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Berger, H. Uber das Elektrenkephalogramm des Menschen. Arch. Psychiat. Nervenkr. 1929 87:527- 570. Bertrand O, Bohorquez J and Pernier J. Time-frequency digital ltering based on an invertible wavelet transform: an application to evoked potentials. IEEE Trans. Biomed. Eng., 1994 41: 77-88. Besthorn C, Sattel H, Geiger-Kabisch C, Zerfass R and Forstl H. Parameters of EEG dimensional complexity in Alzheimer's disease. Electr. Clin. Neurophysiol., 1995 95: 84-89. Blanco S, Garca H, Quian Quiroga R, Romanelli L and Rosso OA. Stationarity of the EEG series. IEEE Eng. Med. Biol., 1995a, 14: 395-399. Blanco S, Quian Quiroga R, Rosso OA and Kochen S. Time-frequency analysis of electroencephalogram series. Phys. Rev. E, 1995b, 51 (3): 2624-2631. Blanco S, Kochen S, Quian Quiroga R, Riquelme L, Rosso OA and Salgado P. Characterization of epileptic EEG time series (I): Gabor transform and nonlinear dynamic methods. In: E M Fernandez Verdaguer and C AD'Attellis (Eds.), Wavelet theory and harmonic analysis in applied sciences. Birkhuser, 1996a. Blanco S, D'Atellis, Isaacson, Rosso OA, Sirne RO. Time-frequency analysis of electroencephalogram series (II): Gabor and Wavelet Transform. Phys. Rev. E, 1996b, 54 (6): 6661-6672. Blanco S, Kochen S, Rosso OA and Salgado P. Applying time-frequency analysis to seizure EEG activity. A method to help to identify the source of epileptic seizures. IEEE Eng. Med. Biol., 1997, 16: 64-71. Blanco S, Figliola A, Quian Quiroga R, Rosso OA and Serrano E. Time-frequency analysis of electroencephalogram series III: information transfer function and wavelets packets. Phys. Rev. E, 57(1):932- 940 1998a. Blanco S, Creso J, Figliola A, Quian Quiroga R and Rosso OA. Nonlinear Dynamical Analysis of Scalp EEG Epileptic Series. In: Instabilities and Non-Equilibrium Structures VI. E Tirapegui and J Martinez (eds.). Kluwer Academic Press 1998b. Brazier MAB. Spread of seizure discharges in epilepsy: anatomical and electrophysiological considerations. Exp. Neurol., 1972 36:263-272. Broomhead, D. and King, G. Physica D, 20:217 1986. Bullock THand McClune MC. Lateral coherence of the electrocorticogram: anewmeasure of brain synchrony. Electroenceph. Clin. Neurophysiol 1989 73:479-498. Bullock TH, McClune MC, Achimowicy JZ, Iragui-Madoz VJ, Duckrow RB and Spencer SS. Temporal uctuations in coherence of brain waves. Proc. Natl. Acad. Sci. USA 1995a 92:11568-11572. Bullock TH, McClune MC, Achimowicy JZ, Iragui-Madoz VJ, Duckrow RB and Spencer SS. EEG coherence has structure in the millimeter domain: subdural and hippocampal recordings from epileptic patients. Electr. Clin. Neurophysiol., 1995b 95:161-177. Chui C. An introduction to wavelets. Academic Press, San Diego, 1992. Clark I, Biscay R,Echeverria M and Virues T. Multiresolution decomposition of non-stationary EEG signals: a preliminary study. Compt. Biol. Med. 1995, 25: 373-382. Cohen L. Time-frequency analysis. Prentice-Hall, New Jersey, 1995. 119
Cooley WJ and Tukey JW. An algorithm for the machine calculation of complex Fourier series. Math. Comput., 1965, 19: 297-301. Crepeau JC and King Isaacson L. On the spectral entropy behavior of self-organizing processes. J. Non-equilib. Thermodyn., 1990 15: 115-126. Darcey T M and Williamson P D. Spatio-temporal EEG measures and their application to human intracranially recorded epileptic seizures. Electr. Clin. Neurophysiol., 1985, 61 (6): 573-587. Demiralp T and Basar E. Theta rhythmicities following expected visual and auditory targets. Int. J. Psychophysiology, 1992 13: 147-160. Demiralp T, Ademoglu A, Schurmann M, Basar-Eroglu C and Basar E. Detection of P300 waves in single trials by thewavelet transform. Brain and language, 1999 66: 108-128. Duy FH, Burchel JL and Lombroso CT. Brain electrical activity mapping (BEAM): a method for extending the clinical utility of EEG and evoked potential data. Ann. Neurol., 1979 5: 309-321. Duy FH. Tophographic mapping of brain electrical activity. London: Butterworths 1986. Dumermuth G and Molinari L. Spectral analysis of EEG background activity. In: A. Gevins and A. Remond (Eds.), Handbook of electroencephalography and clinical neurophysiology, Vol. I: Methods of analysis of brain electrical and magnetic signals. Elsevier, Amsterdam, 1987, pp: 85-130. Eckhorn R, Bauer R, Jordan W, Brosch M, Kruse W, Munk M and Reitboeck H. Coherent oscillations: A mechanism of feature linking in the visual cortex? Biol. Cybern., 60: 121-130, 1988. Eckman, J., Kamphort, S., Ruelle, D. Recurrence Plots of Dinamical Sistems. Europhys. Lett. 1987 4: 973-977. Elbert T, Ray W,Kowalik Z, Skinner J, Graf K and Birmbaumer N. Chaos and physiology: deterministic chaos in excitable cell assemblies. Phys. Rev., 1994 74: 1-47. Feynman R, Leighton R and Sands M. The Feynman lectures on physics. Addison-Wesley, Reading, MA, 1964. Feynman R. Feynman lectures on computation. A Hey and R Allen (eds.). Addison-Wesley, Reading, MA, 1996. Frank GW, Lookman T, Nerenberg MAH and Essex C. Chaotic Time Series Analysis of Epileptic Seizures. Physica D, 46: 427-438 1990. Gabor D. Theory of communication. J. Inst. Elec. Eng., 1946, 93: 429-459. Galambos R. A comparison of certain gamma band (40-Hz) brain rhythms in cat and man. In: Basar E, Bullock TH (eds.) Induced Rhythms in the Brain. Boston Basel Berlin: Birkhuser, 1992. Gallez D and Babloyantz A. Predictability ofhuman EEG: a dynamical approach. Biol. Cybern. 64: 381-391 1991. Garca H and Quian Quiroga R. La utilidad del EEG cuanticado en Neurosiologia Clinica. Archivos de Neurologia, Neurocirugia y Neuropsiquiatria, 1998 2: 34-43. Gasser T. EEG Informatics: a Didactic Review of Methods and Applications of EEG Data Processing, A. Remond (Eds), Elsevier, New York, pp 37-55, 1977. 120
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Quantitative analysis of EEG signal
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1. Berichterstatter: Prof. Dr.-Ing.
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an okzipitalen Positionen und (c) d
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To my family: Mama, Consuelo, Hugui
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Preface In this work, I will descri
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I would certainly like to remember
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Contents Zusammenfassung Preface Ac
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5.2.6 Calculating Lyapunov Exponent
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Summary Since the rsts recordings i
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1 Outline of Neurophysiology: Brain
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Figure 2: Normal 20 channels (10-20
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1.1.2 EEG in Epilepsy One important
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Figure 3: Scalp EEG of 18 channels
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Figure 4: Averaged responses upon N
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2 Fourier Transform 2.1 Introductio
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I xx (k) =jX(k)j 2 = X(k) X (k) (
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17 Figure 5: Topographical mapping
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1987) is that coherence gives the c
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3 Gabor Transform (Short Time Fouri
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where k g D k= R 1 ;1 jg D(t 0 )j 2
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and the band maximum peak frequency
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Figure 7: Intracraneal seizure reco
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Figure 10: Mean (soft line) and max
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EEG as the one with least amount of
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Figure 11: Scalp EEG of the right c
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3.5 Conclusion In this chapter I de
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Original signal FOURIER TRANSFORM G
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4.2.3 Multiresolution Analysis Cont
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Original signal -15 0 15 -1sec 0 1s
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4.2.5 Wavelet Packets In the approa
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marked decrease in computational ti
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ain activity during an epileptic se
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3 2 3 3 3 3.2 Hz 3.6 Hz 4.0 Hz 4.4
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Silva et al.,1973a,1973b Lopes da S
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sweep #1 sweep #2 sweep #3 sweep #4
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VEP non-target target F3 F4 F3 F4 F
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VEP non-target target F3 F4 F3 F4 F
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Electrode F3 F4 Cz P3 P4 O1 O2 Dela
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In conclusion, our results point to
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63 Figure 22: Gamma responses for a
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Figure 24: T-test comparison of the
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wavelet coecients allowed an easy d
Page 86 and 87: the position vs. the linear momentu
Page 88 and 89: unknown topology it is necessary to
Page 90 and 91: the sum of the positive exponents (
Page 92 and 93: performed. On one hand, must be lar
Page 94 and 95: Duke (1992) and Elbert et al. (1994
Page 96 and 97: agation time. They applied this pro
Page 98 and 99: Figure 28: Histogram for the EEG da
Page 100 and 101: Figure 29: Attractors corresponding
Page 102 and 103: able for automatic detection proces
Page 104 and 105: ENTROPY Thermodynamics Signal analy
Page 106 and 107: 6.3 Application to visual event-rel
Page 108 and 109: VEP Non Target Target F3 -20 -10 0
Page 110 and 111: 1 VEP NON-TARGET TARGET 1 1 F3 F3 0
Page 112 and 113: 1 VEP NON-TARGET TARGET 1 1 F3 F3 0
Page 114 and 115: and the Lorenz equations (a model o
Page 116 and 117: P300 deection. Due to the relation
Page 118 and 119: 7 General Discussion In this chapte
Page 120 and 121: Wavelet analysis was also applied t
Page 122 and 123: aect the whole spectrum and for thi
Page 124 and 125: peaks. 7.2.3 Wavelet Transform vs.
Page 126 and 127: the ones having wide peaks (being t
Page 128 and 129: A Time-frequency resolution and the
Page 130 and 131: Z 1 ;1 tx(t) d dt x(t) dt = 1 2 Z 1
Page 132 and 133: Figure 37: Time-frequency resolutio
Page 134 and 135: References Abarbanel HDI, Brown R,
Page 138 and 139: Gastaut H and Broughton R. Epilepti
Page 140 and 141: Lopes da Silva FH, van Lierop THMT,
Page 142 and 143: Pradhan N, Sadasivan P, Chatterji S
Page 144 and 145: Serrano E, Ph.D. Thesis, Department
Page 146: Biographical sketch 21.03.1967 born
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