Advertisement

Neurofeedback

  • Stefanie Enriquez-Geppert
  • René J. Huster
  • Tomas Ros
  • Guilherme Wood
Chapter

Abstract

In the last years, innovations in technology and methodology, as well as increased knowledge about cortical oscillations , have significantly impacted the advancement of new neurofeedback approaches. As such, sham-controlled studies , showing evidence for enhanced performance of cognition after self-regulation of brain activity, have been published. Effects have been demonstrated regarding working memory (Hsueh et al. in Hum Brain Mapp 37(7):2662–2675, 2016), executive functions (Enriquez-Geppert et al. in Front Behav Neurosci 5(8):420, 2014), binding processes (Keizer et al. in NeuroImage 49(4):3404–3413, 2010a; Int J Psychophysiol 75(19):25–32, 2010b), and memory (Guez et al. in Memory 23(5):683–694, 2014), as well as real-life performance (Ros et al. in BMC Neurosci 10:87, 2009). In this chapter, we first present the rationale behind neurofeedback based on electroencephalography (EEG) and then list examples of recent studies demonstrating effects on cognition and everyday life performance. Subsequentially, the conceptualization of the self-regulation of brain activity, as well as neuroplastic effects evoked by neurofeedback follow. As a next step, issues regarding the specificity and efficacy of neurofeedback are discussed. Finally, we conclude with a summary and an outlook of EEG neurofeedback approaches.

Keywords

Self-regulation of endogenous oscillations Neurofeedback Conceptualization of self-control of brain activity Neuroplastic effects (Non)responsers Specificity and efficacy 

References

  1. Adamchic, I., Toth, T., Hauptmann, C., & Tass, P. A. (2014). Reversing pathologically increased EEG power by acoustic coordinated reset neuromodulation. Human Brain Mapping, 35(5), 2099–2118. doi: 10.1002/hbm.22314 PubMedCrossRefGoogle Scholar
  2. Allison, B., & Neuper, C. (2010). Could anyone use a BCI? In D. Tan & A. Nijholt (Eds.), Brain–Computer Interfaces: Human–Computer Interaction Series (pp. 35–54). London: Springer. doi: 10.1007/978-1-84996-272-8_3
  3. Arns, M., Kleinnijenhuis, M., Fallahpour, K., & Breteler, R. (2008). Golf performance enhancement and real-life neurofeedback training using personalized event-locked EEG profiles. Journal of Neurotherapy, 11(4), 11–18. doi: 10.1080/10874200802149656 CrossRefGoogle Scholar
  4. Babiloni, C., Del Percio, C., Iacoboni, M., Infarinato, F., Lizio, R., Marzano, N., et al. (2008). Golf putt outcomes are predicted by sensorimotor cerebral EEG rhythms. Journal of Physiology, 586, 131–139. doi: 10.1113/jphysiol.2007.141630 PubMedCrossRefGoogle Scholar
  5. Başar, E., & Güntekin, B. (2008). A review of brain oscillations in cognitive disorders and the role of neurotransmitters. Brain Research, 1235, 172–193. doi: 10.1016/j.brainres.2008.06.103 PubMedCrossRefGoogle Scholar
  6. Bazanova, O. M., & Aftanas, L. I. (2008). Individual measures of electroencephalogram alpha activity and non-verbal creativity. Neuroscience and Behavioral Physiology, 38(3), 227–235. doi: 10.1007/s11055-008-0034-y PubMedCrossRefGoogle Scholar
  7. Berger, H. (1929). Über das Elektroenzephalogramm des Menschen. Archiv für Psychiatrie und Nervenkrankheiten, 1929(87), 527–557.CrossRefGoogle Scholar
  8. Birbaumer, N., Ruiz, S., & Sitaram, R. (2013). Learned regulation of brain metabolism. Trends in Cognitive Sciences, 17(6), 295–302. doi: 10.1016/j.tics.2013.04.009 PubMedCrossRefGoogle Scholar
  9. Buzsáki, G., Logothetis, N., & Singer, W. (2013). Scaling brain size, keeping timing: evolutionary preservation of brain rhythms. Neuron, 80(3), 751–764. doi: 10.1016/j.neuron.2013.10.002 PubMedPubMedCentralCrossRefGoogle Scholar
  10. Cannon, R., Congedo, M., Lubar, J., & Hutchens, T. (2009). Differentiating a network of executive attention: LORETA neurofeedback in anterior cingulate and dorsolateral prefrontal cortices. International Journal of Neuroscience, 119, 404–441.PubMedCrossRefGoogle Scholar
  11. Cannon, R., Lubar, J., Congedo, M., Thornton, K., Towler, K., & Hutchens, T. (2007). The effects of neurofeedback training in the cognitive division of the cingulate gyrus. International Journal of Neuroscience, 117, 337–357.PubMedCrossRefGoogle Scholar
  12. Cavanagh, J. F., & Frank, M. J. (2014). Frontal theta as a mechanism for cognitive control. Trends in Cognitive Science, 18(8), 414–421. doi: 10.1016/j.tics.2014.04.012 CrossRefGoogle Scholar
  13. Cavanagh, J. F., Zambrano-Vazquez, L., & Allen, J. B. (2012). Theta lingua franca: A common mid-frontal substrate for action monitoring processes. Psychophysiology, 49(2), 220–238. doi: 10.1111/j.1469-8986.2011.01293.x PubMedCrossRefGoogle Scholar
  14. Cheng, M.-Y., Huang, C.-J., Chang, Y.-K., Koester, D., Schack, T., & Hung, T.-M. (2015). Sensorimotor rhythm neurofeedback enhances golf putting performance. Journal of Sport & Exercice Psychology, 37(6), 626–636. doi: 10.1123/jsep.2015-0166 CrossRefGoogle Scholar
  15. Cho, M. K., Jang, H. S., Jeong, S. H., Jang, I. S., Choi, B. J., & Lee, M. G. (2008). Alpha neurofeedback improves the maintaining ability of alpha activity. NeuroReport, 19(3), 315–317. doi: 10.1097/WNR.0b013e3282f4f022 PubMedCrossRefGoogle Scholar
  16. Cohen, M. X., & Donner, T. H. (2013). Midfrontal conflict-related theta-band power reflects neural oscillations that predict behavior. Journal of Neurophysiology, 110(12), 2752–2763. doi: 10.1152/jn.00479.2013 PubMedCrossRefGoogle Scholar
  17. Congedo, M., Lubar, J. F., & Joffe, D. (2004). Low resolution electromagnetic tomography neurofeedback. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 12, 387–397.PubMedCrossRefGoogle Scholar
  18. Cooke, A., Kavussanu, M., Gallicchio, G., Willoughby, A., McIntyre, D., & Ring, C. (2014). Preparation for action: Psychophysiological activity preceding a motor skill as a function of expertise, performance outcome, and psychological pressure. Psychophysiology, 51(4), 374–384. doi: 10.1111/psyp.1218 PubMedPubMedCentralCrossRefGoogle Scholar
  19. Donkers, F. C. L., Schwikert, S. R., Evans, A. M., Cleary, K. M., Perkins, D. O., & Belger, A. (2011). Impaired neural synchrony in the theta frequency range in adolescents at familial risk for schizophrenia. Frontiers in Psychiatry, 22(2), 55. doi: 10.3389/fpsyt.2011.00051 Google Scholar
  20. Egner, T., & Gruzelier, J. H. (2004). Ecological validity of neurofeedback: Modulation of slow wave EEG enhances musical performance. NeuroReport, 14(9), 1221–1224.CrossRefGoogle Scholar
  21. Emmert, K., Kopel, R., Sulzer, J., Brühl, A. B., Berman, B. D., Linden, D. E., …Johnston, S. (2016). Meta-analysis of real-time fMRI neurofeedback studies using individual participant data: How is brain regulation mediated? NeuroImage 124, 806–812. doi: 10.1016/j.neuroimage.2015.09.042
  22. Engel, A. K., & Singer, W. (2001). Temporal binding and the neural correlates of sensory awareness. Trends in Cognitive Science, 5(1), 16–25.CrossRefGoogle Scholar
  23. Engelbregt, H. J., Keeser, D., van Eijk, L., Suiker, E. M., Eichhorn, D., Karch, S., et al. (2016). Short and long-term effects of sham-controlled prefrontal EEG-neurofeedback training in healthy subjects. Clinical Neurophysiology, 172(4), 1931–1937. doi: 10.1016/j.clinph.2016.01.004 CrossRefGoogle Scholar
  24. Enriquez-Geppert, S., Huster, R. J., Figge, C., & Herrmann, C. S. (2013). Modulation of frontal-midline theta by neurofeedback. Biological Psychology, 95, 59–69. doi: 10.1016/j.biopsycho.2013.02.019 PubMedCrossRefGoogle Scholar
  25. Enriquez-Geppert, S., Huster, R. J., Figge, C., & Herrmann, C. S. (2014). Self-regulation of frontal-midline theta facilitates memory updating and mental set shifting. Frontiers in Behavioral Neuroscience, 5(8), 420. doi: 10.3389/fnbeh.2014.00420 Google Scholar
  26. Escolano, C., Aquilar, M., & Minguey, J. (2011). EEG-based upper alpha neurofeedback training improves working memory performance. In Conference Proceedings IEEE Engineering in Medicine and Biology Society (pp. 2327–2330). doi: 10.1109/IEMBS.2011.6090651
  27. Fauth, M., & Tetzlaff, C. (2016). Opposing effects of neuronal activity on structural plasticity. Frontiers in Neuroanatomy, 10, 75. doi: 10.3389/fnana.2016.00075 PubMedPubMedCentralCrossRefGoogle Scholar
  28. Fender, D. H. (1987). Source localization of brain electrical activity. In A. S. Gevins & A. Remond (Eds.), Handbook of electroencephalography and clinical neurophysiology (Vol. 1, pp. 355–399). Methods of analysis of brain electrical and magnetic signals. Amsterdam: Elsevier.Google Scholar
  29. Fink, A., & Neubauer, A. C. (2006). EEG alpha oscillations during the performance of verbal creativity tasks: Differential effects of sex and verbal intelligence. International Journal of Psychophysiology, 62(1), 46–53.PubMedCrossRefGoogle Scholar
  30. Ghaziri, J., Tucholka, A., Larue, V., Blanchette-Sylvetre, M., Reyburn, G., Gilbert, G., et al. (2013). Neurofeedback training induces changes in white and gray matter. Clinical EEG and Neuroscience, 44(4), 265–272. doi: 10.1177/1550059413476031 PubMedCrossRefGoogle Scholar
  31. Grabner, R. H., Fink, A., & Neubauer, A. C. (2007). Brain correlates of self-rated originality of ideas: Evidence from event-related power and phase-locking changes in the EEG. Behavioral Neuroscience, 121(1), 224–230.PubMedCrossRefGoogle Scholar
  32. Gruzelier, J. H. (2014a). EEG-neurofeedback for optimising performance. I. A review of cognitive and affective outcome in healthy participants. Neuroscience and Biobehavioral Review, 44, 124–141. doi: 10.1016/j.neubiorev.2013.09.015 CrossRefGoogle Scholar
  33. Gruzelier, J. H. (2014b). EEG-neurofeedback for optimising performance. II. Creativity, the performing arts and ecological validity. Neuroscience and Biobehavioral Review, 44, 142–158.CrossRefGoogle Scholar
  34. Gruzelier, J. H. (2014c). EEG-neurofeedback for optimising performance. III: A review of methodological and theoretical considerations. Neuroscience and Biobehavioral Review, 44, 159–182.CrossRefGoogle Scholar
  35. Gruzelier, J. H., Hirst, L., Holmes, P., & Leach, J. (2014a). Immediate effects of alpha-theta and sensory/motor rhythm feedback on music performance. International Journal of Psychophysiology, 93(1), 96–106. doi: 10.1016/j.ijpsycho.2014.03.009 PubMedCrossRefGoogle Scholar
  36. Gruzelier, J. H., Thompson, T., Redding, E., Brandt, R., & Steffert, R. (2014b). Application of Alpha-theta neurofeedback and heart rate variability training to young contemporary dancers: State anxiety and creativity. International Journal of Psychophysiology, 93(1), 105–111. doi: 10.1016/j.neubiorev.2013.11.004 PubMedCrossRefGoogle Scholar
  37. Guez, J., Rogel, A., Getter, N., Keha, E., Cohen, T., Amor, T., et al. (2014). Influence of electroencephalography neurofeedback training on episodic memory: A randomized, sham-controlled, double-blind study. Memory, 23(5), 683–694. doi: 10.1080/09658211.2014.921713 PubMedCrossRefGoogle Scholar
  38. Hanslmayr, S., Sauseng, P., Doppelmayr, M., Schabus, M., & Klimesch, W. (2005). Increasing individual upper alpha power by neurofeedback improves cognitive performance in human subjects. Applied Psychophysiology and Biofeedback., 30(1), 1–10.PubMedCrossRefGoogle Scholar
  39. Hardman, E., Gruzelier, J., Cheesman, K., Jones, C., Liddiard, D., Schleichert, H., et al. (1997). Frontal interhemispheric asymmetry: Self-regulation and individual differences in humans. Neuroscience Letters, 221(2), 117–120. doi: 10.1016/S0304-3940(96)13303-6 PubMedCrossRefGoogle Scholar
  40. Herrmann, C. S., & Knight, R. T. (2001). Mechanisms of human attention: Event-related potentials and oscillations. Neuroscience and Biobehavioral Review, 25(6), 465–476. doi: 10.1016/S0149-7634(01)00027-6 CrossRefGoogle Scholar
  41. Hoedlmoser, K., Pecherstorfer, T., Gruber, G., Anderer, P., Doppelmayr, M., Klimesch, W., et al. (2008). Instrumental conditioning of human sensorimotor rhythms (12–15 Hz) and its impact on sleep as well as declarative learning. Sleep, 31(19), 1401–1408. doi: 10.1016/j.ijpsycho.2012.07.182 PubMedPubMedCentralGoogle Scholar
  42. Horschig, J. M., Jensen, O., van Schouwenburg, M. R., Cools, R., & Bonnefond, M. (2014). Alpha activity reflects individual abilities to adapt to the environment. NeuroImage, 89, 235–243. doi: 10.1016/j.neuroimage.2013.12.018 PubMedCrossRefGoogle Scholar
  43. Hsueh, J.-J., Chen, T.-S., Chen, J.-J., & Shaw, F.-Z. (2016). Neurofeedback training of EEG alpha rhythm enhances episodic and working memory. Human Brain Mapping, 37(7), 2662–2675.PubMedCrossRefGoogle Scholar
  44. Hulme, S. R., Jones, O. D., & Abraham, W. C. (2013). Emerging roles of metaplasticity in behaviour and disease. Trends in Neurosciences, 36(6), 353–362. doi: 10.1016/j.tins.2013.03.007 PubMedCrossRefGoogle Scholar
  45. Huster, R. J., Mokom, Z. N., Enriquez-Geppert, S., & Herrmann, C. S. (2014). Brain–computer interfaces for EEG neurofeedback: Peculiarities and solutions. International Journal Psychophysiology., 91(1), 36–45. doi: 10.1016/j.ijpsycho.2013.08.011 CrossRefGoogle Scholar
  46. Ishihara, T., Hayashi, H., & Hishikawa, Y. (1981). Distribution of frontal midline theta rhythm (Fm0) on the scalp in different states (mental calculation, resting and drowsiness). Electroencephalography and Clinical Neurophysiology, 52(3), 19. doi: 10.1016/0013-4694(81)92408-1 Google Scholar
  47. Janssen, T. W., Bink, M., Gelade, K., van Mourik, R., Maras, A., & Oosterlaan, J. (2016). A randomized controlled trial into the effects of neurofeedback, methylphenidate, and physical activity on EEG power spectra in children with ADHD. Journal of Child Psychology and Psychiatry, 57(5), 633–644. doi: 10.1111/jcpp.12517 PubMedCrossRefGoogle Scholar
  48. Kamiya, J. (2011). The first communications about operant conditioning of the EEG. Journal of Neurotherapy, 15(1), 65–73.CrossRefGoogle Scholar
  49. Keizer, A. W., Verment, R. S., & Hommel, B. (2010a). Enhancing cognitive control through neurofeedback: A role of gamma-band activity in managing episodic retrieval. NeuroImage, 49(4), 3404–3413. doi: 10.1016/j.neuroimage.2009.11.023 PubMedCrossRefGoogle Scholar
  50. Keizer, A., Verschoor, M., Verment, R. S., & Hommel, B. (2010b). The effect of gamma enhancing neurofeedback on the control of feature bindings and intelligence measures. International Journal Psychophysiology., 75(19), 25–32. doi: 10.1016/j.ijpsycho.2009.10.011 CrossRefGoogle Scholar
  51. Kikkert, A. (2015). Predictors of neurofeedback efficacy: An exploratory study to the influence of personality and cognitive characteristics on the efficacy of theta and beta neurofeedback training. Dissertation, University of Leiden.Google Scholar
  52. Klimesch, W. (1999). EEG alpha and theta oscillations reflect cognitive and memory performance: A review and analysis. Brain Research Review, 29(2–3), 169–195. doi: 10.1016/S0165-0173(98)00056-3 CrossRefGoogle Scholar
  53. Kluetsch, R. C., Ros, R., Theberge, J., Frewen, P. A., Calhoun, V. D., Schmach, C., et al. (2014). Plastic modulation of PTSD resting-state networks and subjective wellbeing by EEG neurofeedback. Acta Psychiatrica Scandinavica, 130(2), 123–136. doi: 10.1111/acps.12229 PubMedCrossRefGoogle Scholar
  54. Knoblauch, A., Hauser, F., Gewaltig, M.-O., Körner, E., & Palm, G. (2012). Does spike-timing-dependent synaptic plasticity couple or decouple neurons firing in synchrony? Frontiers in Computational Neuroscience, 6, 55. doi: 10.3389/fncom.2012.00055 PubMedPubMedCentralCrossRefGoogle Scholar
  55. Kober, S. E., Schweiger, D., Witte, M., Reichert, J. L., Grieshofer, P., Neuper, C., et al. (2015a). Specific effects of EEG based neurofeedback training on memory functions in post-stroke victims. Journal Neuroengineering and Rehabilitation, 12(1), 1. doi: 10.1186/s12984-015-0105-6 CrossRefGoogle Scholar
  56. Kober, S. E., Witte, M., Ninaus, M., Koschutnig, K., Neuper, C., & Wood, G. (2015b). Spirituality and the ability to gain control over one’s own brain activity: A multimodal imaging study. Geneva: Organization for Human Brain Mapping.Google Scholar
  57. Kober, S. E., Witte, M., Ninaus, M., Neuper, C., & Wood, G. (2013). Learning to modulate one’s own brain activity: The effect of spontaneous mental strategies. Frontiers in Human Neuroscience, 7, 695. doi: 10.3389/fnhum.2013.00695 PubMedPubMedCentralCrossRefGoogle Scholar
  58. Kober, S. E., Witte, M., Stangl, M., Väljamäe, A., Neuper, C., & Wood, G. (2015c). Shutting down sensorimotor interference unblocks the networks for stimulus processing: An SMR neurofeedback training study. Clinical Neurophysiology, 126(1), 82–95. doi: 10.1016/j.clinph.2014.03.031 PubMedCrossRefGoogle Scholar
  59. Legenstein, R., Pecevski, D., & Maass, W. (2008). A learning theory for reward-modulated spike-timing-dependent plasticity with application to biofeedback. PLoS Computational Biology, 4(10), e1000180. doi: 10.1371/journal.pcbi.1000180 PubMedPubMedCentralCrossRefGoogle Scholar
  60. Lévesque, J., Beauregard, M., & Mensour, B. (2006). Effect of neurofeedback training on the neural substrates of selective attention in children with attention-deficit/hyperactivity disorder: A functional magnetic resonance imaging study. Neuroscience Letters, 394(3), 216–221.PubMedCrossRefGoogle Scholar
  61. Lubar, J. F., & Swartwood, M. (1995). Quantitative EEG and auditory event-related potentials in the evaluation of attention-deficit/hyperactivity disorder: Effects of methylphenidate and implications for neurofeedback training. Journal of Psychoeducational Assessment, 1938, 143–160.Google Scholar
  62. Maurizio, S., Liechti, M. D., Heinrich, H., Jäncke, L., Steinhausen, H. C., Walitza, S., et al. (2014). Comparing tomographic EEG neurofeedback and EMG biofeedback in children with attention-deficit/hyperactivity disorder. Biological Psychology, 95, 31–44.PubMedCrossRefGoogle Scholar
  63. Mitchell, D. J., McNaughton, N., Flanagan, D., & Kirk, I. J. (2008). Frontal-midline theta from the perspective of hippocampal “theta”. Progress in Neurobiology, 86(3), 156–185. doi: 10.1016/j.pneurobio.2008.09.005 PubMedCrossRefGoogle Scholar
  64. Monastra, V. J., Monastra, D. M., & George, S. (2002). The effects of stimulant therapy, EEG biofeedback, and parenting style on the primary symptoms of attention-deficit/hyperactivity disorder. Applied Psychophysiology and Biofeedback, 27(4), 231–249.PubMedCrossRefGoogle Scholar
  65. Musall, S., Von Pföstl, V., Rauch, A., Logothetis, N. K., & Whittingstall, K. (2014). Effects of neural synchrony on surface EEG. Cerebral Cortex, 24(4), 1045–1053. doi: 10.1093/cercor/bhs389 PubMedCrossRefGoogle Scholar
  66. Nan, W., Rodrigues, J. R., Ma, J., Qu, X., Wan, F., Mak, R.-I., et al. (2012). Individual alpha neurofeedback training effect on short term memory. International Journal Psychophysiology, 86(1), 83–87. doi: 10.1016/j.ijpsycho.2012.07.182 CrossRefGoogle Scholar
  67. Niendam, T. A., Lair, A. R., Kimberly, L. R., Dean, Y. M., & Carter, C. S. (2012). Meta-analytic evidence for a superordinate cognitive control network subserving diverse executive functions. Cognitive Affective and Behavioral Neuroscience, 12(2), 241–268. doi: 10.3758/s13415-011-0083-5 CrossRefGoogle Scholar
  68. Ninaus, M., Kober, S. E., Witte, M., Koschutnig, K., Neuper, C., & Wood, G. (2015). Brain volumetry and self-regulation of brain activity relevant for neurofeedback. Biological Psychology, 110, 126–133. doi: 10.1016/j.biopsycho.2015.07.009 PubMedCrossRefGoogle Scholar
  69. Ninaus, M., Kober, S. E., Witte, M., Koschutnig, K., Stangl, M., Neuper, C., et al. (2013). Neural substrates of cognitive control under the belief of getting neurofeedback training. Frontiers in Human Neuroscience, 7, 914. doi: 10.3389/fnhum.2013.00914 PubMedPubMedCentralCrossRefGoogle Scholar
  70. Okazaki, Y. O., Horschig, J. M., Luther, L., Oostenveld, R., Murakami, I., & Jensen, O. (2015). Real-time MEG neurofeedback training of posterior alpha activity modulates subsequent visual detection performance. NeuroImage, 107, 323–332. doi: 10.1016/j.neuroimage.2014.12.014 PubMedCrossRefGoogle Scholar
  71. Pascual-Marqui, R. D., Michel, C. M., & Lehmann, D. (1994). Low-resolution electromagnetic tomography—a new method for localizing electrical-activity in the brain. International Journal Psychophysiology, 18(1), 49–65. doi: 10.1016/0167-8760(84)90014-X CrossRefGoogle Scholar
  72. Pfister, J.-P., & Tass, P. A. (2010). STDP in oscillatory recurrent networks: Theoretical conditions for desynchronization and applications to deep brain stimulation. Frontiers in Computational Neuroscience, 4(July), 1–10. doi: 10.3389/fncom.2010.00022 Google Scholar
  73. Raymond, J., Sajid, I., Parkinson, L. A., & Gruzelier, J. H. (2005). Biofeedback and dance performance: A preliminary investigation. Applied Psychophysiology and Biofeedback, 30(1), 64–73.PubMedCrossRefGoogle Scholar
  74. Regestein, Q. R., Pegram, G. V., Cook, B., & Bradley, D. (1973). Alpha rhythm percentage maintained during 4- and 12-hour feedback periods. Psychosomatic Medicine, 35(3), 215–222.PubMedCrossRefGoogle Scholar
  75. Reichert, J. L., Kober, S. E., Neuper, C., & Wood, G. (2016a). Resting-state sensorimotor rhythm (SMR) power predicts the ability to up-regulate SMR in an EEG-instrumental conditioning paradigm. Clinical Neurophysiology, 126(11), 2068–2077. doi: 10.1016/j.clinph.2014.09.032 CrossRefGoogle Scholar
  76. Reichert, J. L., Kober, S. E., Schweiger, D., Grieshofer, P., Neuper, C., & Wood, G. (2016b). Shutting down sensorimotor interferences after stroke: A proof-of-principle SMR neurofeedback study. Frontiers in Human Neuroscience. doi: 10.3389/fnhum.2016.00348 PubMedPubMedCentralGoogle Scholar
  77. Reichert, J. L., Kober, S. E., Witte, M., Neuper, C., & Wood, G. (2016c). Age-related effects on verbal and visuospatial memory are mediated by theta and alpha II rhythms. International Journal Psychophysiology., 99, 67–78.CrossRefGoogle Scholar
  78. Rice, J. K., Rorden, C., Little, J. S., & Parra, L. C. (2013). Subject position affects EEG magnitudes. NeuroImage, 64, 476–484.PubMedCrossRefGoogle Scholar
  79. Rihs, T. A., Michel, C. M., & Thut, G. (2007). Mechanisms of selective inhibition in visual spatial attention are indexed by alpha-band EEG synchronization. European Journal of Neuroscience, 25(2), 603–610.PubMedCrossRefGoogle Scholar
  80. Ring, C., Cooke, A., Kavussnu, M., McIntyre, D., & Masters, R. (2015). Investigating the efficacy of neurofeedback training for expediting expertise and excellence in sport. Psychology of Sport and Exercise, 16(1), 118–127. doi: 10.1016/j.psychsport.2014.08.005 CrossRefGoogle Scholar
  81. Rogala, J., Ruewicz, J., Paluch, K., Kublik, E., Cetnarski, R., & Wrobel, A. (2016). The do’s and don’ts of neurofeedback training: A review of the controlled studies using healthy adults. Frontiers in Human Neuroscience. doi: 10.3389/fnhum.2016.00301 (eCollection 2016).
  82. Ros, T. J., Baars, B., Lanius, R. A., & Vuilleumier, P. (2014). Tuning pathological brain oscillations with neurofeedback: A systems neuroscience framework. Frontiers in Human Neuroscience, 8, 1008. doi: 10.1016/j.ijpsycho.2015.11.004 PubMedPubMedCentralCrossRefGoogle Scholar
  83. Ros, T., Frewen, P., Theberge, J., Michela, A., Kluetsch, R., Mueller, M., et al. (2016). Neurofeedback tunes scale-free dynamics in spontaneous brain activity. Cerebral Cortex. doi: 10.1093/cercor/bhw285 PubMedGoogle Scholar
  84. Ros, T., Moseley, M. R., Bloom, P. A., Benjamin, L., Parkinson, L. A., & Gruzelier, J. H. (2009). Optimizing microsurgical skills with EEG neurofeedback. BMC Neuroscience, 10, 87. doi: 10.1186/1471-2202-10-8 PubMedPubMedCentralCrossRefGoogle Scholar
  85. Ros, T., Munneke, M., Ruge, D., Gruzelier, J., & Rothwell, J. (2010). Endogenous control of waking brain rhythms induces neuroplasticity in humans. European Journal of Neuroscience, 31(4), 770–778. doi: 10.1111/j.1460-9568.2010.07100.x PubMedCrossRefGoogle Scholar
  86. Ros, T., Theberge, J., Frewen, P. A., Gluetsch, R., Densmore, M., Calhoun, V. D., et al. (2013). Mind over chatter: Plastic up-regulation of the fMRI salience network directly after EEG neurofeedback. NeuroImage, 65, 324–335. doi: 10.1016/j.neuroimage.2012.09.046 PubMedCrossRefGoogle Scholar
  87. Salari, N., Buchel, C., & Rose, M. (2013). Functional dissociation of ongoing oscillatory brain states. PLoS ONE, 7, e38090.CrossRefGoogle Scholar
  88. Sauseng, P., & Klimesch, W. (2008). What does phase information of oscillatory brain activity tell us about cognitive processes? Neuroscience and Biobehavioral Review, 32(5), 1001–1013.CrossRefGoogle Scholar
  89. Schabus, M., Heib, D. P. J., Lechinger, J., Griessenberger, H., Klimesch, W., Pawlizki, A., et al. (2014). Enhancing sleep quality and memory in insomnia using instrumental sensorimotor rhythm conditioning. Biological Psychology, 95, 126–134.PubMedCrossRefGoogle Scholar
  90. Schachter, D. L. (1976). The hypnagogic state: A critical review of the literature. Psychological Bulletin, 83(3), 452–481.CrossRefGoogle Scholar
  91. Schulz, P. E., & Fitzgibbons, J. C. (1997). Differing mechanisms of expression for short- and long-term potentiation. Journal of Neurophysiology, 78(1), 321–334.PubMedGoogle Scholar
  92. Sederberg, P. B., Kahana, M. J., Howard, M. W., Donner, E. J., & Madsen, J. R. (2003). Theta and gamma oscillations during encoding predict subsequent recall. Journal of Neuroscience, 23(34), 10809–10814.PubMedGoogle Scholar
  93. Sittenfeld, P., Budzynski, T., & Stoyva, J. (1976). Differential shaping of EEG theta rhythms. Biofeedback and Self Regulation, 1(1), 31–46.PubMedCrossRefGoogle Scholar
  94. Sporns, O. (2014). Contributions and challenges for network models in cognitive neuroscience. Nature Neuroscience, 17(5), 652–660.PubMedCrossRefGoogle Scholar
  95. Staufenbiel, S. M., Brouwer, A. M., Keizer, A. W., & van Wouwe, N. C. (2014). Effect of beta and gamma neurofeedback on memory and intelligence in the elderly. Biological Psychology, 95, 74–85. doi: 10.1016/j.biopsycho.2013.05.020 PubMedCrossRefGoogle Scholar
  96. Steriade, M. (1999). Coherent oscillations and short-term plasticity in corticothalamic networks. Trends in Neuroscience, 22(8), 337–345.CrossRefGoogle Scholar
  97. Sterman, M. B., Howe, R. C., & MacDonald, L. R. (1970). Facilitation of spindle burst sleep by conditioning of electroencephalographic activity while awake. Science, 167, 1146–1148.PubMedCrossRefGoogle Scholar
  98. Sterman, M. B., Wyrwicka, W., & Howe, R. (1969). Behavioral and neurophysiological studies of the sensorimotor rhythm in the cat. Electroencephalogramm and Clinical Neurophysiology, 27, 678–679.Google Scholar
  99. Tallon-Baudry, C., & Bertrand, O. (1999). Oscillatory gamma activity in humans and its role in object representation. Trends in Cognitive Science., 3(4), 151–162.CrossRefGoogle Scholar
  100. Tass, P. A., Silchenko, A. N., Hauptmann, C., Barnikol, U. B., & Speckmann, E. J. (2009). Long-lasting desynchronization in rat hippocampal slice induced by coordinated reset stimulation. Physical Review E, 80(1 Pt 1), 011902.CrossRefGoogle Scholar
  101. Thut, G., Nietzel, A., Brandt, S. A., & Pascual-Leone, A. (2006). Alpha-band electroencephalographic activity over occipital cortex indexes visuospatial attention bias and predicts visual target detection. Journal of Neuroscience, 26(37), 9494–9502.PubMedCrossRefGoogle Scholar
  102. van Gerven, M., & Jensen, O. (2009). Attention modulations of posterior alpha as a control signal for two-dimensional brain–computer interfaces. Journal of Neuroscience and Methods., 179(1), 78–84. doi: 10.1016/j.jneumeth.2009.01.016 CrossRefGoogle Scholar
  103. van Lutterveld, R., Houlihan, S. D., Pal, P., Cacchet, M. D., McFarlane-Blake, C., Sullivan, J. S., Ossadtchi, A., Druker, S., Cauer, C., & Brewer, J. A. (2016). Source-space EEG neurofeedback links subjective experience with brain activity during effortless awareness meditation. NeuroImage. doi: 10.1016/j.neuroimage.2016.02.047 (Epub ahead of print).
  104. Vernon, D., Egner, T., Cooper, N., Compton, T., Neilands, C., Sheri, A., et al. (2003). The effect of training distinct neurofeedback protocols on aspects of cognitive performance. International Journal Psychophysiology., 47(1), 75–85. doi: 10.1016/S0167-8760(02)00091-0 CrossRefGoogle Scholar
  105. Vossen, A., Gross, J., & Thut, G. (2015). Alpha power increase after transcranial alternating current stimulation at alpha frequency (α-tACS) reflects plastic changes rather than entrainment. Brain Stimulation., 8(3), 499–508. doi: 10.1016/j.brs.2014.12.004 PubMedPubMedCentralCrossRefGoogle Scholar
  106. Wang, J.-R., & Hsieh, S. (2014). Neurofeedback training improves attention and working memory performance. Clinical Neurophysiology, 142(1), 2406–2420. doi: 10.1016/j.clinph.2013.05.020 Google Scholar
  107. Whitt, J. L., Petrus, E., & Lee, H. K. (2013). Experience-dependent homeostatic synaptic plasticity in neocortex. Neuropharmacology, 78, 45–54. doi: 10.1016/j.neuropharm.2013.02.016 PubMedPubMedCentralCrossRefGoogle Scholar
  108. Witte, M. (2015). With body and soul—A comparison of self-regulatory mechanisms required for neurofeedback in triathletes and healthy controls. In OHBM Alpine chapter symposium and 15th Austrian fMRI symposium, Wien, 27 November 2015.Google Scholar
  109. Witte, M., Kober, S. E., Ninaus, M., Neuper, C., & Wood, G. (2013). Control beliefs can predict the ability to up-regulate sensorimotor rhythm during neurofeedback training. Frontiers in Human Neuroscience., 7, 478. doi: 10.3389/fnhum.2013.00478 PubMedPubMedCentralCrossRefGoogle Scholar
  110. Wood, G., Kober, S. E., Witte, M., & Neuper, C. (2014). On the need to better specify the concept of “control” in brain–computer-interfaces/neurofeedback research. Frontiers in Systems Neuroscience., 8, 171. doi: 10.3389/fnsys.2014.00171 PubMedPubMedCentralCrossRefGoogle Scholar
  111. Enriquez-Geppert, S., Huster, R. J., & Herrmann, C. S. (subm.). EEG-neurofeedback as a tool to modulate brain oscillations: A review tutorial.Google Scholar
  112. Zaehle, T., Rach, S., & Herrmann, C. S. (2010). Transcranial alternating current stimulation enhances individual alpha activity in human EEG. PLoS ONE, 5(11), e13766. doi: 10.1371/journal.pone.0013766 PubMedPubMedCentralCrossRefGoogle Scholar
  113. Zoefel, B., Huster, R. J., & Herrmann, C. S. (2010). Neurofeedback training of the upper alpha frequency band in EEG improves cognitive performance. NeuroImage., 54(2), 1427–1431. doi: 10.1016/j.neuroimage.2010.08.078 PubMedCrossRefGoogle Scholar
  114. Zotev, V., Krueger, F., Phillipps, R., Alvarez, R. P., Simmons, R. K., Bellgowan, P., et al. (2011). Self-regulation of amygdala activation using real-time fMRI neurofeedback. PLoS ONE, 6, e24522.PubMedPubMedCentralCrossRefGoogle Scholar
  115. Zotev, V., Phillips, R., Yuan, H., Misaki, M., & Bodurka, J. (2014). Self-regulation of human brain activity using simultaneous real-time fMRI and EEG neurofeedback. NeuroImage, 85, 985–995.PubMedCrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Stefanie Enriquez-Geppert
    • 1
  • René J. Huster
    • 2
  • Tomas Ros
    • 3
  • Guilherme Wood
    • 4
  1. 1.Department of Clinical and Developmental Neuropsychology, Faculty of Behavioural and Social SciencesUniversity of GroningenGroningenThe Netherlands
  2. 2.Department of PsychologyUniversity of OsloOsloNorway
  3. 3.Laboratory for Neurology and Imaging of Cognition, Department of NeurosciencesUniversity of GenevaGenevaSwitzerland
  4. 4.Department of NeuropsychologyUniversity of GrazGrazAustria

Personalised recommendations