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 journalArticle

65 Citations (Scopus)

Abstract

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
Pages (from-to)880-893
Number of pages14
JournalPsychophysiology
Volume44
Issue number6
DOIs
Publication statusPublished - Nov 2007

Fingerprint

Functional Neuroimaging
Electroencephalography
Magnetic Resonance Imaging
Head

Keywords

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

ASJC Scopus subject areas

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

Cite this

Imaging functional brain connectivity patterns from high-resolution EEG and fMRI via graph theory. / Astolfi, L.; De Vico Fallani, F.; Cincotti, F.; Mattia, D.; Marciani, M. G.; Bufalari, S.; Salinari, S.; Colosimo, A.; Ding, L.; Edgar, J. C.; Heller, W.; Miller, G. A.; He, B.; Babiloni, F.

In: Psychophysiology, Vol. 44, No. 6, 11.2007, p. 880-893.

Research output: Contribution to journalArticle

Astolfi, L, De Vico Fallani, F, Cincotti, F, Mattia, D, Marciani, MG, Bufalari, S, Salinari, S, Colosimo, A, Ding, L, Edgar, JC, Heller, W, Miller, GA, He, B & Babiloni, F 2007, 'Imaging functional brain connectivity patterns from high-resolution EEG and fMRI via graph theory', Psychophysiology, vol. 44, no. 6, pp. 880-893. https://doi.org/10.1111/j.1469-8986.2007.00556.x
Astolfi, L. ; De Vico Fallani, F. ; Cincotti, F. ; Mattia, D. ; Marciani, M. G. ; Bufalari, S. ; Salinari, S. ; Colosimo, A. ; Ding, L. ; Edgar, J. C. ; Heller, W. ; Miller, G. A. ; He, B. ; Babiloni, F. / Imaging functional brain connectivity patterns from high-resolution EEG and fMRI via graph theory. In: Psychophysiology. 2007 ; Vol. 44, No. 6. pp. 880-893.
@article{7a2a2e0e9c3c4ff59fca78c97c57b1d3,
title = "Imaging functional brain connectivity patterns from high-resolution EEG and fMRI via graph theory",
abstract = "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.",
keywords = "Brain connectivity, fMRI, Graph theory, High-resolution EEG, Partial directed coherence, Stroop task",
author = "L. Astolfi and {De Vico Fallani}, F. and F. Cincotti and D. Mattia and Marciani, {M. G.} and S. Bufalari and S. Salinari and A. Colosimo and L. Ding and Edgar, {J. C.} and W. Heller and Miller, {G. A.} and B. He and F. Babiloni",
year = "2007",
month = "11",
doi = "10.1111/j.1469-8986.2007.00556.x",
language = "English",
volume = "44",
pages = "880--893",
journal = "Psychophysiology",
issn = "0048-5772",
publisher = "Wiley-Blackwell",
number = "6",

}

TY - JOUR

T1 - Imaging functional brain connectivity patterns from high-resolution EEG and fMRI via graph theory

AU - Astolfi, L.

AU - De Vico Fallani, F.

AU - Cincotti, F.

AU - Mattia, D.

AU - Marciani, M. G.

AU - Bufalari, S.

AU - Salinari, S.

AU - Colosimo, A.

AU - Ding, L.

AU - Edgar, J. C.

AU - Heller, W.

AU - Miller, G. A.

AU - He, B.

AU - Babiloni, F.

PY - 2007/11

Y1 - 2007/11

N2 - 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.

AB - 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.

KW - Brain connectivity

KW - fMRI

KW - Graph theory

KW - High-resolution EEG

KW - Partial directed coherence

KW - Stroop task

UR - http://www.scopus.com/inward/record.url?scp=35148867597&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=35148867597&partnerID=8YFLogxK

U2 - 10.1111/j.1469-8986.2007.00556.x

DO - 10.1111/j.1469-8986.2007.00556.x

M3 - Article

C2 - 17617172

AN - SCOPUS:35148867597

VL - 44

SP - 880

EP - 893

JO - Psychophysiology

JF - Psychophysiology

SN - 0048-5772

IS - 6

ER -