Using Brain Activity to Predict Task Performance and Operator Efficiency

  • Hasan Ayaz
  • Scott Bunce
  • Patricia Shewokis
  • Kurtulus Izzetoglu
  • Ben Willems
  • Banu Onaral
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7366)

Abstract

The efficiency and safety of many complex human-machine systems are closely related to the cognitive workload and situational awareness of their human operators. In this study, we utilized functional near infrared (fNIR) spectroscopy to monitor anterior prefrontal cortex activation of experienced operators during a standard working memory and attention task, the n-back. Results indicated that task efficiency can be estimated using operator’s fNIR and behavioral measures together. Moreover, fNIR measures had more predictive power than behavioral measures for estimating operator’s future task performance in higher difficulty conditions.

Keywords

fNIR optical brain imaging working memory task efficiency cognitive workload 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Parasuraman, R., Wilson, G.: Putting the brain to work: Neuroergonomics past, present, and future. Human Factors 50, 468 (2008)CrossRefGoogle Scholar
  2. 2.
    Strangman, G., Boas, D.A., Sutton, J.P.: Non-invasive neuroimaging using near-infrared light. Biological Psychiatry 52, 679–693 (2002)CrossRefGoogle Scholar
  3. 3.
    Chance, B., Anday, E., Nioka, S., Zhou, S., Hong, L., Worden, K., Li, C., Murray, T., Ovetsky, Y., Pidikiti, D., Thomas, R.: A novel method for fast imaging of brain function, non-invasively, with light. Optics Express 2, 411–423 (1998)CrossRefGoogle Scholar
  4. 4.
    Villringer, A., Planck, J., Hock, C., Schleinkofer, L., Dirnagl, U.: Near infrared spectroscopy (NIRS): a new tool to study hemodynamic changes during activation of brain function in human adults. Neuroscience Letters 154, 101–104 (1993)CrossRefGoogle Scholar
  5. 5.
    Chance, B., Zhuang, Z., UnAh, C., Alter, C., Lipton, L.: Cognition-activated low-frequency modulation of light absorption in human brain. Proceedings of the National Academy of Sciences of the United States of America 90, 3770–3774 (1993)CrossRefGoogle Scholar
  6. 6.
    Coyle, S., Ward, T.E., Markham, C.M.: Brain-computer interface using a simplified functional near-infrared spectroscopy system. Journal of Neural Engineering 4, 219–226 (2007)CrossRefGoogle Scholar
  7. 7.
    Obrig, H., Wenzel, R., Kohl, M., Horst, S., Wobst, P., Steinbrink, J., Thomas, F., Villringer, A.: Near-infrared spectroscopy: does it function in functional activation studies of the adult brain? International Journal of Psychophysiology 35, 125–142 (2000)CrossRefGoogle Scholar
  8. 8.
    Irani, F., Platek, S.M., Bunce, S., Ruocco, A.C., Chute, D.: Functional near infrared spectroscopy (fNIRS): an emerging neuroimaging technology with important applications for the study of brain disorders. Clin. Neuropsychol. 21, 9–37 (2007)CrossRefGoogle Scholar
  9. 9.
    Hoshi, Y.: Functional near-infrared spectroscopy: current status and future prospects. Journal of Biomedical Optics 12, 062106 (2007)CrossRefGoogle Scholar
  10. 10.
    Ayaz, H., Shewokis, P.A., Curtin, A., Izzetoglu, M., Izzetoglu, K., Onaral, B.: Using MazeSuite and Functional Near Infrared Spectroscopy to Study Learning in Spatial Navigation. J. Vis. Exp. e3443 (2011)Google Scholar
  11. 11.
    Izzetoglu, M., Izzetoglu, K., Bunce, S., Ayaz, H., Devaraj, A., Onaral, B., Pourrezaei, K.: Functional near-infrared neuroimaging. IEEE Trans. Neural Syst. Rehabil. Eng. 13, 153–159 (2005)CrossRefGoogle Scholar
  12. 12.
    Orihuela-Espina, F., Leff, D., James, D., Darzi, A., Yang, G.: Quality control and assurance in functional near infrared spectroscopy (fNIRS) experimentation. Physics in Medicine and Biology 55, 3701 (2010)CrossRefGoogle Scholar
  13. 13.
    Izzetoglu, K., Ayaz, H., Merzagora, A., Izzetoglu, M., Shewokis, P.A., Bunce, S.C., Pourrezaei, K., Rosen, A., Onaral, B.: The evolution of field deployable fNIR spectroscopy from bench to clinical settings. Journal of Innovative Optical Health Sciences 4, 1–12 (2011)CrossRefGoogle Scholar
  14. 14.
    Ayaz, H., Shewokis, P.A., Bunce, S., Izzetoglu, K., Willems, B., Onaral, B.: Optical brain monitoring for operator training and mental workload assessment. Neuroimage 59, 36–47 (2012)CrossRefGoogle Scholar
  15. 15.
    Clark, R., Nguyen, F., Sweller, J.: Efficiency in learning: Evidence-based guidelines to manage cognitive load. Pfeiffer, An Imprint of Wiley, San Fransico (2006)Google Scholar
  16. 16.
    Owen, A.M., McMillan, K.M., Laird, A.R., Bullmore, E.: N-back working memory paradigm: a meta-analysis of normative functional neuroimaging studies. Human Brain Mapping 25, 46–59 (2005)CrossRefGoogle Scholar
  17. 17.
    D’Esposito, M., Aguirre, G., Zarahn, E., Ballard, D., Shin, R., Lease, J.: Functional MRI studies of spatial and nonspatial working memory. Cognitive Brain Research 7, 1–13 (1998)CrossRefGoogle Scholar
  18. 18.
    Smith, E.E., Jonides, J.: Working Memory: A View from Neuroimaging. Cognitive Psychology 33, 5–42 (1997)CrossRefGoogle Scholar
  19. 19.
    Ayaz, H., Izzetoglu, M., Platek, S.M., Bunce, S., Izzetoglu, K., Pourrezaei, K., Onaral, B.: Registering fNIR data to brain surface image using MRI templates. In: Conf. Proc. IEEE Eng. Med. Biol. Soc., pp. 2671–2674 (2006)Google Scholar
  20. 20.
    Ayaz, H., Izzetoglu, M., Shewokis, P.A., Onaral, B.: Sliding-window Motion Artifact Rejection for Functional Near-Infrared Spectroscopy. In: Conf. Proc. IEEE Eng. Med. Biol. Soc., pp. 6567–6570 (2010)Google Scholar
  21. 21.
    Ayaz, H.: Functional Near Infrared Spectroscopy based Brain Computer Interface. School of Biomedical Engineering Science & Health Systems, p. 214. Drexel University, Philadelphia (2010)Google Scholar
  22. 22.
    Ayaz, H., Cakir, M.P., Izzetoglu, K., Curtin, A., Shewokis, P.A., Bunce, S., Onaral, B.: Monitoring Expertise Development during Simulated UAV Piloting Tasks using Optical Brain Imaging. In: IEEE Aerospace Conference, BigSky, MN, USA, pp. 1–11 (2012)Google Scholar
  23. 23.
    Izzetoglu, K., Bunce, S., Onaral, B., Pourrezaei, K., Chance, B.: Functional Optical Brain Imaging Using Near-Infrared During Cognitive Tasks. International Journal of Human-Computer Interaction 17, 211–227 (2004)CrossRefGoogle Scholar
  24. 24.
    Dumontheil, I., Klingberg, T.: Brain Activity during a Visuospatial Working Memory Task Predicts Arithmetical Performance 2 Years Later. Cerebral Cortex (2011)Google Scholar
  25. 25.
    Shewokis, P.A., Ayaz, H., Izzetoglu, M., Bunce, S., Gentili, R.J., Sela, I., Izzetoglu, K., Onaral, B.: Brain in the Loop: Assessing Learning Using fNIR in Cognitive and Motor Tasks. In: Schmorrow, D.D., Fidopiastis, C.M. (eds.) FAC 2011, HCII 2011. LNCS, vol. 6780, pp. 240–249. Springer, Heidelberg (2011)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hasan Ayaz
    • 1
    • 2
  • Scott Bunce
    • 2
    • 3
  • Patricia Shewokis
    • 1
    • 2
    • 4
  • Kurtulus Izzetoglu
    • 1
    • 2
  • Ben Willems
    • 5
  • Banu Onaral
    • 1
    • 2
  1. 1.School of Biomedical Engineering, Science & Health SystemsDrexel UniversityPhiladelphiaUSA
  2. 2.Cognitive Neuroengineering and Quantitative Experimental Research, (CONQUER) CollaborativeDrexel UniversityPhiladelphiaUSA
  3. 3.Penn State Hershey Medical Center and Penn State College of MedicineHersheyUSA
  4. 4.College of Nursing and Health ProfessionsDrexel UniversityPhiladelphiaUSA
  5. 5.Federal Aviation Administration William J. Hughes Technical CenterUSA

Personalised recommendations