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Brain--computer interface (BCI): is it strictly necessary to use random sequences in visual spellers?

Published: 28 August 2012 Publication History

Abstract

The P300 speller is a standard paradigm for brain--computer interfacing (BCI) based on electroencephalography (EEG). It exploits the fact that the user's selective attention to a target stimulus among a random sequence of stimuli enhances the magnitude of the P300 evoked potential. The present study questions the necessity of using random sequences of stimulation. In two types of experimental runs, subjects attended to a target stimulus while the stimuli, four in total, were each intensified twelve times, in either random order or deterministic order. The 32-channel EEG data were analyzed offline using linear discriminant analysis (LDA). Similar classification accuracies of 95.3% and 93.2% were obtained for the random and deterministic runs, respectively, using the data associated with 3 sequences of stimulation. Furthermore, using a montage of 5 posterior electrodes, the two paradigms attained identical accuracy of 92.4%. These results suggest that: (a) the use of random sequences is not necessary for effective BCI performance; and (b) deterministic sequences can be used in some BCI speller applications.

References

[1]
Allison, B. Z. and Pineda, J. A. Effects of SOA and flash pattern manipulations on ERPs, performance, and preference: Implications for a BCI system. International Journal of Psychophysiology 59, 2 (2006), 127--140.
[2]
Allison, B. Z. and Pineda, J. A. ERPs evoked by different matrix sizes: implications for a brain computer interface (BCI) system. IEEE Transactions on Neural Systems and Rehabilitation Engineering 11, 2 (2003), 110--113.
[3]
Bandt, C., Weymar, M., Samaga, D. and Hamm, A. O. A simple classification tool for single-trial analysis of ERP components. Psychophysiology 46, 4 (2009), 747--757.
[4]
BioSemi. Active Two User Manual (Version 3.2, July 3, 2007). Amsterdam.
[5]
Birbaumer, N. Breaking the silence: Brain-computer interfaces (BCI) for communication and motor control. Psychophysiology 43, 6 (2006), 517--532.
[6]
Blankertz, B., Lemm, S., Treder, M., Haufe, S. and Müller, K.-R. Single-trial analysis and classification of ERP components - A tutorial. NeuroImage 56, 2 (2011), 814--825.
[7]
Delorme, A. and Makeig, S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods 134, 1 (2004), 9--21.
[8]
Donchin, E., Spencer, K. M. and Wijesinghe, R. The mental prosthesis: assessing the speed of a P300-based brain-computer interface. IEEE Transactions on Rehabilitation Engineering 8, 2 (2000), 174--179.
[9]
Duncan-Johnson, C. C. and Donchin, E. On Quantifying Surprise: The Variation of Event-Related Potentials With Subjective Probability. Psychophysiology 14, 5 (1977), 456--467.
[10]
Fabiani, M., Gratton, G., Karis, D. and Donchin, E. The definition, identification and reliability of measurement of the P300 component of the event-related brain potential. In Ackles, P., Jennings, J. and Coles, M. G. H. eds. Advances in psychophysiology, JAI Press, Greenwich, CT, 1987, 1--78.
[11]
Farwell, L. A. and Donchin, E. Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. Electroencephalography and Clinical Neurophysiology 70, 6 (1988), 510--523.
[12]
Fogelson, N., Wang, X., Lewis, J. B., Kishiyama, M. M., Ding, M. and Knight, R. T. Multimodal Effects of Local Context on Target Detection: Evidence from P3b. Journal of Cognitive Neuroscience 21, 9 (2009), 1680--1692.
[13]
Guger, C., Daban, S., Sellers, E., Holzner, C., Krausz, G., Carabalona, R., Gramatica, F. and Edlinger, G. How many people are able to control a P300-based brain-computer interface (BCI)? Neuroscience Letters 462, 1 (2009), 94--98.
[14]
Handy, T. Event-Related Potentials: A Methods Handbook. The MIT Press, Cambridge, MA, USA, 2004.
[15]
Hoffmann, U., Vesin, J.-M., Ebrahimi, T. and Diserens, K. An efficient P300-based brain-computer interface for disabled subjects. Journal of Neuroscience Methods 167, 1 (2008), 115--125.
[16]
Hong, B., Guo, F., Liu, T., Gao, X. and Gao, S. N200-speller using motion-onset visual response. Clinical Neurophysiology 120, 9 (2009), 1658--1666.
[17]
Ikegami, S., Takano, K., Saeki, N. and Kansaku, K. Operation of a P300-based brain-computer interface by individuals with cervical spinal cord injury. Clinical Neurophysiology 122, 5 (2011), 991--996.
[18]
Jeon, Y.-W. and Polich, J. P3a from a passive visual stimulus task. Clinical Neurophysiology 112, 12 (2001), 2202--2208.
[19]
Jin, J., Allison, B. Z., Brunner, C., Wang, B., Wang, X., Zhang, J., Neuper, C. and Pfurtscheller, G. P300 Chinese input system based on Bayesian LDA. Biomedizinische Technik Biomedical engineering 55 (2010), 5--18.
[20]
Krusienski, D. J., Sellers, E. W., McFarland, D. J., Vaughan, T. M. and Wolpaw, J. R. Toward enhanced P300 speller performance. Journal of Neuroscience Methods 167, 1 (2008), 15--21.
[21]
Mak, J. N., Arbel, Y., Minett, J. W., McCane, L. M., Yuksel, B., Ryan, D., Thompson, D., Bianchi, L. and Erdogmus, D. Optimizing the P300-based brain-computer interface: current status, limitations and future directions. Journal of Neural Engineering 8, 2 (2011), 025003.
[22]
Minett, J. W., Zheng, H.-Y., Fong, M. C.-M., Zhou, L., Peng, G. and Wang, W. S.-Y. A Chinese text input brain-computer interface based on the P300 speller. International Journal of Human-Computer Interaction 28, 7 (2012), 472--483.
[23]
Müller, K.-R., Krauledat, M., Dornhege, G., Curio, G. and Blankertz, B. Machine learning techniques for brain-computer interfaces. Biomedizinische Technik 49, Suppl 1 (2004), 11--22.
[24]
Nijboer, F., Sellers, E. W., Mellinger, J., Jordan, M. A., Matuz, T., Furdea, A., Halder, S., Mochty, U., Krusienski, D. J., Vaughan, T. M., Wolpaw, J. R., Birbaumer, N. and Kübler, A. A P300-based brain-computer interface for people with amyotrophic lateral sclerosis. Clinical Neurophysiology 119, 8 (2008), 1909--1916.
[25]
Piccione, F., Giorgi, F., Tonin, P., Priftis, K., Giove, S., Silvoni, S., Palmas, G. and Beverina, F. P300-based brain computer interface: Reliability and performance in healthy and paralysed participants. Clinical Neurophysiology 117, 3 (2006), 531--537.
[26]
Polich, J. Updating P300: An integrative theory of P3a and P3b. Clinical Neurophysiology 118, 10 (2007), 2128--2148.
[27]
Rencher, A. C. Methods of Multivariate Analysis. John Wiley & Sons, NY, USA, 2002.
[28]
Sellers, E. W. and Donchin, E. A P300-based brain-computer interface: Initial tests by ALS patients. Clinical Neurophysiology 117, 3 (2006), 538--548.
[29]
Sellers, E. W., Krusienski, D. J., McFarland, D. J., Vaughan, T. M. and Wolpaw, J. R. A P300 event-related potential brain-computer interface (BCI): The effects of matrix size and inter stimulus interval on performance. Biological Psychology 73, 3 (2006), 242--252.
[30]
Silvoni, S., Volpato, C., Cavinato, M., Marchetti, M., Priftis, K., Merico, A., Tonin, P., Koutsikos, K., Beverina, F. and Piccione, F. P300-based brain-computer interface communication: evaluation and follow-up in amyotrophic lateral sclerosis. Frontiers in Neuroscience 3, 60 (2009).
[31]
Sommer, W., Leuthold, H. and Matt, J. The expectancies that govern the P300 amplitude are mostly automatic and unconscious. Behavioral and Brain Sciences 21, 01 (1998), 149--150.
[32]
Squires, K., Wickens, C., Squires, N. and Donchin, E. The effect of stimulus sequence on the waveform of the cortical event-related potential. Science 193, 4258 (1976), 1142--1146.
[33]
Sutton, S., Braren, M., Zubin, J. and John, E. R. Evoked-potential correlates of stimulus uncertainty. Science 150, 3700 (1965), 1187--1188.
[34]
Takano, K., Komatsu, T., Hata, N., Nakajima, Y. and Kansaku, K. Visual stimuli for the P300 brain-computer interface: A comparison of white/gray and green/blue flicker matrices. Clinical Neurophysiology 120, 8 (2009), 1562--1566.
[35]
Townsend, G., LaPallo, B. K., Boulay, C. B., Krusienski, D. J., Frye, G. E., Hauser, C. K., Schwartz, N. E., Vaughan, T. M., Wolpaw, J. R. and Sellers, E. W. A novel P300-based brain-computer interface stimulus presentation paradigm: Moving beyond rows and columns. Clinical Neurophysiology 121, 7 (2010), 1109--1120.
[36]
Treder, M. and Blankertz, B. (C)overt attention and visual speller design in an ERP-based brain-computer interface. Behavioral and Brain Functions 6, 1 (2010), 28.
[37]
Vidal, J. J. Toward direct brain-computer communication. Annual review of biophysics and bioengineering 2 (1973), 157--180.

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  • (2022)Improving the performance of a gaze independent P300-BCI by using the expectancy waveJournal of Neural Engineering10.1088/1741-2552/ac60c8Online publication date: 24-Mar-2022

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    cover image ACM Conferences
    APCHI '12: Proceedings of the 10th asia pacific conference on Computer human interaction
    August 2012
    312 pages
    ISBN:9781450314961
    DOI:10.1145/2350046
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 28 August 2012

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    Author Tags

    1. brain--computer interface (bci)
    2. electroencephalography
    3. erp-based visual speller
    4. linear discriminant analysis (lda)
    5. oddball paradigm
    6. p300 speller

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    APCHI '12: Asia Pacific Conference on Computer Human Interaction
    August 28 - 31, 2012
    Shimane, Matsue-city, Japan

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    • (2022)Improving the performance of a gaze independent P300-BCI by using the expectancy waveJournal of Neural Engineering10.1088/1741-2552/ac60c8Online publication date: 24-Mar-2022

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