• DocumentCode
    3005684
  • Title

    Identification of brain networks with high time/space resolution using dense EEG

  • Author

    Hassan, M. ; Dufor, O. ; Benquet, P. ; Berrou, C. ; Wendling, F.

  • Author_Institution
    Lab. de Traitement du Signal et de L´image (LTSI), Univ. de Rennes 1, Rennes, France
  • fYear
    2015
  • fDate
    22-24 April 2015
  • Firstpage
    1060
  • Lastpage
    1063
  • Abstract
    A challenging issue in cognition is how to precisely identify brain networks at very short temporal scales. So far, very few studies have addressed this problem as it requires high temporal and spatial resolution simultaneously. The recent past years have seen a noticeable increase of interest for electroencephalography (EEG) to analyze functional connectivity through brain sources reconstructed from scalp signals. Here, we performed a novel study based on EEG source connectivity to identify large scale networks with high temporal and spatial resolution. We show clear evidence of the ability of EEG source connectivity to identify brain networks with high time/space resolution during the visual processing period of picture naming task. Our qualitative and quantitative observations show that the identified brain networks are in accordance with fMRI-based results reported in the literature regarding involved brain areas.
  • Keywords
    cognition; electroencephalography; EEG source connectivity; brain networks; cognition; electroencephalography; fMRI; functional connectivity; high time-space resolution; Electroencephalography; Image reconstruction; Neuroscience; Scalp; Spatial resolution; Synchronization; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Engineering (NER), 2015 7th International IEEE/EMBS Conference on
  • Conference_Location
    Montpellier
  • Type

    conf

  • DOI
    10.1109/NER.2015.7146810
  • Filename
    7146810