[Al-maqtari et al., 2009] A l-m aqtari, M. T., Taha, Z., and Moghavvemi, M. (2009). Steady state-V E P based BCI for control gripping of a Robotic hand. In Interna
tional Conference fo r Technical Postgraduates 2009, TE C H P O S 2009.
[Allison et al., 2010] Allison, B., Luth, T,, Valbuena, D., Teym ourian, A., Volosyak, I., and Graser, A. (2010). Bci demographics: how many (and w hat kinds of) people can use an ssvep bci? IE E E transactions on neural system s and rehabilita,tion
engineering, 18(2): 107-116.
[Allison and Sugiarto, 2008] Allison, B. and Sugiarto, I. (2008). Display optim ization in SSVEP BCIs. Com puter-Human Interaction, pages 2-5.
[Allison et al., 2008] Allison, B. Z., M cFarland, D. J., Schalk, G., Zheng, S. D., Jack son, M. M., and Wolpaw, J. R. (2008). Towards an independent brain-com puter interface using steady state visual evoked potentials. Clinical neurophysiology, 119(2):399-408.
[Armington, 1977] Arm ington, J. C. (1977). Psychophysical applications of hum an electroretinography. Journal o f the Optical Society o f America, 67(11):1458—1465. [Armington et al., 1971] A rm ington, J. C., Corwin, T. R., and M arsetta, R. (1971).
Simultaneously recorded retinal and cortical responses to p attern ed stimuli. Jour
nal o f the Optical Society o f America, 61(11): 1514—1521.
[Armington et al., 1967] A rm ington, J. C., G aarder, K., and Schick, a. M. (1967). Variation of spontaneous ocular and occipital responses w ith stim ulus p atterns.
Journal o f the Optical Society o f America, 57(12): 1534—1539.
[Baas et al., 2002] Baas, J. M. P., Kenemans, J. L., and M angun, G. R. (2002). Selective atten tio n to spatial frequency: An E R P and source localization analysis.
[Bakardjian et a l , 2010] Bakardjian, H., Tanaka, T., and Cichocki, A. (2010). Op tim ization of SSVEP brain responses w ith application to eight-com m and Brain- C om puter Interface. Neuroscience letters, 469(l):34-8.
[Baluja and C aruana, 1995] Baluja, S. and C aruana, R. (1995). Removing the genet ics from th e stan d ard genetic algorithm . International Society o f Machine Learn
ingi, pages 1-11.
[Bin et al., 2009a] Bin, G., Gao, X., Wang, Y., Hong, B., and Gao, S. (2009a). Vep- based brain-com puter interfaces: time, frequency, and code m odulations [research frontier]. Computational Intelligence Magazine, IEEE, 4(4):22-26.
[Bin et al., 2011] Bin, G., Gao, X., Wang, Y., Li, Y., Hong, B., and Gao, S. (2011). A high-speed BCI based on code m odulation VEP. Journal o f neural engineering, 8(2):025015.
[Bin et al., 2009b] Bin, G., Gao, X., Yan, Z., Hong, B., and Gao, S. (2009b). An online multi-channel ssvep-based brain-com puter interface using a canonical cor relation analysis m ethod. Journal o f neural engineering, 6(4):046002.
[Blakemore and Sutton, 1969] Blakemore, C. and Sutton, P. (1969). Size adaptation: a new aftereffect. Science (New York, N .Y .), 166(902):245-247.
[Boksem et al., 2005] Boksem, M. a. S., Meijman, T. F., and Lorist, M. M. (2005). Effects of m ental fatigue on attention: an E R P study. Brain research. Cognitive
brain research, 25(1):107-16.
[B urkitt et al., 2000] B urkitt, G. R., Silberstein, R. B., Cadusch, P. J., and Wood, a. W. (2000). Steady-state visual evoked potentials and travelling waves. Clin
ical neurophysiology : official journal o f the International Federation o f Clinical Neurophysiology, 111 (2):246-58.
[Celesia et al., 1982] Celesia, G. G., M iddleton, W. S., and Veterans, M. (1982). S teady-state and transient visual evoked potentials in clinical practice. Annals o f
[Chen et al., 2014] Chen, X., Chen, Z., Gao, S., and Gao, X. (2014). A high-ITR SSV EP-based BCI speller. Brain-C om puter Interfaces, (December): 1-11.
[Cheng et ah, 2002] Cheng, M., Gao, X., Gao, S., and Xu, D. (2002). Design and im plem entation of a brain-com puter interface w ith high transfer rates. Biomedical
Engineering, IE E E Transactions on, 49(10) :1181—1186.
[Diez et ah, 2013] Diez, P. F., Torres Muller, S. M., M ut, V. A., Laciar, E., Avila, E., Bastos-Filho, T. F., and Sarcinelli-Filho, M. (2013). Com m anding a robotic wheelchair w ith a high-frequency steady-state visual evoked p otential based brain- com puter interface. Medical Engineering and Physics, 35:1155-1164.
[Duszyk et ah, 2014] Duszyk, A., Bierzyska, M., Radzikowska, Z., Milanowski, P., Ku, R., Suffczyski, P., Michalska, M.,. abcki, M., Zwoliski, P., and Durka, P. (2014). Towards an optim ization of stim ulus param eters for brain-com puter inter faces based on steady state visual evoked potentials. P LoS ONE, 9 (ll):e ll2 0 9 9 . [Ficke and Science M anagem ent Corp. W ashington, 1992] Ficke, R. C. and Science
M anagem ent Corp. W ashington, D. C. (1992). Digest o f Data on Persons with
Disabilities [microform] / Robert C. Ficke. D istributed by ERIC Clearinghouse
[Washington, D.C.].
[Galloway, 1990] Galloway, N. (1990). H um an Brain Electrophysiology: Evoked Po tentials and Evoked M agnetic Fields in Science and Medicine. The B ritish Journal
o f Ophthalmology, 74(4):255.
[Gao et ah, 2003] Gao, X., Xu, D., Cheng, M., and Gao, S. (2003). A bci-based en vironm ental controller for the m otion-disabled. Neural System s and Rehabilitation
Engineering, IE E E Transactions on, 11 (2): 137-140.
[Garcia-Molina and Zhu, 2011] Garcia-M olina, G. and Zhu, D. (2011). O ptim al spa tial filtering for th e steady state visual evoked potential: BCI application. 2011
[Goldberg and O thers, 1989] Goldberg, D. E. and O thers (1989). Genetic algorithms
in search, optimization, and m achine learning, volume 412. Addison-Wesley Pro
fessional, 1 edition.
[Grill-Spector et al., 2006] Grill-Spector, K., Henson, R., and M artin, A. (2006). R epetition and th e brain: Neural models of stimulus-specific effects. Trends in
Cognitive Sciences, 10(1): 14-23.
[Guo et al., 2008] Guo, F., Hong, B., Gao, X., and Gao, S. (2008). A brain-com puter interface using m otion-onset visual evoked potential. Journal ofneura,l engineering, 5(4):477-85.
[Haslwanter, 2011] Haslwanter, T. (2011). M agno parvocellular pathw ays [online image], retrieved from http://com m ons.w ikim edia.org/w iki/filew ith permissions under by-sa 3.0 liscence.
[Heinrich and Bach, 2001] Heinrich, S. P. and Bach, M. (2001). A d ap tatio n dy namics in pattern-reversal visual evoked potentials. Documenta Ophthalmologica, 102(2) :141—156.
[Herrmann, 2001] H errm ann, C. S. (2001). H um an EEG responses to 1100 Hz flicker: resonance phenom ena in visual cortex and their potential correlation to cognitive phenomena. Experim ental Brain Research, 137(3-4):346-353.
[Hinterberger et al., 2004] H interberger, T., Schmidt, S., Neum ann, N., Mellinger, J., Blankertz, B., Curio, G., and Birbaum er, N. (2004). B rain-com puter communi cation and slow cortical potentials. IE E E Transactions on Biomedical Engineering, 51 (6): 1011—1018.
[Hong et al., 2009] Hong, B., Guo, F., Liu, T., Gao, X., and Gao, S. (2009). N200- speller using m otion-onset visual response. Clinical neurophysiology, 120(9): 1658—
[Hwang et al., 2013] Hwang, H.-J., Hwan Kim, D., 'Han, C.-H., and Im, C.-H. (2013). A new dual-frequency stim ulation m ethod to increase the num ber of visual stim uli for multi-class SSV EP-based brain-com puter interface (BCI). Brain research, 1515:66-77.
[Jia et al., 2011] Jia, C., Gao, X., and Hong, B. (2011). Frequency and Phase Mixed Coding in SSVEP-Based B rain-C om puter Interface. Biomedical Engineer
ing, IE E E , (c):l-7 .
[Jin et al., 2011] Jin, J., Zhang, Y., and W ang, X. (2011). A novel com bination of tim e phase and EEG frequency com ponents for SSV EP-based BCI. Neural
Inform ation Processing, pages 273-278.
[Johnson et al., 2011] Johnson, G., Waytowich, N., and Krusienski, D. J. (2011). The challenges of using scalp-EEG in p u t signals for continuous device control.
Lecture Notes in Com puter Science, 6780 LNAI:525-527.
[Johnson et al., 2010] Johnson, G. D., Waytowich, N. R., Cox, D. J., and Krusienski, D. J. (2010). Extending the discrete selection capabilities of th e P300 Speller to goal-oriented robotic arm control. 2010 3rd IE E E R A S and E M B S International
Conference on Biomedical Robotics and Biomechatronics, BioRob 2010, pages 572-
575.
[Kapeller et al., 2013] Kapeller, C., Hintermuller, C., A bu-Alqum san, M., Pruckl, R., Peer, A., and Guger, C. (2013). A bci using vep for continuous control of a mobile robot. Conference proceedings: IE E E Engineering in Medicine and Biology
Society., 2013:5254-5257.
[Kelly et al., 2004] Kelly, S. P., Lalor, E., Finucane, C., and Reilly, R. B. (2004). A comparison of covert and overt atten tio n as a control option in a steady-state visual evoked potential-based brain com puter interface. Conference proceedings:
[Klein et al., 1974] Klein, S., Stromeyer, C. F., and Ganz, L. (1974). The sim ulta neous spatial frequency shift: a dissociation between th e detection and perception of gratings. Vision Research, 14(12): 1421-1432.
[Ko, 2013] Ko, S. (2013). On multi-class classification through th e m inim ization of th e confusion m atrix norm. JM LR: Workshop and Conference Proceedings, (2004): 277-292.
[Kubler et al., 2004] Kubler, A., Neumann, N., W ilhelm, B., H interberger, T., and B irbaum er, N. (2004). Predictability of B rain-C om puter Interfaces. Journal o f
Psychophysiology, 18(2-3): 130-139.
[Kus et al., 2013] Kus, R., Duszyk, A., Milanowski, P., abecki, M., Bierzyska, M., Radzikowska, Z., Michalska, M., Zygierewicz, J., Suffczyski, P., and Durka, P. J. (2013). On the Q uantification of SSVEP Frequency Responses in H um an EEG in Realistic BCI Conditions. PLoS ONE, 8(10).
[Lalor and Foxe, 2009] Lalor, E. C. and Foxe, J. J. (2009). Visual evoked spread spectrum analysis (VESPA) responses to stimuli biased towards magnocellular and parvocellular pathways. Vision research, 49(l):127-33.
[Lalor et al., 2005] Lalor, E. C., Kelly, S. P., Finucane, C., Burke, R., Sm ith, R., Reilly, R. B., and McDarby, G. (2005). Steady-state V EP-based brain-com puter interface control in an immersive 3D gaming environment. Eurasip Journal on
Applied Signal Processing, 2005(19):3156-3164.
[Lalor et al., 2007] Lalor, E. C., Kelly, S. P., P earlm utter, B. a., Reilly, R. B., and Foxe, J. J. (2007). Isolating endogenous visuo-spatial atten tio n al effects using the novel visual-evoked spread spectrum analysis (VESPA) technique. The European
journal o f neuroscience, 26(12):3536-42.
[Lee et al., 2011] Lee, P.-L., Yeh, C.-L., Cheng, J. Y.-S., Yang, C.-Y., and Lan, G.-Y. (2011). An SSV EP-based BCI using high duty-cycle visual flicker. IE E E
[Leguire and Rogers, 1985] Leguire, L. E. and Rogers, G. L. (1985). P a tte rn elec- troretinogram : Use of noncorneal skin electrodes. Vision Research, 25(6):867-870. [Lesenfants et al., 2014] Lesenfants, D., Habbal, D., Lugo, Z., Lebeau, M., Horki, P.,
Amico, E., Pokorny, C., Gomez, F., Soddu, a., M iiller-Putz, G., Laureys, S., and Noirhomme, Q. (2014). An independent SSVEP-based brain-com puter interface in locked-in syndrome. Journal o f neural engineering, 11(3):035002.
[Lesenfants et al., 2011] Lesenfants, D., Partoune, N., Soddu, A., Lehembre, R., Noirhomme, Q., and M uller-Putz, G. (2011). Design of a covert SSV EP-based BCI for th e diagnosis of unresponsive patients. In: 5th Int. Brain-C om puter In
terface Conf., pages p p :l-4 .
[Li et al., 2013] Li, Y., Pan, J., Wang, F., and Yu, Z. (2013). A hybrid BCI system combining P300 and SSVEP and its application to wheelchair control. IE E E
transactions on bio-medical engineering, 60(11):3156—66.
[Lin et al., 2007] Lin, Z., Zhang, C., Wu, W ., and Gao, X. (2007). Frequency recog nition based on canonical correlation analysis for SSV EP-based BCIs. IE E E trans
actions on bio-medical engineering, 54(6 P t 2): 1172-6.
[Lotte et ah, 2007] Lotte, F., Congedo, M., Lecuyer, a., Lamarche, F., and Arnaldi, B. (2007). A review of classification algorithm s for EEG -based brain-com puter interfaces. Journal o f neural engineering, 4(2):R1-R13.
[Mackay et al., 2003] Mackay, A. M., B radnam , M. S., and Ham ilton, R. (2003). R apid detection of threshold V EPs. Clinical Neurophysiology, 114(6): 1009-1020. [McKeefry et al., 1996] McKeefry, D. J., Russell, M. H., Murray, I. J., and Ku-
likowski, J. J. (1996). A m plitude and phase variations of harm onic com ponents in hum an achrom atic and chrom atic visual evoked potentials. Visual neuroscience, 13(4) :639—53.
[Middendorf et al., 2000] Middendorf, M., McMillan, G., Calhoun, G., and Jones, K. S. (2000). B rain-com puter interfaces based on the steady-state visual-evoked response. IE E E transactions on rehabilitation engineering, 8(2):211—4.
[Movshon and Lennie, 1979] Movshon, J. A. and Lennie, P. (1979). Pattern-selective ad ap tatio n in visual cortical neurones. Nature, 278(5707):850-852.
[Muller et al., 2011] Muller, S. M. T., Diez, P. F., Bastos-Filho, T. F., Sarcinelli- Filho, M., M ut, V., and Laciar, E. (2011). SSVEP-BCI im plem entation for 37-40 Hz frequency range. Conference proceedings : IE E E Engineering in Medicine and
Biology Society., 2011:6352-5.
[Miiller-Putz and Pfurtscheller, 2008] M iiller-Putz, G. R. and Pfurtscheller, G. (2008). C ontrol of an electrical prosthesis w ith an ssvep-based bci. IE E E transac
tions on bio-medical engineering, 55(l):361-364.
[Ng et al., 2012] Ng, K. B., Bradley, A. P., and Cunnington, R. (2012). Stimulus specificity of a steady-state visual-evoked potential-based braincom puter interface.
Journal o f neural engineering, 9(3):036008.
[Peterson et al., 2005] Peterson, D. a., Knight, J. N., Kirby, M. J., Anderson, C. W ., and T h au t, M. H. (2005). Feature Selection and Blind Source Separation in an EEG -Based B rain-C om puter Interface. E U R A S IP Journal on Advances in Signal
Processing, 2005(19) :3128—3140.
[Pfurtscheller et al., 2010] Pfurtscheller, G., Solis-Escalante, T., O rtner, R., Linort- ner, P., and M iiller-Putz, G. R. (2010). Self-paced operation of an SSVEP-Based orthosis w ith and w ithout an imagery-based ”brain switch:” a feasibility study towards a hybrid BCI. IE E E transactions on neural system s and rehabilitation
engineering, 18(4):409-14.
[Ralaivola, 2012] Ralaivola, L. (2012). Confusion-based online learning and a passive- aggressive scheme. In: Neural Inform ation Processing System s Conference, pages 1-9.
[Rentschler et al., 1975] Rentschler, I., Hilz, R., and Grimm, W. (1975). Processing of positional inform ation in th e hum an visual system. Nature, 253(5491):444-445.
[Saetang et al., 2013] Saetang, J., Punsawad, Y., and W ongsawat, Y. (2013). On the perform ance comparison of using checkerboard and flash ball visual stim ulators for SSV EP-based BCI system. IF M B E Proceedings, 39 IFM BE: 1549-1552.
[Schalk, 2004] Schalk, G. (2004). BCI2000, a general-purpose brain-com puter inter face (BCI) system. IE E E Trans. Biomed Eng, 51:1034-1043.
[Schroeder, 2014] Schroeder, K. (2014). Visual system diagram [online image], re trieved from http://com m ons.w ikim edia.O rg/w iki/file:gray722-svg.svg w ith per missions under by-sa 3.0 liscence.
[Sharbrough et al., 1991] Sharbrough, F., C hatrain, C. E., Lesser, R. P., Luders, H., Nuwer, M., and Picton, T. W. (1991). A m earican Electroencephalographic Society guidelines for stan d ard electrode position nom enclature. J. Clin Neurophysiol,
8:200- 202.
[Sokol and Bloom, 1977] Sokol, S. and Bloom, B. (1977). M acular ergs elicited by checkerboard p a tte rn stimuli. In Lawwill, T., editor, ERG, VER and P sy
chophysics, volume 13 of Documenta Ophthalmologica, pages 299-305. Springer
Netherlands.
[Spuler, 2012] Spuler, M. (2012). One class SVM and Canonical C orrelation A naly sis increase perform ance in a c-V EP based B rain-C om puter Interface (BCI). In:
Proceedings o f 20th European Sym posium on Artificial Neural Networks (E S A N N 2012). Bruges, Belgium,, (April):pp: 103-108.
[Spuler et al., 2012] Spuler, M., Rosenstiel, W ., and Bogdan, M. (2012). Online ad ap tatio n of a c-V EP B rain-com puter Interface(BCI) based on error-related po tentials and unsupervised learning. PloS one, 7(12):e51077.
[Srihari Mukesh et al., 2006] Srihari Mukesh, T. M., Jag an ath an , V., and Reddy, M. R. (2006). A novel multiple frequency stim ulation m ethod for steady state V E P based brain com puter interfaces. Physiological m easurem ent, 27(1):61—71.
[Sutter, 1992] S utter, E. E. (1992). The brain response interface: com m unication through visually-induced electrical brain responses. Journal o f Microcomputer Applications, 15(1):31 - 45. Special Issue on C om puters for H andicapped People.
[Tanaka, 1996] Tanaka, K. (1996). Inferotem poral cortex and object vision. A nnual
review o f neuroscience, 19:109-39.
[Tobimatsu et al., 1993] Tobim atsu, S., K urita-Tashim a, S., Nakayam a-H irom atsu, M., and K ato, M. (1993). Effect of spatial frequency on transient and steady-state VEPs: stim ulation w ith checkerboard, square-wave grating and sinusoidal grating p attern s. Journal o f the neurological sciences, 118(1):17—24.
[Tomoda et al., 1991] Tomoda, H., Celesia, G. G., and Toleikis, S. C. (1991). Effect of spatial frequency on sim ultaneous recorded steady-state p a tte rn electroretino- grams and visual evoked potentials. Electroencephalography and Clinical Neuro
physiology - Evoked Potentials, 80(2):81-88.
[Tu et al., 2012] Tu, T., Xin, Y., Gao, X., and Gao, S. (2012). C hirp-m odulated visual evoked potential as a generalization of steady state visual evoked potential.
Journal o f neural engineering, 9(1):016008.
[Valbuena et al., 2007] Valbuena, D., Cyriacks, M., Friman, O., Volosyak, I., and Graser, A. (2007). B rain-com puter interface for high-level control of rehabilita tion robotic systems. In Rehabilitation Robotics, 2007. IC O R R 2007. IE E E 10th
International Conference on, pages 619-625.
[V ialatte et al., 2010] V ialatte, F.-B., M aurice, M., Dauwels, J., and Cichocki, A. (2010). Steady-state visually evoked potentials: focus on essential paradigm s and future perspectives. Progress in neurobiology, 90(4):418-38.
[Wang et al., 2008] Wang, Y., Gao, X., Hong, B., Jia, C., and Gao, S. (2008). B rain-com puter interfaces based on visual evoked potentials. IE E E engineering
in medicine and biology magazine, 27(5):64-71.
[Waytowich et al., 2010] Waytowich, N., Henderson, a., Krusienski, D., and Cox, D. (2010). R obot application of a brain com puter interface to staubli TX40 robots - early stages. World A utom ation Congress (W AC ), 2010.
[Waytowich and Krusienski, 2014] Waytowich, N. R. and Krusienski, D. J. (2014). Novel C haracterization of the Steady-State Visual Evoked P otential Spectrum of EEG. Braink KDD: International Workshop on Data M ining fo r Brain Science. [Waytowich and Krusienski, 2015] Waytowich, N. R. and Krusienski, D. J. (2015).
Spatial decoupling of targets and flashing stimuli for visual brain-com puter inter faces. Journal o f Neural Engineering, 12(3).
[Westheimer, 1982] W estheimer, G. (1982). The spatial grain of the perifoveal visual field. Vision Research, 22(1):157-162.
[Wolpaw and Wolpaw, ] Wolpaw, J. and Wolpaw, E. W. Oxford: Oxford University Press.
[Wolpaw et al., 2002] Wolpaw, J. R., B irbaum er, N., M cFarland, D. J., Pfurtscheller, G., and Vaughan, T. M. (2002). B rain-com puter interfaces for com m unication and control. Clinical neurophysiology : official journal o f the International Federation
o f Clinical Neurophysiology, 113(6):767-91.
[Wolpaw et al., 1991] Wolpaw, J. R., M cFarland, D. J., Neat, G. W ., and Forneris, C. a. (1991). An EEG -based brain-com puter interface for cursor control. Elec
troencephalography and clinical neurophysiology, 78(3):252-259.
[Xie et al., 2012] Xie, J., Xu, G., Wang, J., Zhang, F., and Zhang, Y. (2012). Steady- state m otion visual evoked potentials produced by oscillating N ew ton’s rings: im plications for brain-com puter interfaces. PloS one, 7(6):e39707.
[Yan et al., 2011] Yan, Z., Gao, X., and Gao, S. (2011). Right-and-left visual field stim ulation: A frequency and space mixed coding m ethod for SSVEP based brain- com puter interface. Science China Inform ation Sciences, 54(12):2492—2498.
[Zerafa et al., 2013] Zerafa, R., Camilleri, T., Falzon, 0 ., and Camilleri, K. R (2013). Comparison of plain and checkerboard stimuli for brain com puter interfaces based on steady state visual evoked potentials. International IE E E /E M B S Conference
on Neural Engineering, NER, pages 33-36.
[Zhang et al., 2012] Zhang, Y., Jin, J., Qing, X., Wang, B., and Wang, X. (2012). LASSO based stim ulus frequency recognition model for SSVEP BCIs. Biomedical
Signal Processing and Control, 7(2): 104-111.
[Zhu et al., 2010] Zhu, D., Bieger, J., G arcia Molina, G., and A arts, R. M. (2010). A survey of stim ulation m ethods used in SSV EP-based BCIs. Computational in
VITA
Nicholas R. Waytowich
D epartm ent of Biomedical Engineering Old Dominion University
Norfolk, VA 23529
Nicholas Waytowich recieved a B.S. in Mechanical Engineering in 2010 at the Uni versity of N orth Florida w ith a specialization in Robotics, and a M asters in Electrical and C om puter Engineering in 2013 a t Old Dominion University w ith an emphasis in neural signal processing and machine learning. During his Ph.D . studies, he worked as a graduate research assistant in th e Advanced Signal Processing in Engineering and Neuroscience (ASPEN) Lab under the advism ent and m entorship of Dr. Dean J Krusienski. His research areas of interest include signal processing and machine learning, image processing, brain-com puter interface developm ent and experim ental design.