In this paper, different linear and nonlinear methodologies for the estimation of cortical connectivity from neuroelectric and hemodynamic measurements are reviewed and applied on common data set in order to highlight similarities and differences in the results. Different effective and functional connectivity methods were applied to motor and cognitive data sets, including structural equation modeling (SEM), directed transfer function (DTF), partial directed coherence (PDC), and direct directed transfer function (dDTF). Comparisons were made between the results in order to understand if, for a same dataset, effective and functional connectivity estimators can return the same cortical connectivity patterns. An application of a nonlinear method [phase synchronization index (PSI)] to similar executed and imagined movements was also reviewed. Connectivity patterns estimated with the use of the neuroelectric information and of the information from the multimodal integration of neuroelectric and hemodynamic data were also compared. Results suggests that the estimation of the cortical connectivity patterns performed with the linear methods (SENT, DTF, PDC, dDTF) or with the nonlinear method (PSI) on movement related potentials returned similar cortical networks. Differences in cortical connectivity were noted between the patterns estimated with the use of multimodal integration and those estimated by using only the neuroelectric data.

Estimation of Effective and Functional Cortical Connectivity From Neuroelectric and Hemodynamic Recordings / Astolfi, Laura; DE VICO FALLANI, Fabrizio; Cincotti, Febo; D., Mattia; M. G., Marciani; Salinari, Serenella; J., Sweeney; G. A., Miller; B., He; Babiloni, Fabio. - In: IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING. - ISSN 1534-4320. - 17:3(2009), pp. 224-233. [10.1109/tnsre.2008.2010472]

Estimation of Effective and Functional Cortical Connectivity From Neuroelectric and Hemodynamic Recordings

ASTOLFI, LAURA;DE VICO FALLANI, FABRIZIO;CINCOTTI, FEBO;SALINARI, Serenella;BABILONI, Fabio
2009

Abstract

In this paper, different linear and nonlinear methodologies for the estimation of cortical connectivity from neuroelectric and hemodynamic measurements are reviewed and applied on common data set in order to highlight similarities and differences in the results. Different effective and functional connectivity methods were applied to motor and cognitive data sets, including structural equation modeling (SEM), directed transfer function (DTF), partial directed coherence (PDC), and direct directed transfer function (dDTF). Comparisons were made between the results in order to understand if, for a same dataset, effective and functional connectivity estimators can return the same cortical connectivity patterns. An application of a nonlinear method [phase synchronization index (PSI)] to similar executed and imagined movements was also reviewed. Connectivity patterns estimated with the use of the neuroelectric information and of the information from the multimodal integration of neuroelectric and hemodynamic data were also compared. Results suggests that the estimation of the cortical connectivity patterns performed with the linear methods (SENT, DTF, PDC, dDTF) or with the nonlinear method (PSI) on movement related potentials returned similar cortical networks. Differences in cortical connectivity were noted between the patterns estimated with the use of multimodal integration and those estimated by using only the neuroelectric data.
2009
directed transfer function (dtf); functional cortical connectivity; high-resolution eeg; partial directed coherence (pdc); structural equation modeling (sem)
01 Pubblicazione su rivista::01a Articolo in rivista
Estimation of Effective and Functional Cortical Connectivity From Neuroelectric and Hemodynamic Recordings / Astolfi, Laura; DE VICO FALLANI, Fabrizio; Cincotti, Febo; D., Mattia; M. G., Marciani; Salinari, Serenella; J., Sweeney; G. A., Miller; B., He; Babiloni, Fabio. - In: IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING. - ISSN 1534-4320. - 17:3(2009), pp. 224-233. [10.1109/tnsre.2008.2010472]
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