Estimation of the cortical connectivity during a finger-tapping movement with multimodal integration of EEG and fMRI recordings

Fabio Babiloni, Claudio Babiloni, Filippo Carducci, Paolo Maria Rossini, Alessandra Basilisco, Laura Astolfi, Febo Cincotti, Lei Ding, Y. Ni, J. Cheng, K. Christine, J. Sweeney, B. He

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

In this paper, advanced methods for the estimation of cortical connectivity from combined high-resolution electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data are presented. We used a computational approach to the estimation of cortical connectivity by computing the Directed Transfer Function (DTF), a technique used to estimate the direction of the information flow between signals gathered from EEG sensors. The proposed method was able to depict the direction of the information flows between the cortical regions of interest, since it is directional in nature. An application of these technique to the real high-resolution EEG and fMRI signals gathered during visual finger-tapping movements in three normal healthy subjects is also provided.

Original languageEnglish (US)
Pages (from-to)126-129
Number of pages4
JournalInternational Congress Series
Volume1270
Issue numberC
DOIs
StatePublished - Aug 1 2004

Keywords

  • Directed Transfer Function
  • EEG and fMRI integration
  • Linear inverse source estimate

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