• DocumentCode
    1124223
  • Title

    Integrated MEG/EEG and fMRI model based on neural masses

  • Author

    Babajani, A. ; Soltanian-Zadeh, Hamid

  • Author_Institution
    Electr. & Comput. Eng. Dept., Tehran Univ.
  • Volume
    53
  • Issue
    9
  • fYear
    2006
  • Firstpage
    1794
  • Lastpage
    1801
  • Abstract
    We introduce a bottom-up model for integrating electroencephalography (EEG) or magnetoencephalography (MEG) with functional magnetic resonance imaging (fMRI). An extended neural mass model is proposed based on the physiological principles of cortical minicolumns and their connections. The fMRI signal is extracted from the proposed neural mass model by introducing a relationship between the stimulus and the neural activity and using the resultant neural activity as input of the extended Balloon model. The proposed model, validated using simulations, is instrumental in evaluating the upcoming combined methods for simultaneous analysis of MEG/EEG and fMRI
  • Keywords
    biomedical MRI; electroencephalography; magnetoencephalography; medical image processing; neurophysiology; physiological models; EEG; MEG; bottom-up model; cortical minicolumns; electroencephalography; extended Balloon model; extended neural mass model; fMRI; functional magnetic resonance imaging; magnetoencephalography; neural activity; signal extraction; Brain modeling; Electroencephalography; Enterprise resource planning; Hemodynamics; Intelligent control; Magnetic resonance imaging; Magnetoencephalography; Process control; Spatial resolution; Spatiotemporal phenomena; EEG; MEG; fMRI; integrated model; neural mass; Algorithms; Brain; Brain Mapping; Computer Simulation; Diagnosis, Computer-Assisted; Electroencephalography; Evoked Potentials; Humans; Magnetic Resonance Imaging; Magnetoencephalography; Models, Neurological; Nerve Net; Systems Integration;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/TBME.2006.873748
  • Filename
    1673621