Abstract
Electroencephalography (EEG) and magnetoencephalography (MEG) are non-invasive electrophysiological methods, which record electric potentials and magnetic fields due to electric currents in synchronously-active neurons. With MEG being more sensitive to neural activity from tangential currents and EEG being able to detect both radial and tangential sources, the two methods are complementary. Over the years, neurophysiological studies have changed considerably: high-density recordings are becoming de rigueur; there is interest in both spontaneous and evoked activity; and sophisticated artifact detection and removal methods are available. Improved head models for source estimation have also increased the precision of the current estimates, particularly for EEG and combined EEG/MEG. Because of their complementarity, more investigators are beginning to perform simultaneous EEG/MEG studies to gain more complete information about neural activity. Given the increase in methodological complexity in EEG/MEG, it is important to gather data that are of high quality and that are as artifact free as possible. Here, we discuss some issues in data acquisition and analysis of EEG and MEG data. Practical considerations for different types of EEG and MEG studies are also discussed.
Highlights
The Evolution of EEG/MEG StudiesEEG and MEG are excellent complementary methods that offer a non-invasive way to studymillisecond brain dynamics
One way to ensure that the timing of stimuli and events are recorded accurately during data acquisition is by performing a “dry run” of the experiment before acquiring real data (Figure 1)
It should be noted that the issues we highlighted with EEG reference electrodes above are not a consideration if the data are analyzed in source space
Summary
EEG and MEG are excellent complementary methods that offer a non-invasive way to study (sub)millisecond brain dynamics. MEG data were traditionally analyzed in source space, i.e., in terms of the estimated spatial distribution and time courses of the actual brain activity, while EEG more typically in sensor space, studying signals in the electrodes of interest. While accurate source estimation is possible based on EEG data, as well, the required head model is much more complex and must consider tissue conductivities and the individual shape of the compartments with different electrical conductivity, e.g., the scalp, skull, grey and white matter, as well as the cerebrospinal fluid [12,13] In this century, EEG/MEG studies have begun to focus more on brain oscillations (rhythms) that are not strictly phase-locked to a stimulus or a motor action, or that occur spontaneously. We have drawn on material in earlier publications [1,2,3,4,5,6], as well as on our own experiences in using EEG/MEG
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