Learning to modulate one's own brain activity: The effect of spontaneous mental strategies

Frontiers in Human Neuroscience

Volumn , Issue OCT, 2013, Pages

  Kober, Silvia E ^a   Witte, Matthias ^a   Ninaus, Manuel ^a   Neuper, Christa ^a,b   Wood, Guilherme ^a  

^a UNIVERSITY OF GRAZ   (Austria)

^b GRAZ UNIVERSITY OF TECHNOLOGY   (Austria)

Author keywords

EEG; Gamma; Implicit learning; Mental strategies; Neurofeedback; Sensorimotor rhythm

Indexed keywords

ADULT; ARTICLE; CONTROLLED STUDY; ELECTROENCEPHALOGRAM; ELECTROENCEPHALOGRAPHY; FEMALE; GAMMA RHYTHM; HUMAN; HUMAN EXPERIMENT; LEARNING; MALE; MENTAL PERFORMANCE; MENTAL TASK; NEUROFEEDBACK; NORMAL HUMAN; SENSORIMOTOR RHYTHM;

EID: 84933672125     PISSN: 16625161     EISSN: None     Source Type: Journal    
DOI: 10.3389/fnhum.2013.00695     Document Type: Article

References (64)

1. Allison, B., and Neuper, C. (2010). "Could anyone use a BCI?" in Brain-Computer Interfaces: Human-Computer Interaction Series, eds D. Tan and A. Nijholt (London: Springer-Verlag), 35-54.
2. Angelakis, E., Stathopoulou, S., Frymiare, J. L., Green, D. L., Lubar, J. F., and Kounios, J. (2007). EEG neurofeedback: a brief overview and an example of peak alpha frequency training for cognitive enhancement in the elderly. Clin. Neuropsychol. 21, 110-129. doi: 10.1080/13854040600744839
3. Banquet, J. P. (1973). Spectral analysis of the EEG in meditation. Electroencephalogr. Clin. Neurophysiol. 35, 143-151. doi: 10.1016/0013-4694(73)90170-3
4. Bird, B. L., Newton, F. A., Sheer, D. E., and Ford, M. (1978). Biofeedback training of 40-Hz EEG in humans. Biofeedback Self. Regul. 3, 1-11. doi: 10.1007/BF00998559
5. Blankertz, B., Sannelli, C., Halder, S., Hammer, E. M., Kübler, A., Müller, K.-R., et al. (2010). Neurophysiological predictor of SMR-based BCI performance. Neuroimage 51, 1303-1309. doi: 10.1016/j.neuroimage.2010.03.022
6. Brain Products GmbH. (2009). BrainVision Analyzer 2.0.1 User Manual, 3rd Edn. Munich: Brain Products GmbH.
7. Burde, W., and Blankertz, B. (2006). "Is the locus of control of reinforcement a predictor of brain-computer interface performance?" in Proceedings of the 3rd International Brain-Computer Interface Workshop and Training Course, (Graz), 76-77.
8. Coben, R., and Evans, J. (2010). Neurofeedback and Neuromodulation Techniques and Applications. London: Academic.
9. Crawford, J., and Garthwaite, P. (2004). Statistical methods for single-case studies in neuropsychology: comparing the slope of a patient's regression line with those of a control sample. Cortex 40, 533-548. doi: 10.1016/S0010-9452(08)70145-X
10. Crawford, J., and Garthwaite, P. H. (2002). Investigation of the single case in neuropsychology: confidence limits on the abnormality of test scores and test score differences. Neuropsychologia 40, 1196-1208. doi: 10.1016/S0028-3932(01)00224-X
11. Crawford, J. R., Garthwaite, P. H., and Porter, S. (2010). Point and interval estimates of effect sizes for the case-controls design in neuropsychology: rationale, methods, implementations, and proposed reporting standards. Cognitive Neuropsychol. 27, 245-260. doi: 10.1080/02643294.2010.513967
12. Crawford, J., and Howell, D. (1998). Comparing an individual's test score against norms derived from small samples. Clin. Neuropsychol. 12, 482-486. doi: 10.1076/clin.12.4.482.7241
13. Curran, E., and Stokes, M. (2003). Learning to control brain activity: a review of the production and control of EEG components for driving brain-computer interface (BCI) systems. Brain Cogn. 51, 326-336. doi: 10.1016/S0278-2626(03)00036-8
14. de Zambotti, M., Bianchin, M., Magazzini, L., Gnesato, G., and Angrilli, A. (2012). The efficacy of EEG neurofeedback aimed at enhancing sensory-motor rhythm theta ratio in healthy subjects. Exp. Brain Res., 221, 69-74. doi: 10.1007/s00221-012-3148-y
15. Dempster, T., and Vernon, D. (2009). Identifying indices of learning for alpha neurofeedback training. Appl. Psychophysiol. Biofeedback 34, 309-318. doi: 10.1007/s10484-009-9112-3
16. Doppelmayr, M., and Weber, E. (2011). Effects of SMR and theta/beta neurofeedback on reaction times, spatial abilities, and creativity. J. Neurother. 15, 115-129. doi: 10.1080/10874208.2011.570689
17. Egner, T., Zech, T., and Gruzelier, J. (2004). The effects of neurofeedback training on the spectral topography of the electroencephalogram. Clin. Neurophysiol. 115, 2452-2460. doi: 10.1016/j.clinph.2004.05.033
18. leming, S. M. Dolan, R. J. (2012). The neural basis of metacognitive ability. Philos. Trans. R. Soc B Biol. Sci. 367, 1338-1349. doi: 10.1098/rstb.2011.0417
19. Friedrich, E. V., Scherer, R., and Neuper, C. (2012). The effect of distinct mental strategies on classification performance for brain-computer interfaces. Int. J. Psychophysiol. 84, 86-94. doi: 10.1016/j.ijpsycho.2012.01.014
20. Friedrich, E. V., Scherer, R., and Neuper, C. (2013). Long-term evaluation of a 4-class imagery-based brain-computer interface. Clin. Neurophysiol. 124, 916-927. doi: 10.1016/j.clinph.2012.11.010
21. Gevensleben, H., Holl, B., Albrecht, B., Schlamp, D., Kratz, O., Studer, P., et al. (2009). Distinct EEG effects related to neurofeedback training in children with ADHD: a randomized controlled trial. Int. J. Psychophysiol. 74, 149-157. doi: 10.1016/j.ijpsycho.2009.08.005
22. Gruzelier, J., and Egner, T. (2005). Critical validation studies of neurofeedback. Child Adolesc. Psychiatr. Clin. N. Am. 14, 83-104. doi: 10.1016/j.chc.2004.07.002
23. Gruzelier, J., Inoue, A., Smart, R., Steed, A., and Steffert, T. (2010). Acting performance and flow state enhanced with sensory-motor rhythm neurofeedback comparing ecologically valid immersive VR and training screen scenarios. Neurosci. Lett. 480, 112-116. doi: 10.1016/j.neulet.2010.06.019
24. Halder, S., Hammer, E. M., Kleih, S. C., Bogdan, M., Rosenstiel, W., Birbaumer, N., et al. (2013a). Prediction of auditory and visual P300 brain-computer interface aptitude. PLoS ONE 8:e53513. doi: 10.1371/journal.pone.0053513
25. Halder, S., Varkuti, B., Bogdan, M., Kübler, A., Rosenstiel, W., Sitaram, R., et al. (2013b). Prediction of brain-computer interface aptitude from individual brain structure. Front. Hum. Neurosci. 7, 1-9. doi: 10.3389/fnhum.2013.00105
26. Hammer, E. M., Halder, S., Blankertz, B., Sannelli, C., Dickhaus, T., Kleih, S., et al. (2012). Psychological predictors of SMR-BCI performance. Biol. Psychol. 89, 80-86. doi: 10.1016/j.biopsycho.2011.09.006
27. Hoedlmoser, K., Pecherstorfer, T., Gruber, G., Anderer, P., Doppelmayr, M., Klimesch, W., et al. (2008). Instrumental conditioning of human sensorimotor rhythm (12-15 Hz) and its impact on sleep as well as declarative learning. Sleep 31, 1401-1408.
28. Keizer, A. W., Verment, R. S., and Hommel, B. (2010a). Enhancing cognitive control through neurofeedback: A role of gamma-band activity in managing episodic retrieval. Neuroimage 49, 3404-3413. doi: 10.1016/j.neuroimage.2009.11.023
29. Keizer, A. W., Verschoor, M., Verment, R. S., and Hommel, B. (2010b). The effect of gamma enhancing neurofeedback on the control of feature bindings and intelligence measures. Int. J. Psychophysiol. 75, 25-32. doi: 10.1016/j.ijpsycho.2009.10.011
30. Kleih, S., Nijboer, F., Halder, S., and Kübler, A. (2010). Motivation modulates the P300 amplitude during brain-computer interface use. Clin. Neurophysiol. 121, 1023-1031. doi: 10.1016/j.clinph.2010.01.034
31. Kotchoubey, B., Strehl, U., Holzapfel, S., Blankenhorn, V., Fröscher, W., and Birbaumer, N. (1999). Negative potential shifts and the prediction of the outcome of neurofeedback therapy in epilepsy. Clin. Neurophysiol. 110, 683-686. doi: 10.1016/S1388-2457(99)00005-X
32. Kropotov, J. D. (2009). Quantitative EEG, Event-related Potentials and Neurotherapy. 1st Edn. Amsterdam; Boston, MA; London: Elsevier/Academic.
33. Kropotov, J. D., Grin-Yatsenko, V. A., Ponomarev, V. A., Chutko, L. S., Yakovenko, E. A., and Nikishena, I. S. (2005). ERPs correlates of EEG relative beta training in ADHD children. Int. J. Psychophysiol. 55, 23-34. doi: 10.1016/j.ijpsycho.2004.05.011
34. Kübler, A., and Kotchoubey, B. (2007). Brain-computer interfaces in the continuum of consciousness. Curr. Opin. Neurol. 20, 643-649. doi: 10.1097/WCO.0b013e3282f14782
35. Kübler, A., Kotchoubey, B., Hinterberger, T., Ghanayim, N., Perelmouter, J., Schauer, M., et al. (1999). The thought translation device: a neurophysiological approach to communication in total motor paralysis. Exp. Brain Res. 124, 223-232. doi: 10.1007/s002210050617
36. Kübler, A., Neumann, N., Wilhelm, B., Hinterberger, T., and Birbaumer, N. (2004). Predictability of brain-computer communication. J. Psychophysiol. 18, 121-129. doi: 10.1027/0269-8803.18.23.121
37. Kübler, A., Nijboer, F., Mellinger, J., Vaughan, T. M., Pawelzik, H., Schalk, G., et al. (2005). Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface. Neurology 64, 1775-1777. doi: 10.1212/01.WNL.0000158616.43002.6D
38. LaConte, S. M. (2011). Decoding fMRI brain states in real-time: multivariate decoding and brain reading. Neuroimage 56, 440-454. doi: 10.1016/j.neuroimage.2010.06.052
39. Lacroix, J. M. (1986). "Mechanisms of biofeedback control, " in Consciousness and Self-regulation, Vol. 4, eds D. Shapiro and G. E. Schwartz (New York, NY: Plenum), 137-162.
40. Lacroix, J. M., and Gowen, A. H. (1981). The acquisition of autonomic control through biofeedback: some tests of discrimination theory. Psychophysiology 18, 559-572. doi: 10.1111/j.1469-8986.1981.tb01826.x
41. Lang, P. J., and Twentyman, C. T. (1976). Learning to control heart rate: effects of varying incentive and criterion of success on task performance. Psychophysiology 13, 378-385. doi: 10.1111/j.1469-8986.1976.tb00848.x
42. Leins, U., Goth, G., Hinterberger, T., Klinger, C., Rumpf, N., and Strehl, U. (2007). Neurofeedback for children with ADHD: a comparison of SCP and theta/beta protocols. Appl. Psychophysiol. Biofeedback 32, 73-88. doi: 10.1007/s10484-007-9031-0
43. Lutz, A., Greischar, L., Rawlings, N., and Ricard, M. D. R. (2004). Long-term meditators self-induce high-amplitude gamma synchrony during mental practice. Proc. Natl. Acad. Sci. U.S.A. 101, 16369-16373. doi: 10.1073/pnas.0407401101
44. Nan, W., Rodrigues, J. P., Ma, J., Qu, X., Wan, F., Mak, P.-I., et al. (2012). Individual alpha neurofeedback training effect on short term memory. Int. J. Psychophysiol. 86, 83-87. doi: 10.1016/j.ijpsycho.2012.07.182
45. Neumann, N., and Birbaumer, N. (2003). Predictors of successful self control during brain-computer communication. J. Neurol. Neurosurg. Psychiatr. 74, 1117-1121. doi: 10.1136/jnnp.74.8.1117
46. Neuper, C., Scherer, R., Reiner, M., and Pfurtscheller, G. (2005). Imagery of motor actions: Differential effects of kinesthetic and visual-motor mode of imagery in single-trial EEG. Cogn. Brain Res. 25, 668-677. doi: 10.1016/j.cogbrainres.2005.08.014
47. Nijboer, F., Furdea, A., Gunst, I., Mellinger, J., McFarland, D. J., Birbaumer, N., et al. (2008). An auditory brain-computer interface (BCI). J. Neurosci. Methods 167, 43-50. doi: 10.1016/j.jneumeth.2007.02.009
48. Pfurtscheller, G., and Lopes da Silva, F. H. (1999). Event-related EEG/MEG synchronization and desynchronization: basic principles. Clin. Neurophysiol. 110, 1842-1857. doi: 10.1016/S1388-2457(99)00141-8
49. Pfurtscheller, G., and Neuper, C. (1997). Motor imagery activates primary sensorimotor area in humans. Neurosci. Lett. 239, 65-68. doi: 10.1016/S0304-3940(97)00889-6
50. Raymond, J., Varney, C., Parkinson, L. A., and Gruzelier, J. H. (2005). The effects of alpha/theta neurofeedback on personality and mood. Cogn. Brain Res. 23, 287-292. doi: 10.1016/j.cogbrainres.2004.10.023
51. Rubik, B. (2011). Neurofeedback-enhanced gamma brainwaves from the prefrontal cortical region of meditators and non-meditators and associated subjective experiences. J. Altern. Complement. Med. 17, 109-115. doi: 10.1089/acm.2009.0191
52. Schabus, M., Gruber, G., Parapatics, S., Sauter, C., Klosch, G., Anderer, P., et al. (2004). Sleep spindles and their significance for declarative memory consolidation. Sleep 27, 1479-1485.
53. Serruya, M., and Kahana, M. J. (2008). Techniques and devices to restore cognition. Behav. Brain Res. 192, 149-165. doi: 10.1016/j.bbr.2008.04.007
54. Skinner, B. (1945). The operational analysis of psychological terms. Psychol. Rev. 52, 270-277. doi: 10.1037/h0062535
55. Sterman, M. B. (1996). Physiological origins and functional correlates of EEG rhythmic activities: implications for self-regulation. Biofeedback Self. Regul. 21, 3-33. doi: 10.1007/BF02214147
56. Sterman, M. B. (2000). Basic concepts and clinical findings in the treatment of seizure disorders with EEG operant conditioning. Clin. EEG Electroencephalogr. 31, 45-55.
57. Strehl, U. (ed.). (2013). Neurofeedback: Theoretische Grundlagen-Praktisches Vorgehen-Wissenschaftliche Evidenz. Stuttgart: Kohlhammer.
58. Tansey, M. A. (1984). EEG sensorimotor rhythm biofeedback training: some effects on the neurologic precursors of learning disabilities. Int. J. Psychophysiol. 1, 163-177. doi: 10.1016/0167-8760(84)90036-9
59. Tansey, M. A., and Bruner, R. L. (1983). EMG and EEG biofeedback training in the treatment of a 10-year-old hyperactive boy with a developmental reading disorder. Biofeedback Self. Regul. 8, 25-37. doi: 10.1007/BF01000534
60. Tinius, T., and Tinius, K. (2000). Changes after EEG biofeedback and cognitive retraining in adults with mild traumatic brain Injury and attention deficit hyperactivity disorder. J. Neurother. 4, 27-43. doi: 10.1300/J184v04n02_05
61. 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. Int. J. Psychophysiol. 47, 75-85. doi: 10.1016/S0167-8760(02)00091-0
62. Weber, E., Köberl, A., Frank, S., and Doppelmayr, M. (2011). Predicting successful learning of SMR neurofeedback in healthy participants: methodological considerations. Appl. Psychophysiol. Biofeedback 36, 37-45. doi: 10.1007/s10484-010-9142-x
63. Witte, M., Kober, S., Ninaus, M., Neuper, C., and Wood, G. (2013). Control beliefs can predict the ability to up-regulate sensorimotor rhythm during neurofeedback training. Front. Hum. Neurosci. 7, 1-8. doi: 10.3389/fnhum.2013.00478
64. Wolpaw, J. R., Birbaumer, N., McFarland, D. J., Pfurtscheller, G., and Vaughan, T. M. (2002). Brain-computer interfaces for communication and control. Clinical Neurophysiol. 113, 767-791. doi: 10.1016/S1388-2457(02)00057-3