Get access

Endogenous brain oscillations and related networks detected by surface EEG-combined fMRI


  • Helmut Laufs

    Corresponding author
    1. Department of Neurology and Brain Imaging Center, Johann Wolfgang Goethe-University, Frankfurt am Main, Germany
    2. Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, United Kingdom
    • Klinikum der Johann Wolfgang Goethe-Universität, Zentrum der Neurologie und Neurochirurgie, Klinik für Neurologie, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany
    Search for more papers by this author


It is difficult to study the brain “at rest” with an approach generally pursued in science when external manipulation (independent variable) is used to obtain informative measurements (dependent variable) about the object of interest. External manipulation in its classic sense may suspend the resting state, and hence the object of interest will evade. Naturally, unless in a final and irreversible state, biological rest will always be an endogenously dynamic process. Combining two modalities, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), to simultaneously measure the brain's activity from two angles, one can be chosen to be interpreted as the independent variable and the other as the dependent variable, and without external manipulation the brain's spontaneous dynamics can be studied. The EEG, for example, observes endogenous modulations of vigilance and detects spontaneous events such as sleep spindles or epileptic discharges and can be used as the independent variable, i.e., to form a regressor to interrogate the fMRI data (dependent variable). The opposite is possible as well, and data fusion attempts try using all data both as dependent and independent variables at the same time. This review limits itself to an exemplary discussion of simultaneous EEG/fMRI studies in humans, and among a variety of proposed resting state networks only discusses a few, especially those for which non-resting state literature has proposed a functional meaning: the “default mode” network and an attentional network. It will be shown that one EEG feature can correlate with different fMRI activation maps and that a single resting state network may be associated with a variety of EEG patterns giving insight into the function of different resting states and the relationship between the two modalities in themselves. Hum Brain Mapp 2008. © 2008 Wiley-Liss, Inc.