Non-linear EEG analyses predict non-response to rTMS treatment in major depressive disorder

Clinical Neurophysiology

Volumn 125, Issue 7, 2014, Pages 1392-1399

  Arns, Martijn ^a,b   Cerquera, Alexander ^c   Gutiérrez, Rafael M ^c   Hasselman, Fred ^d   Freund, Jan A ^e  

^a RESEARCH INSTITUTE BRAINCLINICS   (Netherlands)

^b UTRECHT UNIVERSITY   (Netherlands)

^c CENTRO DE INVESTIGACIONES   (Colombia)

^d RADBOUD UNIVERSITY NIJMEGEN   (Netherlands)

^e UNIVERSITY OF OLDENBURG   (Germany)

Author keywords

Depression; EEG; Lempel Ziv complexity; Non linear analysis; Personalized medicine; RTMS; Signal processing

Indexed keywords

ADULT; AGED; ALPHA RHYTHM; ARTICLE; CONTROLLED STUDY; ELECTROENCEPHALOGRAPHY; FALSE NEAREST NEIGHBOR; FEMALE; HUMAN; LARGEST LYAPUNOV EXPONENT; LEMPEL ZIV COMPLEXITY; MAJOR CLINICAL STUDY; MAJOR DEPRESSION; MALE; MATHEMATICAL MODEL; NERVE STIMULATOR; NON LINEAR ELECTROENCEPHALOGRAPHY; NONLINEAR SYSTEM; PRIORITY JOURNAL; PSYCHOTHERAPY; REPETITIVE TRANSCRANIAL MAGNETIC STIMULATION; TRANSCRANIAL MAGNETIC STIMULATION; TREATMENT OUTCOME; ADOLESCENT; ANALYSIS OF VARIANCE; CLINICAL TRIAL; CONTROLLED CLINICAL TRIAL; DEPRESSIVE DISORDER, MAJOR; DISCRIMINANT ANALYSIS; MIDDLE AGED; MULTICENTER STUDY; PROGNOSIS; RECEIVER OPERATING CHARACTERISTIC; SIGNAL PROCESSING; YOUNG ADULT;

ADOLESCENT; ADULT; AGED; ANALYSIS OF VARIANCE; DEPRESSIVE DISORDER, MAJOR; DISCRIMINANT ANALYSIS; ELECTROENCEPHALOGRAPHY; FEMALE; HUMANS; MALE; MIDDLE AGED; NONLINEAR DYNAMICS; PROGNOSIS; PSYCHOTHERAPY; ROC CURVE; SIGNAL PROCESSING, COMPUTER-ASSISTED; TRANSCRANIAL MAGNETIC STIMULATION; TREATMENT OUTCOME; YOUNG ADULT;

EID: 84901247199     PISSN: 13882457     EISSN: 18728952     Source Type: Journal    
DOI: 10.1016/j.clinph.2013.11.022     Document Type: Article

References (59)

1. Aboy M., Hornero R., Abásolo D., Alvarez D. Interpretation of the Lempel-Ziv complexity measure in the context of biomedical signal analysis. IEEE Transactions Bio-med Engin 2006, 53:2282-2288.
2. Arns M. EEG-based personalized medicine in ADHD: individual alpha peak frequency as an endophenotype associated with nonresponse. J Neurother 2012, 16:123-141.
3. Arns M., Conners C.K., Kraemer H.C. A decade of EEG theta/beta ratio research in ADHD: a meta-analysis. J Atten Disord 2013, 17:374-383.
4. Arns M., Drinkenburg P., Fitzgerald P., Kenemans L. Neurophysiological predictors of non-response to rtms in depression. Brain Stimul 2012, 5:569-576.
5. Arns M., Kenemans J.L. Neurofeedback in ADHD and insomnia: vigilance stabilization through sleep spindles and circadian networks. Neurosci Biobehav Rev 2012, 10.1016/j.neubiorev.2012.10.006.
6. Arns M., Spronk D., Fitzgerald P.B. Potential differential effects of 9Hz rTMS and 10Hz rTMS in the treatment of depression. Brain Stimul 2010, 3:124-126.
7. Arns M., Olbrich S. Two EEG channels do not make a quantitative EEG (QEEG): a response to Widge, Avery and Zarkowski. Brain Stim 2013, 10.1016/j.brs.2013.09.009.
8. Babloyantz A. Evidence for slow brain waves: a dynamical approach. Electroencephalogr Clin Neurophysiol 1991, 78:402-405.
9. Bagby R.M., Ryder A.G., Cristi C. Psychosocial and clinical predictors of response to pharmacotherapy for depression. J Psychiatry Neurosci 2002, 27:250-257.
10. Berlim M.T., Van den Eynde F., Jeff Daskalakis Z. Clinically meaningful efficacy and acceptability of low-frequency repetitive transcranial magnetic stimulation (rtms) for treating primary major depression: a meta-analysis of randomized, double-blind and sham-controlled trials. Neuropsychopharmacology 2013, 38:543-551.
11. Berthouze L., James L.M., Farmer S.F. Human EEG shows long-range temporal correlations of oscillation amplitude in Theta, Alpha and Beta bands across a wide age range. Clin Neurophysiol 2010, 121:1187-1197.
12. Boord P., Siddall P.J., Tran Y., Herbert D., Middleton J., Craig A. Electroencephalographic slowing and reduced reactivity in neuropathic pain following spinal cord injury. Spinal cord 2008, 46:118-123.
13. Bravi A., Longtin A., Seely A.J.E. Review and classification of variability analysis techniques with clinical applications. Biomed Eng Online 2011, 10:90.
14. Bruder G.E., Sedoruk J.P., Stewart J.W., McGrath P.J., Quitkin F.M., Tenke C.E. Electroencephalographic alpha measures predict therapeutic response to a selective serotonin reuptake inhibitor antidepressant: pre- and post-treatment findings. Biol Psychiatry 2008, 6(63):1171-1177.
15. Bruder G.E., Stewart J.W., Tenke C.E., McGrath P.J., Leite P., Bhattacharya N., Quitkin F.M. Electroencephalographic and perceptual asymmetry differences between responders and nonresponders to an SSRI antidepressant. Biol Psychiatry 2001, 3(49):416-425.
16. Conca A., Swoboda E., König P., Koppi S., Beraus W., Künz A., et al. Clinical impacts of single transcranial magnetic stimulation (stms) as an add-on therapy in severely depressed patients under SSRI treatment. Hum Psychopharmacol 2000, 15:429-438.
17. Freeman W.J., Ahlfors S.P., Menon V. Combining fMRI with EEG and MEG in order to relate patterns of brain activity to cognition. Int J Psychophysiol 2009, 73:43-52.
18. Gangadhar B.N., Subbakrishna D.K., Janakiramaiah N., Motreja S., Narayana Dutt D., Paramehwara G. Post-seizure EEG fractal dimension of first ECT predicts antidepressant response at two weeks. J Affect Disord 1999, 52:235-238.
19. Gatt J.M., Kuan S.A., Dobson-Stone C., Paul R.H., Joffe R.T., Kemp A.H., et al. Association between BDNF val66met polymorphism and trait depression is mediated via resting EEG alpha band activity. Biol Psychol 2008, 79:275-284.
20. Gilden D.L., Hancock H. Response variability in attention-deficit disorders. Psychol Sci 2007, 18:796-802.
21. Goldberger A.L., Peng C.-K., Lipsitz L.A. What is physiologic complexity and how does it change with aging and disease?. Neurobiol Aging 2002, 23:23-26.
22. Granic I., Hollenstein T. Dynamic systems methods for models of developmental psychopathology. Dev Psychopathol 2003, 15:641-669.
23. Gratton G., Coles M.G., Donchin E. A new method for off-line removal of ocular artifact. Electroencephalography and Clinical Neurophysiology 1983, 55(4):468-484.
24. Harbourne R.T., Stergiou N. Movement variability and the use of nonlinear tools: principles to guide physical therapist practice. Physical Ther 2009, 89:267-282.
25. Hayes A.M., Laurenceau J.-P., Feldman G., Strauss J.L., Cardaciotto L. Change is not always linear: the study of nonlinear and discontinuous patterns of change in psychotherapy. Clin Psychol Rev 2007, 27:715-723.
26. Hegerl U., Hensch T. The vigilance regulation model of affective disorders and ADHD. Neurosci Biobehav Rev 2012, 20.
27. Hegerl U., Wilk K., Olbrich S., Schoenknecht P., Sander C. Hyperstable regulation of vigilance in patients with major depressive disorder. World J Biol Psychiatry 2012, 13:436-446.
28. Huikuri H.V., Stein P.K. Clinical application of heart rate variability after acute myocardial infarction. Front Physiol 2012, 3:41.
29. Kantz H., Schreiber T. Nonlinear Time Series Analysis 2004, Cambridge University Press. second ed.
30. Kleinnijenhuis M., Arns M.W., Spronk D.B., Breteler M.H.M., Duysens J.E.J. Comparison of discrete-trial based SMR and SCP training and the interrelationship between SCP and SMR networks: implications for brain-computer interfaces and neurofeedback. J Neurother 2008, 11:19-35.
31. Krystal A.D., Zaidman C., Greenside H.S., Weiner R.D., Coffey C.E. The largest lyapunov exponent of the EEG during ECT seizures as a measure of ECT seizure adequacy. Electroencephalogr Clin Neurophysiol 1997, 103:599-606.
32. Lemere F. The significance of individual differences in the berger rhythm. Brain 1936, 366-375.
33. Lichtwarck-Aschoff A., Hasselman F., Cox R., Pepler D., Granic I. A characteristic destabilization profile in parent-child interactions associated with treatment efficacy for aggressive children. Nonlinear Dynamics-Psychol Life Sci 2012, 16:353.
34. Linkenkaer-Hansen K., Monto S., Rytsälä H., Suominen K., Isometsä E., Kähkönen S. Breakdown of long-range temporal correlations in theta oscillations in patients with major depressive disorder. J Neurosci 2005, 25:10131-10137.
35. Linkenkaer-Hansen K., Nikouline V.V., Palva J.M., Ilmoniemi R.J. Long-range temporal correlations and scaling behavior in human brain oscillations. J Neurosci 2001, 21:1370-1377.
36. Little, M.A., McSharry, P.E., Moroz, I.M., Roberts, S.J., 2006. Nonlinear, biophysically-informed speech pathology detection. In Proceedings of IEEE ICASSP. IEEE Publishers: Toulouse, France.
37. Niedermeyer E., Lopes da Silva F. Electroencephalography: Basic principles, clinical applications, and related fields 1999, Williams & Wilkins, Baltimore. Fourth ed.
38. Orlandi J.G., Soriano J., Alvarez-Lacalle E., Teller S., Casademunt J. Noise focusing and the emergence of coherent activity in neuronal cultures. Nat Phys 2013, 9:582-590.
39. Palva J.M., Zhigalov A., Hirvonen J., Korhonen O., Linkenkaer-Hansen K., Palva S. Neuronal long-range temporal correlations and avalanche dynamics are correlated with behavioral scaling laws. Proc Natl Acad Sci USA 2013, 10:3585-3590.
40. Olbrich S., Arns M. EEG biomarkers in major depressive disorder: discriminative power and prediction of treatment response. Int Rev Psychiatry 2013, 25:604-618.
41. Riedel M., Möller H.J., Obermeier M., Schennach-Wolff R., Bauer M., Adli M., et al. Response and remission criteria in major depression-a validation of current practice. J Psychiatr Res 2010, 44:1063-1068.
42. Rodriguez G., Copello F., Vitali P., Perego G., Nobili F. EEG spectral profile to stage alzheimer's disease. Clin Neurophysiol 1999, 110:1831-1837.
43. Rubinov M., Sporns O. Complex network measures of brain connectivity: uses and interpretations. Neuroimage 2010, 52:1059-1069.
44. Schutter D.J.L.G. Antidepressant efficacy of high-frequency transcranial magnetic stimulation over the left dorsolateral prefrontal cortex in double-blind sham-controlled designs: a meta-analysis. Psychol Med 2009, 39:65-75.
45. Schutter D.J.L.G. Quantitative review of the efficacy of slow-frequency magnetic brain stimulation in major depressive disorder. Psychol Med 2010, 1:1-7.
46. Simon G.E., Perlis R.H. Personalized medicine for depression: can we match patients with treatments?. Am J Psychiatry 2010, 167:1445-1455.
47. Small M. Applied Nonlinear Time Series Analysis: Applications in Physics, Physiology and Finance 2005, World Scientific Publishing Company.
48. Spronk D., Kleinnijenhuis M., Luijtelaar G.V., Arns M. Discrete-trial SCP and GSR training and the interrelationship between central and peripheral arousal. J Neurother 2010, 14:217-228.
49. Stam C.J. Nonlinear dynamical analysis of EEG and MEG: review of an emerging field. Clin Neurophysiol 2005, 116:2266-2301.
50. Stam C.J. Characterization of anatomical and functional connectivity in the brain: a complex networks perspective. Int J Psychophysiol 2010, 77:186-194.
51. Tagliazucchi E., Balenzuela P., Fraiman D., Chialvo D.R. Criticality in large-scale brain FMRI dynamics unveiled by a novel point process analysis. Front Physiol 2012, 3:15.
52. Tenke C.E., Kayser J., Manna C.G., Fekri S., Kroppmann C.J., Schaller J.D., et al. Current source density measures of electroencephalographic alpha predict antidepressant treatment response. Biol Psychiatry 2011, 8(70):388-394.
53. Tirsch W.S., Keidel M., Perz S., Scherb H., Sommer G. Inverse covariation of spectral density and correlation dimension in cyclic EEG dynamics of the human brain. Biol Cybern 2000, 82:1-14.
54. Tirsch W.S., Stude P., Scherb H., Keidel M. Temporal order of nonlinear dynamics in human brain. Brain Res Brain Res Rev 2004, 45:79-95.
55. Ulrich G., Renfordt E., Frick K. The topographical distribution of alpha-activity in the resting EEG of endogenous-depressive in-patients with and without clinical response to pharmacotherapy. Pharmacopsychiatry 1986, 19:272-273.
56. Van Orden, G.C., Kloos, H., Wallot, S. Living in the pink: Intentionality, wellbeing, and complexity. In Handbook of the Philosophy of Science 2009. Philosophy of Complex Systems, Vol. 10. Amsterdam: Elsevier B.V. Retrieved from . http://www.uc.edu/ccrl/documents/2009_Van_Orden_Kloos_Wallot.pdf.
57. Wijnants M.L., Hasselman F., Cox R.F.A., Bosman A.M.T., Van Orden G. An interaction-dominant perspective on reading fluency and dyslexia. Ann Dyslexia 2012, 62:100-119.
58. Yu S., Yang H., Shriki O., Plenz D. Universal organization of resting brain activity at the thermodynamic critical point. Front Syst Neurosci 2013, 7:42.
59. Zoon H.F., Veth C.P., Arns M., Drinkenburg W.H., Talloen W., Peeters P.J., Kenemans J.L. EEG alpha power as an intermediate measure between brain-derived neurotrophic factor val66met and depression severity in patients with major depressive disorder. J Clin Neurophysiol 2013, 30:261-267.