Comparison of different cortical connectivity estimators for high-resolution EEG recordings.
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Comparison of different cortical connectivity estimators for high-resolution EEG recordings. / Astolfi, Laura; Cincotti, Febo; Mattia, Donatella; Marciani, M Grazia; Baccala, Luiz A; de Vico Fallani, Fabrizio; Salinari, Serenella; Ursino, Mauro; Zavaglia, Melissa; Ding, Lei; Edgar, J Christopher; Miller, Gregory A; He, Bin; Babiloni, Fabio.
In: HUM BRAIN MAPP, Vol. 28, No. 2, 2, 2007, p. 143-157.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
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TY - JOUR
T1 - Comparison of different cortical connectivity estimators for high-resolution EEG recordings.
AU - Astolfi, Laura
AU - Cincotti, Febo
AU - Mattia, Donatella
AU - Marciani, M Grazia
AU - Baccala, Luiz A
AU - de Vico Fallani, Fabrizio
AU - Salinari, Serenella
AU - Ursino, Mauro
AU - Zavaglia, Melissa
AU - Ding, Lei
AU - Edgar, J Christopher
AU - Miller, Gregory A
AU - He, Bin
AU - Babiloni, Fabio
PY - 2007
Y1 - 2007
N2 - The aim of this work is to characterize quantitatively the performance of a body of techniques in the frequency domain for the estimation of cortical connectivity from high-resolution EEG recordings in different operative conditions commonly encountered in practice. Connectivity pattern estimators investigated are the Directed Transfer Function (DTF), its modification known as direct DTF (dDTF) and the Partial Directed Coherence (PDC). Predefined patterns of cortical connectivity were simulated and then retrieved by the application of the DTF, dDTF, and PDC methods. Signal-to-noise ratio (SNR) and length (LENGTH) of EEG epochs were studied as factors affecting the reconstruction of the imposed connectivity patterns. Reconstruction quality and error rate in estimated connectivity patterns were evaluated by means of some indexes of quality for the reconstructed connectivity pattern. The error functions were statistically analyzed with analysis of variance (ANOVA). The whole methodology was then applied to high-resolution EEG data recorded during the well-known Stroop paradigm. Simulations indicated that all three methods correctly estimated the simulated connectivity patterns under reasonable conditions. However, performance of the methods differed somewhat as a function of SNR and LENGTH factors. The methods were generally equivalent when applied to the Stroop data. In general, the amount of available EEG affected the accuracy of connectivity pattern estimations. Analysis of 27 s of nonconsecutive recordings with an SNR of 3 or more ensured that the connectivity pattern could be accurately recovered with an error below 7% for the PDC and 5% for the DTF. In conclusion, functional connectivity patterns of cortical activity can be effectively estimated under general conditions met in most EEG recordings by combining high-resolution EEG techniques, linear inverse estimation of the cortical activity, and frequency domain multivariate methods such as PDC, DTF, and dDTF.
AB - The aim of this work is to characterize quantitatively the performance of a body of techniques in the frequency domain for the estimation of cortical connectivity from high-resolution EEG recordings in different operative conditions commonly encountered in practice. Connectivity pattern estimators investigated are the Directed Transfer Function (DTF), its modification known as direct DTF (dDTF) and the Partial Directed Coherence (PDC). Predefined patterns of cortical connectivity were simulated and then retrieved by the application of the DTF, dDTF, and PDC methods. Signal-to-noise ratio (SNR) and length (LENGTH) of EEG epochs were studied as factors affecting the reconstruction of the imposed connectivity patterns. Reconstruction quality and error rate in estimated connectivity patterns were evaluated by means of some indexes of quality for the reconstructed connectivity pattern. The error functions were statistically analyzed with analysis of variance (ANOVA). The whole methodology was then applied to high-resolution EEG data recorded during the well-known Stroop paradigm. Simulations indicated that all three methods correctly estimated the simulated connectivity patterns under reasonable conditions. However, performance of the methods differed somewhat as a function of SNR and LENGTH factors. The methods were generally equivalent when applied to the Stroop data. In general, the amount of available EEG affected the accuracy of connectivity pattern estimations. Analysis of 27 s of nonconsecutive recordings with an SNR of 3 or more ensured that the connectivity pattern could be accurately recovered with an error below 7% for the PDC and 5% for the DTF. In conclusion, functional connectivity patterns of cortical activity can be effectively estimated under general conditions met in most EEG recordings by combining high-resolution EEG techniques, linear inverse estimation of the cortical activity, and frequency domain multivariate methods such as PDC, DTF, and dDTF.
KW - Humans
KW - Signal Processing, Computer-Assisted
KW - Magnetic Resonance Imaging
KW - Analysis of Variance
KW - Computer Simulation
KW - Brain Mapping
KW - Models, Neurological
KW - Cerebral Cortex/physiology
KW - Electroencephalography
KW - Neural Pathways/physiology
KW - Humans
KW - Signal Processing, Computer-Assisted
KW - Magnetic Resonance Imaging
KW - Analysis of Variance
KW - Computer Simulation
KW - Brain Mapping
KW - Models, Neurological
KW - Cerebral Cortex/physiology
KW - Electroencephalography
KW - Neural Pathways/physiology
M3 - SCORING: Journal article
VL - 28
SP - 143
EP - 157
JO - HUM BRAIN MAPP
JF - HUM BRAIN MAPP
SN - 1065-9471
IS - 2
M1 - 2
ER -
