Abstract
Car accidents are considered to be one of the major cause of death all around the world. In order to design electronic devices to improve car safety in the future, we aimed to identify electroencephalographic (EEG) activities to disentangle left from right steering actions in car driving simulation. For this purpose, we performed 128-channels EEG recordings during the driving of a car simulator. EEG scalp topographies resulting from and Independent Component Analysis were clustered across subjects. The corresponding time-frequency patterns of power activity were compared, revealing two distinct EEG clusters reacting with a coupled alpha and beta desynchronization in the preparation of the left and right steering onset, respectively. Topographic maps and dipole localization showed that these EEG components are originated from motor regions of the two hemispheres. Overall, these results illustrate that alpha and beta EEG rhythms could be exploited to predict the driver’s intention in steering actions.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
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). https://doi.org/10.1016/j.neuroimage.2011.06.037
Borghini, G., Astolfi, L., Vecchiato, G., Mattia, D., Babiloni, 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). https://doi.org/10.1016/j.neubiorev.2012.10.003
Biasiucci, A., Franceschiello, B., Murray, M.M.: Electroencephalography. Curr. Biol. 29, R80–R85 (2019). https://doi.org/10.1016/j.cub.2018.11.052
Delorme, A., Palmer, J., Onton, J., Oostenveld, R., Makeig, S.: Independent EEG sources are dipolar. PLoS ONE 7, e30135 (2012). https://doi.org/10.1371/journal.pone.0030135
Debnath, R., Salo, V.C., Buzzell, G.A., Yoo, K.H., Fox, N.A.: Mu rhythm desynchronization is specific to action execution and observation: evidence from time-frequency and connectivity analysis. NeuroImage 184, 496–507 (2019). https://doi.org/10.1016/j.neuroimage.2018.09.053
Vecchiato, G., Vecchio, M.D., Ascari, L., Antopolskiy, S., Deon, F., Kubin, L., Ambeck-Madsen, J., Rizzolatti, G., Avanzini, P.: Electroencephalographic time-frequency patterns of braking and acceleration movement preparation in car driving simulation. Brain Res. (2018). https://doi.org/10.1016/j.brainres.2018.09.004
Swartz Center for Computational Neuroscience (2019). sccn/labstreaminglayer
Bigdely-Shamlo, N., Mullen, T., Kothe, C., Su, K.-M., Robbins, K.A.: The PREP pipeline: standardized preprocessing for large-scale EEG analysis. Front Neuroinform. 9 (2015). https://doi.org/10.3389/fninf.2015.00016
Palmer, J., Kreutz-Delgado, K., Makeig, S.: AMICA: an adaptive mixture of independent component analyzers with shared components (2011). https://sccn.ucsd.edu/~jason/amica_a.pdf
Chaumon, M., Bishop, D.V.M., Busch, N.A.: A practical guide to the selection of independent components of the electroencephalogram for artifact correction. J. Neurosci. Methods 250, 47–63 (2015). https://doi.org/10.1016/j.jneumeth.2015.02.025
Makeig, S., Debener, S., Onton, J., Delorme, A.: Mining event-related brain dynamics. Trends Cogn. Sci. 8, 204–210 (2004). https://doi.org/10.1016/j.tics.2004.03.008
Avanzini, P., Fabbri-Destro, M., Volta, R.D., Daprati, E., Rizzolatti, G., Cantalupo, G.: The dynamics of sensorimotor cortical oscillations during the observation of hand movements: an EEG study. PLoS ONE 7, e37534 (2012). https://doi.org/10.1371/journal.pone.0037534
Zhang, H., Chavarriaga, R., Khaliliardali, Z., Gheorghe, L., Iturrate, I., Millán, Jd.R.: EEG-based decoding of error-related brain activity in a real-world driving task. J. Neural Eng. 12, 066028 (2015). https://doi.org/10.1088/1741-2560/12/6/066028
Acknowledgments
This research was funded by a CAMLIN Limited and Toyota Motor Europe.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Vecchiato, G. et al. (2020). Alpha and Beta EEG Desynchronizations Anticipate Steering Actions in a Driving Simulation Experiment. In: Ahram, T., Karwowski, W., Vergnano, A., Leali, F., Taiar, R. (eds) Intelligent Human Systems Integration 2020. IHSI 2020. Advances in Intelligent Systems and Computing, vol 1131. Springer, Cham. https://doi.org/10.1007/978-3-030-39512-4_41
Download citation
DOI: https://doi.org/10.1007/978-3-030-39512-4_41
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-39511-7
Online ISBN: 978-3-030-39512-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)