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Comparison of different multivariate methods for the estimation of cortical connectivity: simulations and applications to EEG data.

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Comparison of different multivariate methods for the estimation of cortical connectivity: simulations and applications to EEG data. / Astolfi, L; Cincotti, F; Mattia, D; de Vico Fallani, F; Lai, M; Baccala, L; Salinari, S; Ursino, M; Zavaglia, Melissa; Babiloni, F.

In: Conf Proc IEEE Eng Med Biol Soc, Vol. 5, 2005, p. 4484-4487.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Astolfi, L, Cincotti, F, Mattia, D, de Vico Fallani, F, Lai, M, Baccala, L, Salinari, S, Ursino, M, Zavaglia, M & Babiloni, F 2005, 'Comparison of different multivariate methods for the estimation of cortical connectivity: simulations and applications to EEG data.', Conf Proc IEEE Eng Med Biol Soc, vol. 5, pp. 4484-4487. <http://www.ncbi.nlm.nih.gov/pubmed/17281233?dopt=Citation>

APA

Astolfi, L., Cincotti, F., Mattia, D., de Vico Fallani, F., Lai, M., Baccala, L., Salinari, S., Ursino, M., Zavaglia, M., & Babiloni, F. (2005). Comparison of different multivariate methods for the estimation of cortical connectivity: simulations and applications to EEG data. Conf Proc IEEE Eng Med Biol Soc, 5, 4484-4487. http://www.ncbi.nlm.nih.gov/pubmed/17281233?dopt=Citation

Vancouver

Astolfi L, Cincotti F, Mattia D, de Vico Fallani F, Lai M, Baccala L et al. Comparison of different multivariate methods for the estimation of cortical connectivity: simulations and applications to EEG data. Conf Proc IEEE Eng Med Biol Soc. 2005;5:4484-4487.

Bibtex

@article{f39800be9463406b88823b095d16324d,
title = "Comparison of different multivariate methods for the estimation of cortical connectivity: simulations and applications to EEG data.",
abstract = "The problem of the definition and evaluation of brain connectivity has become a central one in neuroscience during the latest years, as a way to understand the organization and interaction of cortical areas during the execution of cognitive or motor tasks. Among various methods established during the years, the Directed Transfer Function (DTF), the Partial Directed Coherence (PDC) and the direct DTF (dDTF) are frequency-domain approaches to this problem, all based on a multivariate autoregressive modeling of time series and on the concept of Granger causality. In this paper we propose the use of these methods on cortical signals estimated from high resolution EEG recordings, a non invasive method which exhibits a higher spatial resolution than conventional cerebral electromagnetic measures. The principle contribution of this work are the results of a simulation study, testing the capability of the three estimators to reconstruct a connectivity model imposed, with a particular eye on the capability to distinguish between direct and indirect causality. An application to high resolution EEG recordings during a foot movement is also presented.",
author = "L Astolfi and F Cincotti and D Mattia and {de Vico Fallani}, F and M Lai and L Baccala and S Salinari and M Ursino and Melissa Zavaglia and F Babiloni",
year = "2005",
language = "English",
volume = "5",
pages = "4484--4487",

}

RIS

TY - JOUR

T1 - Comparison of different multivariate methods for the estimation of cortical connectivity: simulations and applications to EEG data.

AU - Astolfi, L

AU - Cincotti, F

AU - Mattia, D

AU - de Vico Fallani, F

AU - Lai, M

AU - Baccala, L

AU - Salinari, S

AU - Ursino, M

AU - Zavaglia, Melissa

AU - Babiloni, F

PY - 2005

Y1 - 2005

N2 - The problem of the definition and evaluation of brain connectivity has become a central one in neuroscience during the latest years, as a way to understand the organization and interaction of cortical areas during the execution of cognitive or motor tasks. Among various methods established during the years, the Directed Transfer Function (DTF), the Partial Directed Coherence (PDC) and the direct DTF (dDTF) are frequency-domain approaches to this problem, all based on a multivariate autoregressive modeling of time series and on the concept of Granger causality. In this paper we propose the use of these methods on cortical signals estimated from high resolution EEG recordings, a non invasive method which exhibits a higher spatial resolution than conventional cerebral electromagnetic measures. The principle contribution of this work are the results of a simulation study, testing the capability of the three estimators to reconstruct a connectivity model imposed, with a particular eye on the capability to distinguish between direct and indirect causality. An application to high resolution EEG recordings during a foot movement is also presented.

AB - The problem of the definition and evaluation of brain connectivity has become a central one in neuroscience during the latest years, as a way to understand the organization and interaction of cortical areas during the execution of cognitive or motor tasks. Among various methods established during the years, the Directed Transfer Function (DTF), the Partial Directed Coherence (PDC) and the direct DTF (dDTF) are frequency-domain approaches to this problem, all based on a multivariate autoregressive modeling of time series and on the concept of Granger causality. In this paper we propose the use of these methods on cortical signals estimated from high resolution EEG recordings, a non invasive method which exhibits a higher spatial resolution than conventional cerebral electromagnetic measures. The principle contribution of this work are the results of a simulation study, testing the capability of the three estimators to reconstruct a connectivity model imposed, with a particular eye on the capability to distinguish between direct and indirect causality. An application to high resolution EEG recordings during a foot movement is also presented.

M3 - SCORING: Journal article

VL - 5

SP - 4484

EP - 4487

ER -