Multimodal integration of EEG, MEG and fMRI data for the solution of the neuroimage puzzle

被引:59
作者
Babiloni, F [1 ]
Mattia, D
Babiloni, C
Astolfi, L
Salinari, S
Basilisco, A
Rossini, PM
Marciani, MG
Cincotti, F
机构
[1] Univ Roma La Sapienza, Dept Human Physiol & Pharmacol, I-00185 Rome, Italy
[2] Fdn Santa Lucia, Ist Ricovero & Cura Carattere Sci, Dipartimento Neurofisiopatol, I-00100 Rome, Italy
[3] Osped Iola Tiberina, Assoc Fatebenefratelli Ric, Dept Neurosci, I-00100 Rome, Italy
[4] Ist Ricovero & Cura Carattere Sci San Giovanni Di, I-25100 Brescia, Italy
[5] Univ Roma La Sapienza, Dept Informat & Syst, I-00185 Rome, Italy
[6] Cattedra Neurol, I-00100 Rome, Italy
[7] Univ Roma Tor Vergata, Dept Neurosci, I-00100 Rome, Italy
关键词
linear inverse source estimate; multimodal EEG; MEG and fMRI integration; movement-related potentials;
D O I
10.1016/j.mri.2004.10.007
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
In this paper, advanced methods for the modeling of human cortical activity from combined high-resolution electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) data are presented. These methods include a subject's multicompartment head model (scalp, skull, dura mater, cortex) constructed from magnetic resonance images, multidipole source model and regulafized linear inverse source estimates of cortical current density. Determination of the priors in the resolution of the linear inverse problem was per-formed with the use of information from the hemodynamic responses of the cortical areas as revealed by block-designed (strength of activated voxels) fMRI. Examples of the application of these methods to the estimation of the time varying cortical current density activity in selected region of interest (ROI) are presented for movement-related high-resolution EEG data. (C) 2004 Elsevier Inc. All rights reserved.
引用
收藏
页码:1471 / 1476
页数:6
相关论文
共 31 条
  • [1] Dynamics of ongoing activity: Explanation of the large variability in evoked cortical responses
    Arieli, A
    Sterkin, A
    Grinvald, A
    Aertsen, A
    [J]. SCIENCE, 1996, 273 (5283) : 1868 - 1871
  • [2] How well do we understand the neural origins of the fMRI BOLD signal?
    Arthurs, OJ
    Boniface, S
    [J]. TRENDS IN NEUROSCIENCES, 2002, 25 (01) : 27 - 31
  • [3] Babiloni F, 2000, METHOD INFORM MED, V39, P179
  • [4] Multimodal integration of high-resolution EEG and functional magnetic resonance imaging data: a simulation study
    Babiloni, F
    Babiloni, C
    Carducci, F
    Romani, GL
    Rossini, PM
    Angelone, LM
    Cincotti, F
    [J]. NEUROIMAGE, 2003, 19 (01) : 1 - 15
  • [5] Linear inverse source estimate of combined EEG and MEG data related to voluntary movements
    Babiloni, F
    Carducci, F
    Cincotti, F
    Del Gratta, C
    Pizzella, V
    Romani, GL
    Rossini, PM
    Tecchio, F
    Babiloni, C
    [J]. HUMAN BRAIN MAPPING, 2001, 14 (04) : 197 - 209
  • [6] A Bayesian approach to introducing anatomo-functional priors in the EEG/MEG inverse problem
    Baillet, S
    Garnero, L
    [J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 1997, 44 (05) : 374 - 385
  • [7] Combined MEG and EEG source imaging by minimization of mutual information
    Baillet, S
    Garnero, L
    Marin, G
    Hugonin, JP
    [J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 1999, 46 (05) : 522 - 534
  • [8] BRAITEMBERG V, 1991, ANAT CORTEX
  • [9] Dynamic statistical parametric mapping: Combining fMRI and MEG for high-resolution imaging of cortical activity
    Dale, AM
    Liu, AK
    Fischl, BR
    Buckner, RL
    Belliveau, JW
    Lewine, JD
    Halgren, E
    [J]. NEURON, 2000, 26 (01) : 55 - 67
  • [10] IMPROVED LOCALIZATION OF CORTICAL ACTIVITY BY COMBINING EEG AND MEG WITH MRI CORTICAL SURFACE RECONSTRUCTION - A LINEAR-APPROACH
    DALE, AM
    SERENO, MI
    [J]. JOURNAL OF COGNITIVE NEUROSCIENCE, 1993, 5 (02) : 162 - 176