adaptation to a cognitive-motor executive challenge. Psychophysiology (in press)Google Scholar
  10. 10.
    Hatfield, B.D., Landers, D.M., Ray, W.J.: Cognitive processes during self-paced motor performance: an electroencephalographic profile of skilled marksmen. J. Sport Psychol. 6, 42–59 (1984)CrossRefGoogle Scholar
  11. 11.
    Hatfield, B.D., Haufler, A.J., Hung, T.M., Spalding, T.W.: Electroencephalographic studies of skilled psychomotor performance. J. Clin. Neurophysiol. 21(3), 144–156 (2004)CrossRefGoogle Scholar
  12. 12.
    Haufler, A.J., Spalding, T.W., Santa Maria, D.L., Hatfield, B.D.: Neurocognitive activity during a self-paced visuospatial task: comparative EEG profiles in marksmen and novice shooters. Biol. Psychol. 53(3), 131–160 (2000)CrossRefGoogle Scholar
  13. 13.
    Kerick, S.E., Douglass, L.W., Hatfield, B.D.: Cerebral cortical adaptations associated with visuomotor practice. Med. Sci. Sports Exerc. 36(1), 118–129 (2004)CrossRefGoogle Scholar
  14. 14.
    Landers, D.M., Han, M.W., Salazar, W., Petruzzello, S.J., Kubitz, K.A., et al.: Effects of learning on electroencephalographic and electrocardiographic patterns in novice archers. Int. J. Sport Psychol. 25, 313–330 (1994)Google Scholar
  15. 15.
    Slobounov, S., Ray, W., Cao, C., Chiang, H.: Modulation of cortical activity as a result of task-specific practice. Neurosci. Lett. 421(2), 126–131 (2007)CrossRefGoogle Scholar
  16. 16.
    Kranczioch, C., Athanassiou, S., Shen, S., Gao, G., Sterr, A.: Short-term learning of a visually guided power-grip task is associated with dynamic changes in EEG oscillatory activity. Clin. Neurophysiol. 119(6), 1419–1430 (2008)CrossRefGoogle Scholar
  17. 17.
    Caplan, J.B., Madsen, J.R., Schulze-Bonhage, A., Aschenbrenner-Scheibe, R., Newman, E.L., et al.: Human theta oscillations related to sensorimotor integration and spatial learning. J. Neurosci. 23(11), 4726–4736 (2003)Google Scholar
  18. 18.
    Yordanova, J., Falkenstein, M., Hohnsbein, J., Kolev, V.: Parallel systems of error processing in the brain. Neuroimage 22(2), 590–602 (2004)CrossRefGoogle Scholar
  19. 19.
    Bell, M.A., Fox, N.A.: Crawling experience is related to changes in cortical organization during infancy: evidence from EEG coherence. Dev. Psychobiol. 29(7), 551–561 (1996)CrossRefGoogle Scholar
  20. 20.
    Gentili, R.J., Bradberry, T.J., Hatfield, B.D., Contreras-Vidal, J.L.: Brain Biomarkers of Motor Adaptation Using Phase Synchronization. In: Proceedings of the IEEE International Conference of the Engineering in Medicine and Biology Society, Minneapolis, Minnesota, USA, September 2-6, vol. 1, pp. 5930–3 (2009)Google Scholar
  21. 21.
    Izzetoglu, M., Bunce, S.C., Izzetoglu, K., Onaral, B., et al.: Functional brain imaging using near-infrared technology. IEEE Eng. Med. Biol. Mag. 26(4), 8–46 (2007)CrossRefGoogle Scholar
  22. 22.
    Leff, D.R., Orihuela-Espina, F., Atallah, L., Athanasiou, T., et al.: Functional prefrontal reorganization accompanies learning-associated refinements in surgery: a manifold embedding approach. Comput. Aided Surg. 13, 325–339 (2008)CrossRefGoogle Scholar
  23. 23.
    Gentili, R.J., Hadavi, C., Ayaz, H., Shewokis, P.A., Contreras-Vidal, J.L.: Hemodynamic Correlates of Visuomotor Adaptation by Functional Near Infrared Spectroscopy. In: IEEE EMBS Proceedings, Buenos Aires, Argentina, pp. 2918–2921 (2010)Google Scholar
  24. 24.
    Defense Advanced Research Projects Agency - Defense Science Office, http://www.darpa.mil/dso/thrusts/trainhu/accelerated/index.htm
  25. 25.
    Thompson, T., Steffert, T., Ros, T., Leach, J., Gruzelier, J.: EEG applications for sport and performance. Methods 45, 279–288 (2008)CrossRefGoogle Scholar
  26. 26.
    Landers, D.M., Petruzzello, S.J., Salazar, W., Crews, D.L., Kubitz, K.A., Grannon, T.L., Han, M.: The influence of electrocortical biofeedback on performance in pre-elite archers. Medicine and Science in Sports and Exercise 23, 123–129 (1991)CrossRefGoogle Scholar
  27. 27.
    Arns, M., Kleinnijenhuis, M., Fallahpour, K., Breteler, R.: Golf Performance Enhancement and Real-Life Neurofeedback Training Using Personalized Event-Locked EEG Profiles. J. Neurother. 11(4), 11–18 (2009)CrossRefGoogle Scholar
  28. 28.
    Vernon, D., Egner, T., Cooper, N., Compton, T., Neilands, C., Sheri, A., Gruzelier, J.: The effect of training distinct neurofeedback protocols on aspects of cognitive performance. Int. J. Psychophysiol. 47(1), 75–85 (2003)CrossRefGoogle Scholar
  29. 29.
    Egner, T., Gruzelier, J.H.: Ecological validity of neurofeedback: Modulation of slow wave EEG enhances musical performance. NeuroReport 14, 1221–1224 (2003)CrossRefGoogle Scholar
  30. 30.
    Hoyt, R.W., Reifman, J., Coster, T.S., Buller, M.J.: Combat medical infomatics: Present and future. In: Proceedings of AMIA Symposium, pp. 335–339 (2002)Google Scholar
  31. 31.
    Oken, B.S., Salinsky, M.C., Elsas, S.M.: Vigilance, alertness, or sustained attention: physiological basis and measurement. Clin. Neurophys. 117(9), 1885–1901 (2006)CrossRefGoogle Scholar
  32. 32.
    Miller, M.W., Rietschel, J., McDonald, C.G., Pangelinan, M., Bush, L., Hatfield, B.D.: EEG assessment of incremental changes in cognitive workload during an ecologically valid visuo-motor task. In: 40th SFN Meeting, San Diego, CA, USA, November 13-17 (2009)Google Scholar
  33. 33.
    Costanzo, M.E., Oh, H., Bulkley, B., Contreras-Vidal, J.L., Goodman, R., Haufler, A., Lo, L.C., et al.: Independent component analysis of brain processes under psychological stress during motor performance. In: 39th SFN Meeting, Chicago, IL, USA, October 17-21 (2009)Google Scholar
  34. 34.
    Makeig, S., Jung, T.P.: Changes in alertness are a principal component of variance in theEEG spectrum. NeuroReport 7, 213–216 (1995)CrossRefGoogle Scholar
  35. 35.
    Miller, M.W., Rietschel, J., McDonald, C.G., Hatfield, B.D.: A Novel Approach to the Physiological Measurement of Mental Workload. International Journal of Psychophysiology (in press)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Rodolphe J. Gentili
    • 1
    • 2
  1. 1.Cognitive Motor Neuroscience Laboratory Department of KinesiologySchool of Public Health University of MarylandCollege ParkUSA
  2. 2.Neuroscience and Cognitive Science ProgramUniversity of MarylandCollege ParkUSA

Personalised recommendations