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Detection of phase synchronization applied to audio-visual stimulation EEG
M. Teplan,
K. Šušmáková, M. Paluš, M. Vejmělka
Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovak republic
Institute of Computer Science, Academy of Sciences of the Czech republic, Praha, Czech republic
Outline
• synchronization phenomena
• phase synchronization detection
• brief illustration of the method
• audio-visual stimulation
• conclusions
Introduction
- synchronization phenomena play a key role in organization of biological structures
- for application of existing theories and models dfficulties may arise with experimental data contaminated by noise: problem to distinguish phase synchronized regime from asynchronous one.
- we illustrate a method that is able to quantify a degree of phase synchrony
- demonstration on audio-visual stimulation data
Synchronization phenomena
- biomeasurements may yield complex and broadband data
- emergence of dynamical order: spontanous development of structural organizations in complex systems
- in some cases phase synchronization is sufficient for order maintaining, or it may be a sign for aproaching general synchronization
- simplest system: two coupled 1D harmonic oscilators
- 3D nonlinear system: Lorentz, Rosler
- two or N coupled 3D nonlinear system:
- coupling in one or both directions
- common inherent frequencies or (slightly) different ones
Phase synchronization detection
- increasing coupling constant: asynchrony, phase synchrony, general synchrony:
M. Rosenblum et al.: Phase synchronization of chaotic oscillators. Physical Review Letters, 1996, 76/11.
- phase synchronization can be expected to occur in real biosystems at different organizational levels due to nonlinear nature and feedback ties
- synchronization may not be obvious but masked
- phase locking: nφ1 - mφ2 = const- applied in study of epilepsy - onset and predictions- cardio-respiratory data
- atmoshere CO2 concentration and sun spot cycles
- estimation of degree of phase dependence- method is sensitive to number of parameters- approaches are still under development
EEG and wavelet transform
Complex wavelet transform
0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5
-15
-10
-5
0
5
10
time [sec]
Vol
tage
[V
]
P3O1P4O2
-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1
-1
-0.5
0
0.5
1
time [sec]
ampl
itude
Morlet wavelet with central frequency 4 Hz and width 1 Hz
Phase extraction
655 660 665 670 675 680400
500
600
700
800
900
1000
1100
time [sec]
an
gu
lar
diff
ere
nce
[ra
d]
during stimulation
660 661 662 663 664 665
-3
-2
-1
0
1
2
3
time [sec]
wra
ped
phas
e [r
ad]
Phase difference in unwrapped mode
flat regions represent synchronized periods, slopy intervals mark phase slips 20 40 60 80 100 120 140 160
0
50
100
150
200
250
time [sec]
angu
lar
diffe
renc
e [r
ad] before stimulation
640 660 680 700 720 7400
10
20
30
40
50
60
time [sec]
angu
lar
diffe
renc
e [r
ad]
during stimulation
710 711 712 71330
31
32
33
34
35
36
37
38
39
40
2π
Phase differences distribution evaluation
1 2 3 4 5 60
20
40
60
80
100
wraped phase difference [rad]
amou
nt
1 2 3 4 5 60
5
10
15
20
25
30
wraped phase difference [rad]
amou
nt
- evaluation of irregularity of the distribution by mean phase coherence
(MPC): values between 0 (uniform) and 1 (fully concentrated) and reflects
how the relative phase is distributed over the unit circle
- high values of MPC do not always identify synchrony clearly
during stimulation before stimulation
Surrogate data
640 660 680 700 720 740
0.2
0.4
0.6
0.8
time [sec]
during stimulation
20 40 60 80 100 120 140 160
0.2
0.4
0.6
0.8
time [sec]
syn
chro
niz
atio
n m
ea
sure
before stimulation
- Testing hypothesis that value of dependence index is due to
selected data properties
- FT1 surrogates preserves the power spectrum, however randomly changes the
phases of the Fourier coefficients for each time serie separately
- If the null hypothesis stating that surrogates possess the same synchronization as
EEG is refused, occurrence of linear phase synchronization is assumed
Mind machines?
Audio-visual stimulation of the brain (AVS): - brain influence through audio and visual sensory channel
- adaptation of dominant EEG frequency – wave brain entrainment
- potential use: strokes, head injury, headaches, dental anxiety, premenstrual syndrome, cognitive and behavioral functioning, performance improvement
- AVS training: direct, short and long term effects
M. Teplan et al.: EEG responses to long-term audio-visual stimulation. International Journal of Psychophysiology, 2006, 59/2
M. Teplan, A. Krakovská, S. Štolc: Direct and transient effects of audio-visual stimulation on EEG, submitted
Brain wave entrainmentcourse of the stimulation &
brain response - EEG spectrogram:
Direct effects of stimulation
• evaluation with ratios of relative powers in narrow frequency band:
• during stimulation referenced to interval prior to stimulation
• high statistical significancy of AVS effect, quite large variations
• the strongest effect at visual cortex and for higher frequencies
Ratio of relative band powers
0
5
10
15
20
25
30
F3C3 F4C4 C3P3 C4P4 P3O1 P4O2
2 Hz4 Hz9 Hz17 Hz
Phase synchronization during AVS
• Difference in phase synchronization during stimulation in respect to nonstimulation conditions: Difference of medians of z-scores. Z-scores evaluate distance of synchronization measure MPC from testing surrogate MPCs. Higher positive values mean higher increase of synchronization during the stimulation.
• Mann-Whitney U test (paired Wilcoxon) reflects a strong level of statistical significance (p-values from 10-7 to 0.03) in all selected pairs for both stimulating frequencies.
• Stronger effect for 17 Hz than for 4 Hz stimulation.
• Interhemispheric relations: without monotonous decrease towards frontal locations - top values for centro-parietal regions.
• Possible enhanced communication also between cross areas (F3C3-P3O1, F4C4-P4O2).
Comparison to coherence methodsduring stimulation:
prior to stimulation: linear correlation coefficient < 0.5
- approaches determining phase synchrony level are usefull for EEG studies
- in the case of audio-visual stimulation we were able to determine regions with different synchronization relations
- decrease in synchronization roughly follows power attenuation
- possible impact on higher brain functions across the cortex
- future work: application of directionality index – related technique for finding direction of the information flow
Conclusions