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Brain Gamma Oscillations of Healthy People During Simulated Driving

  • Min Lei
  • Guang Meng
  • Wenming Zhang
  • Joshua Wade
  • Nilanjan Sarkar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9835)

Abstract

Driving was a complex human behavior not only including limb movements but also involving a lot of neuropsychological processes, such as perception, attention, learning, memory, decision making, and action control. Gamma rhythm had been linked with several cognitive functions such attention, memory and perception. In order to explore the understanding of the brain under the real environments, a driving simulator environment might be a best tool that stimulates the brain dynamic activity. The purpose of this study was to investigate cerebral gamma oscillatory differences in the frontal, temporal, parietal, and occipital regions associated with psychological processes during simulated car driving. Neurophysiological signals of 5 healthy volunteers were recorded by using electroencephalography (EEG) during resting and simulated driving, respectively. Oscillatory differences in the gamma band were calculated by comparison between “resting” and “driving”. “Resting” was the baseline, and oscillatory differences in the different regions during “driving” showed an increase in comparison with a baseline. The results indicated that brain oscillatory dynamics could play a role in cognitive processing, and might mediate the interaction between excitation and inhibition.

Keywords

Electroencephalogram (EEG) Gamma oscillation Brain oscillatory dynamics Driving simulator Neuropsychological process 

Notes

Acknowledgments

This work was funded by the Science Fund for Creative Research Groups of the National Natural Science Foundation of China (Grant No. 51421092), the National Natural Science Foundation of China (Grant No. 10872125), the Natural Science Foundation of Shanghai, China (Grant No. 06ZR14042), the Research Fund of State Key Laboratory of Mechanical System and Vibration, China (Grant No. MSV-MS-2010-08), the Research Fund from Shanghai Jiao Tong University for Medical and Engineering Science, China (Grant No. YG2013MS74), the NSF Project of USA (Grant Nos. 0967170, 1264462), and the NIH project of USA (Grant Nos. 1R01MH091102-01A1, 1R21MH103518-01).

References

  1. 1.
    Borghini, G., Astolfi, L., Vecchiato, G., Mattia, D., Bahiloni, F.: Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness. Neurosci. Biobehav. Rev. 44, 58–75 (2014)CrossRefGoogle Scholar
  2. 2.
    Laukka, S.J., Jarvilchto, T., Alexandrov, Y.I., Lindqvist, J.: Frontal midline-theta related to learning in a simulated driving task. Biol. Psychol. 40, 313–320 (1995)CrossRefGoogle Scholar
  3. 3.
    Schier, M.A.: Changes in EEG alpha power during simulated driving: a demonstration. Int. J. Psychophysiol. 37, 155–162 (2000)CrossRefGoogle Scholar
  4. 4.
    Kim, J.Y., Park, J.S., Lee, H.Y., Yoo, S.Y.: Analysis of psychologically optimal driving state through measurement of physiological signals. J. Korean Soc. Emot. Sensibility 7, 27–35 (2004)Google Scholar
  5. 5.
    Jäncke, L., Brunner, B., Esslen, M.: Brain activation during fast driving in a driving simulator: the role of the lateral prefrontal cortex. Neuroreport 19(11), 1127–1130 (2008)CrossRefGoogle Scholar
  6. 6.
    Lin, C.-T., Chen, S.-A., Chiu, T.-T., Lin, H.-Z., Ko, L.-W.: Spatial and temporal EEG dynamics of dual-task driving performance. J. Neuroeng. Rehabil. 8, 11–23 (2011)CrossRefGoogle Scholar
  7. 7.
    Zhao, C.L., Zhao, M., Liu, J.P., Zheng, C.X.: Electroencephalogram and electrocardiograph assessment of mental fatigue in a driving simulator. Accid. Anal. Prev. 45, 83–90 (2012)CrossRefGoogle Scholar
  8. 8.
    Sonnleitner, A., Simon, M., Kincses, W.E., Buchner, A., Schrauf, M.: Alpha spindles as neurophysiological correlates indicating attentional shift in a simulated driving task. Int. J. Psychophysiol. 83, 110–118 (2012)CrossRefGoogle Scholar
  9. 9.
    Fries, P.: Neuronal gamma-band synchronization as a fundamental process in cortical computation. Annu. Rev. Neurosci. 32, 209–224 (2009)CrossRefGoogle Scholar
  10. 10.
    Ray, S., Maunsell, J.: Do Gamma oscillations play a role in cerebral cortex? Trends Cogn. Sci. 19(2), 78–85 (2015)CrossRefGoogle Scholar
  11. 11.
    Kim, H., Hwang, Y., Yoon, D., Choi, W., Park, C.: Driver workload characteristics analysis using EEG data from an urban road. IEEE Trans. Intell. Transp. Syst. 15(4), 1844–1849 (2014)CrossRefGoogle Scholar
  12. 12.
    Calhoun, V.D., Pearlson, G.D.: A selective review of simulated driving studies: combining naturalistic and hybrid paradigms, analysis approaches, and future directions. Neuroimage 59, 25–35 (2012)CrossRefGoogle Scholar
  13. 13.
    Wang, Y., Chen, S., Lin, C.: An EEG-based brain-computer interface for dual task driving detection. Neurocomputing 129, 85–93 (2014)CrossRefGoogle Scholar
  14. 15.
    Zhang, H., Chavarriaga, R., Khaliliardali, Z., Gheorghe, L., Iturrate, I., Millán, J.: EEG-based decoding of error-related brain activity in a real-world driving task. J. Neural Eng. 12, 066028 (2015)CrossRefGoogle Scholar
  15. 16.
    Wade, J., Bian, D., Zhang, L., Swanson, A., Sarkar, M., Warren, Z., Sarkar, N.: Design of a virtual reality driving environment to assess performance of teenagers with ASD. In: Stephanidis, C., Antona, M. (eds.) UAHCI 2014, Part II. LNCS, vol. 8514, pp. 466–474. Springer, Heidelberg (2014)Google Scholar
  16. 17.
    Lei, M., Meng, G., Zhang, W.M., Sarkar, N.: Sample entropy of electroencephalogram for children with autism based on virtual driving game. Acta Phys. Sin. 65(10), 108701 (2016)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.State Key Laboratory of Mechanical System and Vibration, Fundamental Science on Vibration, Shock and Noise Laboratory, School of Mechanical Engineering, Institute of Vibration, Shock and NoiseShanghai Jiao Tong UniversityShanghaiChina
  2. 2.Robotics and Autonomous Systems Laboratory, Department of Mechanical EngineeringVanderbilt UniversityNashvilleUSA

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