All Title Author
Keywords Abstract

PLOS ONE  2014 

Generating Visual Flickers for Eliciting Robust Steady-State Visual Evoked Potentials at Flexible Frequencies Using Monitor Refresh Rate

DOI: 10.1371/journal.pone.0099235

Full-Text   Cite this paper   Add to My Lib


In the study of steady-state visual evoked potentials (SSVEPs), it remains a challenge to present visual flickers at flexible frequencies using monitor refresh rate. For example, in an SSVEP-based brain-computer interface (BCI), it is difficult to present a large number of visual flickers simultaneously on a monitor. This study aims to explore whether or how a newly proposed frequency approximation approach changes signal characteristics of SSVEPs. At 10 Hz and 12 Hz, the SSVEPs elicited using two refresh rates (75 Hz and 120 Hz) were measured separately to represent the approximation and constant-period approaches. This study compared amplitude, signal-to-noise ratio (SNR), phase, latency, scalp distribution, and frequency detection accuracy of SSVEPs elicited using the two approaches. To further prove the efficacy of the approximation approach, this study implemented an eight-target BCI using frequencies from 8–15 Hz. The SSVEPs elicited by the two approaches were found comparable with regard to all parameters except amplitude and SNR of SSVEPs at 12 Hz. The BCI obtained an averaged information transfer rate (ITR) of 95.0 bits/min across 10 subjects with a maximum ITR of 120 bits/min on two subjects, the highest ITR reported in the SSVEP-based BCIs. This study clearly showed that the frequency approximation approach can elicit robust SSVEPs at flexible frequencies using monitor refresh rate and thereby can largely facilitate various SSVEP-related studies in neural engineering and visual neuroscience.


[1]  Regan D (1989) Human Brain electrophysiology: Evoked potentials and Evoked Magnetic Fields in Science and Medicine. New York: Elsevier. 672 p.
[2]  Wang Y, Gao X, Hong B, Jia C, Gao S (2008) Brain-computer interfaces based on visual evoked potentials: feasibility of practical system design. IEEE EMB Mag 27: 64–71. doi: 10.1109/memb.2008.923958
[3]  Vialatte FB, Maurice M, Dauwels J, Cichocki A (2010) Steady-state visually evoked potentials: Focus on essential paradigms and future perspectives. Prog Neurobiol 90: 418–438. doi: 10.1016/j.pneurobio.2009.11.005
[4]  Morgan ST, Hansen JC, Hillyard SA (1996) Selective attention to stimulus location modulates the steady-state visual evoked potential. Proc Natl Acad Sci USA 93: 4770–4774. doi: 10.1073/pnas.93.10.4770
[5]  Muller MM, Picton TW, Valdes-Sosa P, Riera J, Teder-Salejarvi WA, et al. (1998) Effects of spatial selective attention on the steady-state visual evoked potential in the 20–28 hz range. Cogn Brain Res 6: 249–261. doi: 10.1016/s0926-6410(97)00036-0
[6]  Muller MM, Andersen S, Trujillo NJ, Valdes-Sosa P, Malinowski P, et al. (2006) Feature-selective attention enhances color signals in early visual areas of the human brain. Proc Natl Acad Sci USA 103: 14250–14254. doi: 10.1073/pnas.0606668103
[7]  Andersen SK, Muler MM (2010) Behavioral performance follows the time course of neural facilitation and suppression during cued shifts of feature selective attention. Proc Natl Acad Sci USA 107: 13878–13882. doi: 10.1073/pnas.1002436107
[8]  Wolpaw JR, Birbaumer N, McFarland DJ, Pfurtscheller G, Vaughan TM (2002) Brain-computer interfaces for communication and control. Clin Neurophysiol 113: 767–791. doi: 10.1016/s1388-2457(02)00057-3
[9]  Middendorf M, McMillan G, Calhoun G, Jones KS (2000) Brain computer interfaces based on the steady-state visual-evoked response. IEEE Trans Rehabili Eng 8: 211–214. doi: 10.1109/86.847819
[10]  Cheng M, Gao X, Gao S, Xu D (2002) Design and implementation of a brain-computer interface with high transfer rates. IEEE Trans Biomed Eng 49: 1181–1186. doi: 10.1109/tbme.2002.803536
[11]  Gao X, Xu D, Cheng M, Gao S (2003) A BCI-based environmental controller for the motion-disabled. IEEE Trans Neural Syst Rehabili Eng 11: 137–140. doi: 10.1109/tnsre.2003.814449
[12]  Lalor EC, Kelly SP, Finucane C, Burke R, Smith R, et al. (2005) Steady-state vep-based brain-computer interface control in an immersive 3d gaming environment. EURASIP J Appl Signal Process 19: 3156–3164. doi: 10.1155/asp.2005.3156
[13]  Wang Y, Wang R, Gao X, Hong B, Gao S (2006) A practical VEP-based brain-computer interface. IEEE Trans Neural Syst Rehabili Eng 14: 234–240. doi: 10.1109/tnsre.2006.875576
[14]  Bin G, Gao X, Wang Y, Hong B, Gao S (2009) Research frontier: VEP based brain-computer interfaces: time, frequency, and code modulations. IEEE Comput Intell Mag 4: 22–26. doi: 10.1109/mci.2009.934562
[15]  Daniel BPM, Whiteridge D (1961) The representation of the visual field on the cerebral cortex in monkeys. J Physiol 159: 203–221.
[16]  Wang YT, Wang Y, Jung TP (2011) A cell-phone-based brain-computer interface for communication in daily life. J Neural Eng 8: 025018 (5pp).. doi: 10.1088/1741-2560/8/2/025018
[17]  Wang YT, Wang Y, Cheng CK, Jung TP (2013) Developing stimulus presentation on mobile devices for a truly portable SSVEP-based BCI. Proc 35th Intl IEEE EMBS Conf 5271–5274.
[18]  Chi YM, Wang YT, Wang Y, Maier C, Jung TP, et al. (2012) Dry and noncontact EEG sensors for mobile brain-computer interfaces. IEEE Trans Neural Syst Rehabili Eng 20: 228–235. doi: 10.1109/tnsre.2011.2174652
[19]  Lin YP, Wang Y, Jung TP (2013) A mobile SSVEP-based brain-computer interface for freely moving humans: The robustness of canonical correlation analysis to motion artifacts. Proc 35th Intl IEEE EMBS Conf 1350–1353.
[20]  Wang Y, Wang YT, Jung TP (2010) Visual stimulus design for high-rate SSVEP. Electron Lett 46: 1057–1058. doi: 10.1049/el.2010.0923
[21]  Nan W, Wong CM, Wang B, Wan F, Mak PU, et al.. (2011) A comparison of minimum energy combination and canonical correlation analysis for SSVEP detection. Proc 5th Intl IEEE EMBS Conf Neural Eng 469–472.
[22]  Cao T, Wang X, Wang B, Wong CM, Wan F, et al.. (2011) A high rate online SSVEP based brain-computer interface speller. Proc 5th Intl IEEE EMBS Conf Neural Eng 465–468.
[23]  Ng KB, Bradley AP, Cunnington R (2012) Stimulus specificity of a steady state visual-evoked potential-based brain-computer interface. J Neural Eng 9: 036008 (13pp).. doi: 10.1088/1741-2560/9/3/036008
[24]  Gergondet P, Druon S, Kheddar A, Hintermuller C, Guger C, et al.. (2011) Using brain-computer interface to steer a humanoid robot, Proc IEEE Intl Conf Robotics and Biomimetics 192–197.
[25]  Jia C, Gao X, Hong B, Gao S (2011) Frequency and phase mixed coding in SSVEP-based brain-computer interface. IEEE Trans Biomed Eng 58: 200–206. doi: 10.1109/tbme.2010.2068571
[26]  Regan D (1966) Some characteristics of average steady-state and transient response evoked by modulated light. EEG Clin Neurophysiol 20: 238–248. doi: 10.1016/0013-4694(66)90088-5
[27]  Spekreijse H, Estevez MA, Reits D (1977) Visual evoked potentials and the physiological analysis of visual processes in man, In: Desmedt JE, editor. Visual evoked potentials in man: new development. Oxford: Clarendon press. 16–89.
[28]  Delorme A, Makeig S (2004) EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods 134: 9–21. doi: 10.1016/j.jneumeth.2003.10.009
[29]  Bin G, Gao X, Yan Z, Hong B, Gao S (2009) An online multi-channel SSVEP-based brain-computer interface using a canonical correlation analysis method. J Nueral Eng 6: 046002 (6pp).. doi: 10.1088/1741-2560/6/4/046002
[30]  Lin Z, Zhang C, Wu W, Gao X (2007) Frequency recognition based on canonical correlation analysis for SSVEP-based BCIs. IEEE Trans Biomed Eng 54: 1172–1176. doi: 10.1109/tbme.2006.889197
[31]  Friman O, Volosyak I, Graser A (2007) Multiple channel detection of steady-state visual evoked potentials for brain-computer interfaces. IEEE Trans Biomed Eng 54: 742–750. doi: 10.1109/tbme.2006.889160
[32]  Brainard DH (1997) The psychophysics toolbox. Spat Vis 10: 433–436. doi: 10.1163/156856897x00357
[33]  Russo FD, Spinelli D (1999) Electrophysiological evidnece for an early attentional mechanism in visual processing in humans. Vision Res 39: 2975–2985. doi: 10.1016/s0042-6989(99)00031-0
[34]  Herrmann CS (2001) Human EEG responses to 1–100 Hz flicker: Resonance phenomena in visual cortex and their potential correlation to cognitive phenomena, Exp Brain Res. 137: 346–353. doi: 10.1007/s002210100682
[35]  Nakanishi M, Wang Y, Wang YT, Mitsukura Y, Jung TP (2013) Integrating interference frequency components elicited by monitor refresh rate to enhance frequency detection of SSVEPs. Proc 6th Intl IEEE EMBS Conf Neural Eng 1092–1095.
[36]  Bakardjian H, Tanaka T, Cichocki A (2010) Optimization of SSVEP brain responses with application to eight-command brain-computer interface. Neurosci Lett 469: 34–38. doi: 10.1016/j.neulet.2009.11.039
[37]  Wang Y, Wang R, Gao X, Gao S (2005) Brain-computer interface based on the high frequency SSVEP. Proc 1st Intl NIC Conf 37–39.
[38]  Diez PF, Mut VA, Avila Perona EM, Laciar Leber E (2011) Asynchronous BCI control using high-frequency SSVEP. J Neuroeng Rehabil 8: 39. doi: 10.1186/1743-0003-8-39
[39]  Kluge T, Hartmann M (2007) Phase coherent detection of steady-state evoked potentials: Experimental results and application to brain–computer interfaces. Proc 3rd Intl IEEE EMBS Conf Neural Eng 425–429.
[40]  Lopez-Gordo MA, Prieto A, Pelayo F, Morillas C (2010) Use of Phase in Brain–Computer Interfaces based on Steady-State Visual Evoked Potentials. Neural Process Lett 32: 1–9. doi: 10.1007/s11063-010-9139-8
[41]  Lee PL, Sie JJ, Liu YJ, Wu CH, Lee MH, et al. (2010) An SSVEP-actuated brain computer interface using phase-tagged flickering sequences: a cursor system. Ann Biomed Eng 38: 2383–2397. doi: 10.1007/s10439-010-9964-y
[42]  Hwang HJ, Lim JH, Jung YJ, Choi H, Lee SW, et al. (2012) Development of an SSVEP-based BCI spelling system adopting a QWERTY-style LED keyboard. J Neurosci Methods 208: 59–65. doi: 10.1016/j.jneumeth.2012.04.011
[43]  Shyu KK, Lee PL, Liu YJ, Sie JJ (2010) Dual-frequency steady-state visual evoked potential for brain computer interface. Neurosci Lett 483: 28–31. doi: 10.1016/j.neulet.2010.07.043


comments powered by Disqus

Contact Us


微信:OALib Journal