Quantitative analysis of EEG signals: Time-frequency methods and ...

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Figure 3: Scalp EEG of 18 channels during a Tonic-Clonic seizure. Note how the artifacts obscure the recording completely. Vertical lines show one second divisions. 9
Modalities and paradigms There are mainly three modalities of stimulation (for more details see Regan, 1989): 1. Auditory: stimuli are single tones of a determined frequency, or clicks with a broadband frequency distribution. 2. Visual: stimuli are produced by a single light or by the reversal of a pattern as for example a checkerboard. 3. Somatosensory: stimuli are elicited by electrical stimulation of peripheral nerves. The rst two modalities can be combined in what is called bimodal stimulation. Bimodal stimulation will be studied in sec. x4.6. Sequence of stimuli are arranged in paradigms in order to study the responses to dierent tasks. The most widely used paradigms are: 1. No-task evoked potentials: subjects are relaxed and instructed to perceive the stimuli without performing any task. 2. Oddball paradigm: two dierent stimuli are presented in a pseudorandom order. A frequent NON-TARGET stimulus is presented in 75% of the trials, and a deviant stimuli called TARGET in the remaining 25% of the trials. Subjects are instructed to pay attention to the appearance of the TARGET stimuli. Transient responses: description of P100 and P300 peaks. Responses can be classied in: 1) transient (occurring after the delivery of a shortlasting stimulus, with interstimulus intervals greater than the responses), 2) driven (generated with rapidly repeating stimuli), or 3) sustained (occurring throughout the duration of a continuous stimulus). In the following we will only study transient responses. As an example, gure 4 shows the averaged transient responses to pattern visual ERPs generated with an oddball paradigm. One second pre- and one second post-stimulation EEG recorded from the left occipital electrode are plotted. A positive peak at about 100ms after stimulation (P100) can be observed upon NON-TARGET and TARGET stimulation. Since this peak does not depend on the task, it has a relatively short latency (100ms) and it is best dened in the primary sensory visual cortex (occipital locations), it is mostly related with primary sensory processing (Regan, 1989). Another peak at about 450ms after stimulation (P300) appears only upon TARGET stimulation. Since this response is task dependent and has long latency, it is traditionally related to cognitive processes as signal matching, decision making, attention, memory updating, etc. (Polich and Kok, 1995 Regan, 1989 Basar-Eroglu et al., 1992). 10
Page 1 and 2: Quantitative analysis of EEG signal
Page 3 and 4: 1. Berichterstatter: Prof. Dr.-Ing.
Page 5 and 6: an okzipitalen Positionen und (c) d
Page 8 and 9: To my family: Mama, Consuelo, Hugui
Page 10 and 11: Preface In this work, I will descri
Page 12 and 13: I would certainly like to remember
Page 14 and 15: Contents Zusammenfassung Preface Ac
Page 16 and 17: 5.2.6 Calculating Lyapunov Exponent
Page 18 and 19: Summary Since the rsts recordings i
Page 20 and 21: 1 Outline of Neurophysiology: Brain
Page 22 and 23: Figure 2: Normal 20 channels (10-20
Page 24 and 25: 1.1.2 EEG in Epilepsy One important
Page 28 and 29: Figure 4: Averaged responses upon N
Page 30 and 31: 2 Fourier Transform 2.1 Introductio
Page 32 and 33: I xx (k) =jX(k)j 2 = X(k) X (k) (
Page 34 and 35: 17 Figure 5: Topographical mapping
Page 36 and 37: 1987) is that coherence gives the c
Page 38 and 39: 3 Gabor Transform (Short Time Fouri
Page 40 and 41: where k g D k= R 1 ;1 jg D(t 0 )j 2
Page 42 and 43: and the band maximum peak frequency
Page 44 and 45: Figure 7: Intracraneal seizure reco
Page 46 and 47: Figure 10: Mean (soft line) and max
Page 48 and 49: EEG as the one with least amount of
Page 50 and 51: Figure 11: Scalp EEG of the right c
Page 52 and 53: 3.5 Conclusion In this chapter I de
Page 54 and 55: Original signal FOURIER TRANSFORM G
Page 56 and 57: 4.2.3 Multiresolution Analysis Cont
Page 58 and 59: Original signal -15 0 15 -1sec 0 1s
Page 60 and 61: 4.2.5 Wavelet Packets In the approa
Page 62 and 63: marked decrease in computational ti
Page 64 and 65: ain activity during an epileptic se
Page 66 and 67: 3 2 3 3 3 3.2 Hz 3.6 Hz 4.0 Hz 4.4
Page 68 and 69: Silva et al.,1973a,1973b Lopes da S
Page 70 and 71: sweep #1 sweep #2 sweep #3 sweep #4
Page 72 and 73: VEP non-target target F3 F4 F3 F4 F
Page 74 and 75: 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
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the position vs. the linear momentu
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unknown topology it is necessary to
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the sum of the positive exponents (
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performed. On one hand, must be lar
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Duke (1992) and Elbert et al. (1994
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agation time. They applied this pro
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Figure 28: Histogram for the EEG da
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Figure 29: Attractors corresponding
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able for automatic detection proces
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ENTROPY Thermodynamics Signal analy
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6.3 Application to visual event-rel
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VEP Non Target Target F3 -20 -10 0
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1 VEP NON-TARGET TARGET 1 1 F3 F3 0
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1 VEP NON-TARGET TARGET 1 1 F3 F3 0
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and the Lorenz equations (a model o
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P300 deection. Due to the relation
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7 General Discussion In this chapte
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Wavelet analysis was also applied t
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aect the whole spectrum and for thi
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peaks. 7.2.3 Wavelet Transform vs.
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the ones having wide peaks (being t
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A Time-frequency resolution and the
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Z 1 ;1 tx(t) d dt x(t) dt = 1 2 Z 1
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Figure 37: Time-frequency resolutio
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References Abarbanel HDI, Brown R,
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Berger, H. Uber das Elektrenkephalo
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Gastaut H and Broughton R. Epilepti
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Lopes da Silva FH, van Lierop THMT,
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Pradhan N, Sadasivan P, Chatterji S
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Serrano E, Ph.D. Thesis, Department
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Biographical sketch 21.03.1967 born
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