The concept of “brain activity” is elusive, since activity can be measured in different ways and the concept express very different things. Do we mean single neuron action potentials, coordinated assemblies of neurons, metabolic consumption, sub-threshold oscillations…? From an experimental point of view, this ambiguity translates into different techniques that measure different facets of what we could consider activity in the brain. It seems only natural to simultaneously combine methods that capture different facets of neural activity, even more since methods usually differ in their spatio-temporal resolution. For instance, electroencephalography (EEG), an old method to capture variations in the electrical potential over the scalp, measures oscillatory activity with a very high sampling rate (temporal resolution). Functional Magnetic Resonance Imaging (fMRI) measures quantities related to metabolic rate and oxygen consumption, with good spatial resolution but bad temporal resolution. Thus, both methods appear to be complementary.

Indeed, with adequate equipment and precautions, EEG and fMRI can be measured simultaneously. In the Laufs group of the Frankfurt Brain Imaging Center, we perform simultaneous EEG-fMRI experiments to understand the neural basis of the fMRI signal and to perform spatial mapping of diffuse oscillatory activity measured (at the scalp level) with EEG. In recent work, for example, we have demonstrated the presence of relatively slow fluctuations in functional connectivity (“dynamic functional connectivity”), measured with fMRI, and established their electrophysiological correlates. This and similar analyses act as a bridge between a wealth of results linking EEG oscillations in different frequencies to cognitive processes, and the relatively unexplored world of large-scale synchronisation between cortical areas, as measured with fMRI.

Journal reference:

Tagliazucchi, E., Von Wegner, F., Morzelewski, A., Brodbeck, V., Laufs, H. (2012). Dynamic BOLD functional connectivity in humans and its electrophysiological correlates. Frontiers in Neuroscience.