Resting-state sensorimotor rhythm (SMR) power predicts the ability to up-regulate SMR in an EEG-instrumental conditioning paradigm

Clinical Neurophysiology

Volumn 126, Issue 11, 2015, Pages 2068-2077

  Reichert, Johanna Louise ^a   Kober, Silvia Erika ^a,c   Neuper, Christa ^a,b,c   Wood, Guilherme ^a,c  

^a UNIVERSITY OF GRAZ   (Austria)

^b GRAZ UNIVERSITY OF TECHNOLOGY   (Austria)

^c BIOTECHMED GRAZ   (Austria)

Author keywords

EEG instrumental conditioning; Neurofeedback; Regulation of brain activity; Responders; Resting state EEG activity; Sensorimotor rhythm

Indexed keywords

ADULT; ARTICLE; BRAIN REGION; CONTROLLED STUDY; DISCRIMINANT ANALYSIS; ELECTROENCEPHALOGRAM; EYELID REFLEX; FEEDBACK SYSTEM; FEMALE; GAMMA RHYTHM; HUMAN; INSTRUMENTAL CONDITIONING; LEARNING; NORMAL HUMAN; PREDICTOR VARIABLE; PRIORITY JOURNAL; RESTING STATE NETWORK; RESTING STATE SENSORIMOTOR RHYTHM; UPREGULATION; AGING; BRAIN MAPPING; COGNITION; COMPARATIVE STUDY; ELECTROENCEPHALOGRAPHY; MALE; MIDDLE AGED; NEUROFEEDBACK; PHYSIOLOGY; PREDICTIVE VALUE; PROCEDURES; REST; SENSORIMOTOR CORTEX;

ADULT; AGING; BRAIN MAPPING; COGNITION; ELECTROENCEPHALOGRAPHY; FEMALE; HUMANS; LEARNING; MALE; MIDDLE AGED; NEUROFEEDBACK; PREDICTIVE VALUE OF TESTS; REST; SENSORIMOTOR CORTEX; UP-REGULATION;

EID: 84952637956     PISSN: 13882457     EISSN: 18728952     Source Type: Journal    
DOI: 10.1016/j.clinph.2014.09.032     Document Type: Article

References (56)

1. Allison B.Z., Neuper C. Could anyone use a BCI?. Brain-computer interfaces 2010, 35-54. Springer, London. D. Tan, A. Nijholt (Eds.).
2. Angelakis E., Stathopoulou S., Frymiare J.L., Green D.L., Lubar J.F., Kounios J. EEG neurofeedback: a brief overview and an example of peak alpha frequency training for cognitive enhancement in the elderly. Clin Neuropsychol 2007, 1:110-129.
3. Arns M., de Ridder S., Strehl U., Breteler M., Coenen A. Efficacy of neurofeedback treatment in ADHD: the effects on inattention, impulsivity and hyperactivity: a meta-analysis. Clin EEG Neurosci 2009, 3:180-189.
4. Bearden T.S., Cassisi J.E., Pineda M. Neurofeedback training for a patient with thalamic and cortical infarctions. Appl Psychophysiol Biofeedback 2003, 3:241-253.
5. Blankertz B., Sannelli C., Halder S., Hammer E.M., Kübler A., Müller K., et al. Neurophysiological predictor of SMR-based BCI performance. NeuroImage 2010, 4:1303-1309.
6. Burde W., Blankertz B. Is the locus of control of reinforcement a predictor of brain-computer interface performance?. Proceedings of the 3rd international brain-computer interface workshop and training course 2006, 76-77. Verlag der TU Graz, Graz. G.R. Müller-Putz (Ed.).
7. Doppelmayr M., Weber E. Effects of SMR and theta/beta neurofeedback on reaction times, spatial abilities, and creativity. J Neurother 2011, 2:115-129.
8. Doppelmayr M., Nosko H., Pecherstorfer T., Fink A. An attempt to increase cognitive performance after stroke with neurofeedback. Biofeedback 2007, 4:126-130.
9. Egner T., Gruzelier J.H. EEG biofeedback of low beta band components: frequency-specific effects on variables of attention and event-related brain potentials. Clin Neurophysiol 2004, 1:131-139.
10. Enriquez-Geppert S., Huster R.J., Scharfenort R., Mokom Z.N., Zimmermann J., Herrmann C.S. Modulation of frontal-midline theta by neurofeedback. Biol Psychol 2013, 59-69.
11. Escolano C., Olivan B., Lopez-del-Hoyo Y., Garcia-Campayo J., Minguez J. Double-blind single-session neurofeedback training in upper-alpha for cognitive enhancement of healthy subjects. Conf Proc IEEE Eng Med Biol Soc 2012, 4643-4647.
12. Finnigan S., Robertson I.H. Resting EEG theta power correlates with cognitive performance in healthy older adults. Psychophysiology 2011, 8:1083-1087.
13. Fox D.J., Tharp D.F., Fox L.C. Neurofeedback: an alternative and efficacious treatment for attention deficit hyperactivity disorder. Appl Psychophysiol Biofeedback 2005, 4:365-373.
14. Garaas, T., Pepe, R., Lo, H., Nestor, P., Pomplun, M. (Eds.). Neural adaptability and inspection time. ICCI '09. 8th IEEE International Conference on Cognitive Informatics 2009.
15. Ghoshuni M., Firoozabadi M., Khalilzadeh M.A., Hashemi Golpayegani M.R. The effect of sensorimotor rhythm enhancing neurofeedback on power of adjacent frequency bands. Biomed Eng 2012, 04:307-312.
16. Gratton G., Coles M.G.H., Donchin E. A new method for off-line removal of ocular artifact. Electroencephalogr Clin Neurophysiol 1983, 4:468-484.
17. Gruzelier J.H. EEG-neurofeedback for optimising performance. III: A review of methodological and theoretical considerations. Neurosci Biobehav Rev 2014, 44:159-182.
18. Gruzelier J., Inoue A., Smart R., Steed A., Steffert T. Acting performance and flow state enhanced with sensory-motor rhythm neurofeedback comparing ecologically valid immersive VR and training screen scenarios. Neurosci Lett 2010, 2:112-116.
19. Halder S., Agorastos D., Veit R., Hammer E.M., Lee S., Varkuti B., et al. Neural mechanisms of brain-computer interface control. NeuroImage 2011, 4:1779-1790.
20. Halder S., Hammer E.M., Kleih S.C., Bogdan M., Rosenstiel W., Birbaumer N., et al. Prediction of auditory and visual p300 brain-computer interface aptitude. PloS one 2013, 2:1-11.
21. Halder S., Varkuti B., Bogdan M., Kübler A., Rosenstiel W., Sitaram R., et al. Prediction of brain-computer interface aptitude from individual brain structure. Front Hum Neurosci 2013, 7:105.
22. Hammer E.M., Halder S., Blankertz B., Sannelli C., Dickhaus T., Kleih S., et al. Psychological predictors of SMR-BCI performance. Biol Psychol 2012, 1:80-86.
23. Hoedlmoser K., Pecherstorfer T., Gruber G., Anderer P., Doppelmayr M., Klimesch W., et al. Instrumental conditioning of human sensorimotor rhythm (12-15Hz) and its impact on sleep as well as declarative learning. Sleep 2008, 10:1401-1408.
24. Hofer D., Kober S.E., Reichert J.L., Krenn M., Farveleder K., Grieshofer P., et al. Spezifische Effekte von EEG basiertem Neurofeedbacktraining auf kognitive Leistungen nach einem Schlaganfall: Ein nutzvolles Werkzeug für die Rehabilitation?. Lernen und Lernstörungen 2014, 7. In Press; doi http://dx.doi.org/10.1024/2235-0977/a000078.
25. Kleih S.C., Nijboer F., Halder S., Kübler A. Motivation modulates the P300 amplitude during brain-computer interface use. Clin Neurophysiol 2010, 7:1023-1031.
26. Kleih SC, Riccio A, Mattia D, Kaiser V, Friedrich, E. V. C., Kübler A et al. Motivation influences performance in SMR-BCI. Proceedings of the fifth international brain-computer interface conference 2011.
27. Klimesch W. EEG alpha and theta oscillations reflect cognitive and memory performance. a review and analysis. Brain Res Brain Res Rev 1999, 2:169-195.
28. Kober S.E., Witte M., Ninaus M., Neuper C., Wood G. Learning to modulate one's own brain activity: the effect of spontaneous mental strategies. Front Hum Neurosci 2013, 7:695.
29. Kober S.E., Witte M., Stangl M., Valjamae A., Neuper C., Wood G. Shutting down sensorimotor interference unblocks the networks for stimulus processing: An SMR neurofeedback training study. Clin Neurophysiol 2015, 126:82-95.
30. Könönen M., Partanen J.V. Blocking of EEG alpha activity during visual performance in healthy adults. A quantitative study. Electroencephalogr Clin Neurophysiol 1993, 3:164-166.
31. Kropotov J.D., Quantitative E.E.G. Event-related potentials and neurotherapy 2009, Elsevier, Amsterdam. 1st ed.
32. Lubar J.F., Swartwood M.O., Swartwood J.N., O'Donnell P.H. Evaluation of the effectiveness of EEG neurofeedback training for ADHD in a clinical setting as measured by changes in TOVA scores, behavioral ratings, and WISC-R performance. Biofeedback Self Regul 1995, 1:83-99.
33. Luck S.J. An introduction to the event-related potential technique 2005, MIT Press, Cambridge, Mass.
34. Mak J.N., McFarland D.J., Vaughan T.M., McCane L.M., Tsui P.Z., Zeitlin D.J., et al. EEG correlates of P300-based brain-computer interface (BCI) performance in people with amyotrophic lateral sclerosis. J Neural Eng 2012, 2:1-11.
35. Nan W., Rodrigues J.P., Ma J., Qu X., Wan F., Mak P., et al. Individual alpha neurofeedback training effect on short term memory. Int J Psychophysiol 2012, 1:83-87.
36. Niedermeyer E. The normal EEG of the waking adult. Electroencephalography: basic principles, clinical applications, and related fields 2005, 167167. Lippincott Williams & Wilkins. E. Niedermeyer, F.H.L. Da Silva (Eds.).
37. Nijboer F., Furdea A., Gunst I., Mellinger J., McFarland D.J., Birbaumer N., et al. An auditory brain-computer interface (BCI). J Neurosci Methods 2008, 1:43-50.
38. Nunez P.L., Srinivasan R. Electric fields of the brain: the neurophysics of EEG 2006, Oxford University Press.
39. Pfurtscheller G., Neuper C. Motor imagery activates primary sensorimotor area in humans. Neurosci Lett 1997, 2:65-68.
40. Polich J. EEG and ERP assessment of normal aging. Electroencephalogr Clin Neurophysiol 1997, 3:244-256.
41. Prat C.S. The brain basis of individual differences in language comprehension abilities. Lang Linguist Compass 2011, 9:635-649.
42. Richards M., Deary I.J. A life course approach to cognitive reserve: a model for cognitive aging and development?. Ann Neurol 2005, 4:617-622.
43. Rossini P.M., Rossi S., Babiloni C., Polich J. Clinical neurophysiology of aging brain: from normal aging to neurodegeneration. Prog Neurobiol 2007, 6:375-400.
44. Satz P. Brain reserve capacity on symptom onset after brain injury: a formulation and review of evidence for threshold theory. Neuropsychology 1993, 3:273.
45. Schabus M., Heib D.P.J., Lechinger J., Griessenberger H., Klimesch W., Pawlizki A., et al. Enhancing sleep quality and memory in insomnia using instrumental sensorimotor rhythm conditioning. Biol Psychol 2014, 95:126-134.
46. Schafer E.W.P. Neural adaptability: a biological determinant of behavioral intelligence. Int J Neurosci 1982, 3:183-191.
47. Sherlin L.H., Arns M., Lubar J., Heinrich H., Kerson C., Strehl U., et al. Neurofeedback and basic learning theory: implications for research and practice. J Neurother 2011, 4:292-304.
48. Sterman M.B. Physiological origins and functional correlates of EEG rhythmic activities: implications for self-regulation. Biofeedback Self Regul 1996, 1:3-33.
49. Sterman M.B., Egner T. Foundation and practice of neurofeedback for the treatment of epilepsy. Appl Psychophysiol Biofeedback 2006, 1:21-35.
50. Tinius T.P., Tinius K.A. Changes after EEG biofeedback and cognitive retraining in adults with mild traumatic brain injury and attention deficit hyperactivity disorder. J Neurother 2000, 2:27-44.
51. Vernon D., Egner T., Cooper N., Compton T., Neilands C., Sheri A., et al. The effect of training distinct neurofeedback protocols on aspects of cognitive performance. Int J Psychophysiol 2003, 1:75-85.
52. Wan F., Nan W., Vai M.I., Rosa A. Resting alpha activity predicts learning ability in alpha neurofeedback. Front Hum Neurosci 2014, 10.3389/fnhum.2014.00500.
53. Wang J., Barstein J., Ethridge L.E., Mosconi M.W., Takarae Y., Sweeney J.A., et al. Resting state EEG abnormalities in autism spectrum disorders. J Neurodev Disord 2013, 5(1):1-14.
54. Weber E., Köberl A., Frank S., Doppelmayr M. Predicting successful learning of SMR neurofeedback in healthy participants: methodological considerations. Appl Psychophysiol Biofeedback 2011, 1:37-45.
55. Witte M., Kober S.E., Ninaus M., Neuper C., Wood G. Control beliefs can predict the ability to up-regulate sensorimotor rhythm during neurofeedback training. Front Hum Neurosci 2013, 7:1-8.
56. Zoefel B., Huster R.J., Herrmann C.S. Neurofeedback training of the upper alpha frequency band in EEG improves cognitive performance. NeuroImage 2011, 2:1427-1431.