Gamma band oscillations in the human brain (around 40 Hz) play a functional role in information processing, and a real-time assessment of gamma band activity could be used to evaluate the functional relevance more directly. Therefore, we developed a source based Brain-Computer-Interface (BCI) with an online detection of gamma band activity in a selective brain region in the visual cortex. The BCI incorporates modules for online detection of various artifacts (including microsaccades) and the artifacts were continuously fed back to the volunteer. We examined the efficiency of the source-based BCI for Neurofeedback training of gamma- and alpha-band (8–12 Hz) oscillations and compared the specificity for the spatial and frequency domain. Our results demonstrated that volunteers learned to selectively switch between modulating alpha- or gamma-band oscillations and benefited from online artifact information. The analyses revealed a high level of accuracy with respect to frequency and topography for the gamma-band modulations. Thus, the developed BCI can be used to manipulate the fast oscillatory activity with a high level of specificity. These selective modulations can be used to assess the relevance of fast neural oscillations for information processing in a more direct way, i.e., by the adaptive presentation of stimuli within well-described brain states.
References
[1]
Kelly, S.P.; Lalor, E.C.; Finucane, C.; McDarby, G.; Reilly, R.B. Visual spatial attention control in an independent brain-computer interface. IEEE Trans. Biomed. Eng. 2005, 52, 1588–1596, doi:10.1109/TBME.2005.851510.
[2]
Middendorf, M.; McMillan, G.; Calhoun, G.; Jones, K.S. Brain-computer interfaces based on the steady-state visual-evoked response. IEEE Trans. Rehabil. Eng. 2000, 8, 211–214, doi:10.1109/86.847819.
[3]
Donchin, E.; Spencer, K.M.; Wijesinghe, R. The mental prosthesis: Assessing the speed of a P300-based brain-computer interface. IEEE Trans. Rehabil. Eng. 2000, 8, 174–179, doi:10.1109/86.847808.
[4]
Pfurtscheller, G.; Brunner, C.; Schlogl, A.; Lopes da Silva, F.H. Mu rhythm (de)synchronization and EEG single-trial classification of different motor imagery tasks. Neuroimage 2006, 31, 153–159, doi:10.1016/j.neuroimage.2005.12.003.
[5]
Wolpaw, J.R.; McFarland, D.J. Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. Proc. Natl. Acad. Sci. USA 2004, 101, 17849–17854, doi:10.1073/pnas.0403504101.
[6]
Birbaumer, N.; Ghanayim, N.; Hinterberger, T.; Iversen, I.; Kotchoubey, B.; Kubler, A.; Perelmouter, J.; Taub, E.; Flor, H. A spelling device for the paralysed. Nature 1999, 398, 297–298, doi:10.1038/18581.
[7]
Lubar, J.F.; Shouse, M.N. EEG and behavioral changes in a hyperkinetic child concurrent with training of the sensorimotor rhythm (SMR): A preliminary report. Biofeedback Self Regul. 1976, 1, 293–306, doi:10.1007/BF01001170.
[8]
Fox, D.J.; Tharp, D.F.; Fox, L.C. Neurofeedback: An alternative and efficacious treatment for Attention Deficit Hyperactivity Disorder. Appl. Psychophysiol. Biofeedback 2005, 30, 365–373, doi:10.1007/s10484-005-8422-3.
[9]
Sterman, M.B.; Egner, T. Foundation and practice of neurofeedback for the treatment of epilepsy. Appl. Psychophysiol. Biofeedback 2006, 31, 21–35, doi:10.1007/s10484-006-9002-x.
[10]
Tallon-Baudry, C.; Bertrand, O. Oscillatory gamma activity in humans and its role in object representation. Trends Cogn. Sci. 1999, 3, 151–162, doi:10.1016/S1364-6613(99)01299-1.
[11]
Fries, P.; Reynolds, J.H.; Rorie, A.E.; Desimone, R. Modulation of oscillatory neuronal synchronization by selective visual attention. Science 2001, 291, 1560–1563, doi:10.1126/science.1055465.
[12]
Miltner, W.H.; Braun, C.; Arnold, M.; Witte, H.; Taub, E. Coherence of gamma-band EEG activity as a basis for associative learning. Nature 1999, 397, 434–436, doi:10.1038/17126.
[13]
Rose, M.; Buchel, C. Neural coupling binds visual tokens to moving stimuli. J. Neurosci. 2005, 25, 10101–10104, doi:10.1523/JNEUROSCI.2998-05.2005.
[14]
Wyart, V.; Tallon-Baudry, C. How ongoing fluctuations in human visual cortex predict perceptual awareness: Baseline shift versus decision bias. J. Neurosci. 2009, 29, 8715–8725, doi:10.1523/JNEUROSCI.0962-09.2009.
Romei, V.; Gross, J.; Thut, G. On the role of prestimulus alpha rhythms over occipito-parietal areas in visual input regulation: Correlation or causation? J. Neurosci. 2010, 30, 8692–8697, doi:10.1523/JNEUROSCI.0160-10.2010.
[17]
Kanai, R.; Chaieb, L.; Antal, A.; Walsh, V.; Paulus, W. Frequency-dependent electrical stimulation of the visual cortex. Curr. Biol. 2008, 18, 1839–1843, doi:10.1016/j.cub.2008.10.027.
[18]
Mensh, B.; Werfel, J.; Seung, H. BCI Competition 2003—Data set Ia: Combining gamma-band power with slow cortical potentials to improve single-trial classification of electroencephalographic signals. IEEE Trans. Biomed. Eng. 2004, 51, 1052–1056, doi:10.1109/TBME.2004.827081.
[19]
Palaniappan, R. Utilizing gamma band to improve mental task based brain-computer interface design. IEEE Trans. Neural Syst. Rehabil. Eng. 2006, 14, 299–303, doi:10.1109/TNSRE.2006.881539.
[20]
Grosse-Wentrup, M.; Scholkopf, B. High gamma-power predicts performance in sensorimotor-rhythm brain-computer interfaces. J. Neural Eng. 2012, 9, doi:10.1088/1741-2560/9/4/046001.
[21]
Salari, N.; Buchel, C.; Rose, M. Functional dissociation of ongoing oscillatory brain States. PLoS One 2012, 7, e38090, doi:10.1371/journal.pone.0038090.
[22]
Yuval-Greenberg, S.; Tomer, O.; Keren, A.S.; Nelken, I.; Deouell, L.Y. Transient induced gamma-band response in EEG as a manifestation of miniature saccades. Neuron 2008, 58, 429–441, doi:10.1016/j.neuron.2008.03.027.
[23]
Tallon-Baudry, C.; Bertrand, O.; Henaff, M.A.; Isnard, J.; Fischer, C. Attention modulates gamma-band oscillations differently in the human lateral occipital cortex and fusiform gyrus. Cereb. Cortex 2005, 15, 654–662.
[24]
Vernon, D.; Egner, T.; Cooper, N.; Compton, T.; Neilands, C.; Sheri, A.; Gruzelier, J. The effect of training distinct neurofeedback protocols on aspects of cognitive performance. Int. J. Psychophysiol. 2003, 47, 75–85, doi:10.1016/S0167-8760(02)00091-0.
[25]
Hanslmayr, S.; Sauseng, P.; Doppelmayr, M.; Schabus, M.; Klimesch, W. Increasing individual upper alpha power by neurofeedback improves cognitive performance in human subjects. Appl. Psychophysiol. Biofeedback 2005, 30, 1–10, doi:10.1007/s10484-005-2169-8.
[26]
Gruzelier, J.; Egner, T.; Vernon, D. Validating the efficacy of neurofeedback for optimising performance. Prog. Brain Res. 2006, 159, 421–431, doi:10.1016/S0079-6123(06)59027-2.
[27]
Malach, R.; Reppas, J.B.; Benson, R.R.; Kwong, K.K.; Jiang, H.; Kennedy, W.A.; Ledden, P.J.; Brady, T.J.; Rosen, B.R.; Tootell, R.B. Object-related activity revealed by functional magnetic resonance imaging in human occipital cortex. Proc. Natl. Acad. Sci. USA 1995, 92, 8135–8139, doi:10.1073/pnas.92.18.8135.
[28]
Rose, M.; Schmid, C.; Winzen, A.; Sommer, T.; Buchel, C. The functional and temporal characteristics of top-down modulation in visual selection. Cereb. Cortex 2005, 15, 1290–1298.
[29]
Congedo, M.; Lubar, J.F.; Joffe, D. Low-resolution electromagnetic tomography neurofeedback. IEEE Trans. Neural Syst. Rehabil. Eng. 2004, 12, 387–397, doi:10.1109/TNSRE.2004.840492.
[30]
Pascual-Marqui, R.D.; Michel, C.M.; Lehmann, D. Low resolution electromagnetic tomography: A new method for localizing electrical activity in the brain. Int. J. Psychophysiol. 1994, 18, 49–65, doi:10.1016/0167-8760(84)90014-X.
[31]
Krishnaveni, V.; Jayaraman, S.; Anitha, L.; Ramadoss, K. Removal of ocular artifacts from EEG using adaptive thresholding of wavelet coefficients. J. Neural Eng. 2006, 3, 338–346, doi:10.1088/1741-2560/3/4/011.
[32]
Keren, A.S.; Yuval-Greenberg, S.; Deouell, L.Y. Saccadic spike potentials in gamma-band EEG: Characterization, detection and suppression. Neuroimage 2009, 49, 2248–2263.
[33]
Boylan, C.; Doig, H.R. Effect of saccade size on presaccadic spike potential amplitude. Invest. Ophthalmol. Vis. Sci. 1989, 30, 2521–2527.
[34]
Knuth, D.E. The Art of Computer Programming, Volume 2: Seminumerical Algorithms., 3rd ed.; Addison-Wesley: Reading, MA, USA, 1997.
[35]
Welford, B.P. Note on a method for calculating corrected sums of squares and products. Technometrics 1962, 4, 419–420, doi:10.1080/00401706.1962.10490022.
Talairach, J.; Tournoux, P. Co-Planar Stereotaxic Atlas of the Human Brain; Thieme: Stuttgart, Germany, 1988.
[38]
Fuchs, M.; Kastner, J.; Wagner, M.; Hawes, S.; Ebersole, J.S. A standardized boundary element method volume conductor model. Clin. Neurophysiol. 2002, 113, 702–712, doi:10.1016/S1388-2457(02)00030-5.
[39]
Jurcak, V.; Tsuzuki, D.; Dan, I. 10/20, 10/10, and 10/5 systems revisited: Their validity as relative head-surface-based positioning systems. Neuroimage 2007, 34, 1600–1611, doi:10.1016/j.neuroimage.2006.09.024.
[40]
Sirota, A.; Montgomery, S.; Fujisawa, S.; Isomura, Y.; Zugaro, M.; Buzsaki, G. Entrainment of neocortical neurons and gamma oscillations by the hippocampal theta rhythm. Neuron 2008, 60, 683–697, doi:10.1016/j.neuron.2008.09.014.
[41]
Keizer, A.W.; Verment, R.S.; Hommel, B. Enhancing cognitive control through neurofeedback: A role of gamma-band activity in managing episodic retrieval. Neuroimage 2010, 49, 3404–3413, doi:10.1016/j.neuroimage.2009.11.023.
Berger, H. über das elektrenkephalogramm des menschen. Arch. Psycchiatr. Nervenkr. 1929, 87, 527–570. (in German).
[45]
Adrian, E.D.; Matthews, B.H. The interpretation of potential waves in the cortex. J. Physiol. 1934, 81, 440–471.
[46]
Hari, R.; Salmelin, R.; Makela, J.P.; Salenius, S.; Helle, M. Magnetoencephalographic cortical rhythms. Int. J. Psychophysiol. 1997, 26, 51–62, doi:10.1016/S0167-8760(97)00755-1.
[47]
Cannon, R.; Lubar, J.; Congedo, M.; Thornton, K.; Towler, K.; Hutchens, T. The effects of neurofeedback training in the cognitive division of the anterior cingulate gyrus. Int. J. Neurosci. 2007, 117, 337–357, doi:10.1080/00207450500514003.
