Imaging functional brain connectivity patterns from high-resolution EEG and fMRI via graph theory

L. Astolfi, F. De Vico Fallani, F. Cincotti, D. Mattia, M. G. Marciani, S. Bufalari, S. Salinari, A. Colosimo, L. Ding, J. C. Edgar, W. Heller, G. A. Miller, B. He, F. Babiloni

Research output: Contribution to journalArticlepeer-review


We describe a set of computational tools able to estimate cortical activity and connectivity from high-resolution EEG and fMRI recordings in humans. These methods comprise the estimation of cortical activity using realistic geometry head volume conductor models and distributed cortical source models, followed by the evaluation of cortical connectivity between regions of interest coincident with the Brodmann areas via the use of Partial Directed Coherence. Connectivity patterns estimated on the cortical surface in different frequency bands are then imaged and interpreted with measures based on graph theory. These computational tools were applied on a set of EEG and fMRI data from a Stroop task to demonstrate the potential of the proposed approach. The present findings suggest that the methodology is able to identify differences in functional connectivity patterns elicited by different experimental tasks or conditions.

Original languageEnglish (US)
Pages (from-to)880-893
Number of pages14
Issue number6
StatePublished - Nov 2007


  • Brain connectivity
  • Graph theory
  • High-resolution EEG
  • Partial directed coherence
  • Stroop task
  • fMRI

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Neuropsychology and Physiological Psychology
  • Physiology (medical)
  • Physiology


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