Embed Size (px)
DESCRIPTION
Alois Schlögl University of Technology Graz, Austria . Analyzing EEG Coupling. COST B27 ENOC Joint WGs Meeting Swansea UK, 16-18 September 2006. Offer: Methods for analysing EEG coupling using Multivariate autoregressive modelling - PowerPoint PPT Presentation
Citation preview
1
Analyzing EEG Coupling
Alois Schlögl University of Technology Graz, Austria
COST B27 ENOC Joint WGs Meeting Swansea UK, 16-18 September 2006
2
• Offer: – Methods for analysing EEG coupling using
Multivariate autoregressive modelling– Coherency, PDC, DTF, phase, etc. – BioSig http://biosig.sf.net
• Asking for:– EEG data on interesting research topics– collaboration
3
Multivariate AutoRegressive (MVAR) models
• Multivariate: spatio-temporal correlation
• Estimators:– Levinson-Wiggins-Robinson (LWR):
Multivariate Yule-Walker– Nutall-Strand method (multivariate burg method)– Vieira-Morf (multivariate geometric lattice)
• Software: – TSA-toolbox: MVAR.M– BioSig http://biosig.sf.net
Schlögl (2006), Comparison of MVAR estimators, Signal Processing.
4
5Coupling almost all the time in all frequencies !?
Time-Frequency AnalysisPDC (Hypothesis: PDC>0)
0
1
Subject K3Left hand
6
Event-related PDC (Hypothesis: PDC != ref)
Increases and decreases of coupling can be observed !
pdc<ref
pdc>ref
Subject K3Left handref=pdc(0-3s)
7
8
MVAR estimators
Comparison of • ARFIT• Multichannel Yule-
Walker• Multichannel Burg
(Nutall-Strand)
Schlögl, A. (2006) Comparison of Multivariate Autoregressive Estimators.Signal processing
1 2 5 10 20
1
2
3
4
5
mean square predicition error
rank
ing
N=50N=60N=70N=100N=400
Nuttall-Strand with unbiased covariance
Nuttall-Strand with biased covariance
ARFIT-0
multichannel Yule-Walker
ARFIT
N=40
9
Signal processing (II)
• Spectrum • Coherence (absCOH, imagCOH)• Partial coherence (pCOH)• Partial directed coherence (PDC) • Directed transfer function (DTF)• Full-Frequency DTF (ffDTF)• Directed coupling (DC) • Phase
10
Auto/Crossspectra & Coherence
0 10 20 30 40 50
100
#01
#01
0 10 20 30 40 50
100
#02
0 10 20 30 40 50
100
#03
0 10 20 30 40 50
100
#04
0 10 20 30 40 50
100
#05
0 10 20 30 40 50
100
#02
0 10 20 30 40 50
100
0 10 20 30 40 50
100
0 10 20 30 40 50
100
0 10 20 30 40 50
100
0 10 20 30 40 50
100
#03
0 10 20 30 40 50
100
0 10 20 30 40 50
100
0 10 20 30 40 50
100
0 10 20 30 40 50
100
0 10 20 30 40 50
100
#04
0 10 20 30 40 50
100
0 10 20 30 40 50
100
0 10 20 30 40 50
100
0 10 20 30 40 50
100
0 10 20 30 40 50
100
#05
0 10 20 30 40 50
100
0 10 20 30 40 50
100
0 10 20 30 40 50
100
logS
0 10 20 30 40 50
100
0 500
0.5
1
#01
#01
0 500
0.5
1#02
0 500
0.5
1#03
0 500
0.5
1#04
0 500
0.5
1#05
0 500
0.5
1
#02
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
#03
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
#04
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
#05
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
COH
0 500
0.5
1
11
Imaginare und partiel Coherence
0 500
0.5
1
#01
#01
0 500
0.5
1#02
0 500
0.5
1#03
0 500
0.5
1#04
0 500
0.5
1#05
0 500
0.5
1
#02
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
#03
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
#04
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
#05
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
pCOH
0 500
0.5
1
0 50-1
0
1
#01
#01
0 50-1
0
1#02
0 50-1
0
1#03
0 50-1
0
1#04
0 50-1
0
1#05
0 50-1
0
1
#02
0 50-1
0
1
0 50-1
0
1
0 50-1
0
1
0 50-1
0
1
0 50-1
0
1
#03
0 50-1
0
1
0 50-1
0
1
0 50-1
0
1
0 50-1
0
1
0 50-1
0
1
#04
0 50-1
0
1
0 50-1
0
1
0 50-1
0
1
0 50-1
0
1
0 50-1
0
1
#05
0 50-1
0
1
0 50-1
0
1
0 50-1
0
1
iCOH
0 50-1
0
1
12
Directed transfer function DTF & partial directed coherence (PDC)
0 500
0.5
1
#01
#01
0 500
0.5
1#02
0 500
0.5
1#03
0 500
0.5
1#04
0 500
0.5
1#05
0 500
0.5
1
#02
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
#03
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
#04
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
#05
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
DTF
0 500
0.5
1
0 500
0.5
1
#01
#01
0 500
0.5
1#02
0 500
0.5
1#03
0 500
0.5
1#04
0 500
0.5
1#05
0 500
0.5
1
#02
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
#03
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
#04
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
#05
0 500
0.5
1
0 500
0.5
1
0 500
0.5
1
PDC
0 500
0.5
1
13
Thank You for the Attention
• References: – Schlögl, 2006, Comparison of Multivariate
Autoregressive Estimators.Signal processing
– Schlögl and Supp (in press), Progress In Brain Research
Contact: Alois Schlögl [email protected]://biosig.sf.net
14Coupling almost all the time in all frequencies !?
DTF (Hypothesis: DTF>0)
0
1
Subject K3Left hand
15Increases and decreases of coupling can be observed !
pdc<ref
pdc>ref
Subject K3Right handref=pdc(0-3s)
Event-related PDC (Hypothesis: PDC != ref)
![NSF Project EEG CIRCUIT DESIGN. Micro-Power EEG Acquisition SoC[10] Electrode circuit EEG sensing Interference](https://img.pdfslide.net/doc/110x75/56649cfb5503460f949ccecd/nsf-project-eeg-circuit-design-micro-power-eeg-acquisition-soc10-electrode.jpg)
