Source analysis of EEG oscillations using high-resolution EEG and MEG

Abstract

We investigated spatial properties of the source distributions that generate scalp electroencephalographic (EEG) oscillations. The inherent complexity of the spatiotemporal dynamics of EEG oscillations indicates that conceptual models that view source activity as consisting of only of a few "equivalent dipoles" are inadequate. We present an approach that uses volume conduction models to characterize the distinct spatial filtering of cortical source activity by averagereference EEG, high-resolution EEG, and magnetoencephalography (MEG). By comparing these three measures, we can make inferences about the sources of EEG oscillations without having to make prior assumptions about the sources. We apply this approach to spontaneous EEG oscillations observed with eyes closed at rest. Both EEG and MEG recordings show robust alpha rhythms over posterior regions of the cortex; however, the dominant frequency of these rhythms varies between EEG and MEG recordings. Frontal alpha and theta rhythms are generated almost exclusively by superficial radial dipole layers that generate robust EEG signals but very little MEG signals; these sources are presumably mainly in the gyral crowns of frontal cortex. MEG and high-resolution EEG estimates of alpha rhythms provide evidence of local tangential and radial sources in the posterior cortex, lying mainly on sulcal and gyral surfaces. Despite the detailed information about local radial and tangential sources potentially afforded by high-resolution EEG and MEG, it is also evident that the alpha and theta rhythms receive contributions from non-local source activity, for instance large dipole layers distributed over lobeal or (potentially) even larger spatial scales.

EEG signatures of arm isometric exertions in preparation, planning and execution

“…Magnetoencephalography (MEG) and EEG signatures of arm movements (Waldert et al, 2008), as well as electrocorticography (ECoG) signatures show ERD in α and β bands with most of the reported ERD on contralateral and to some extent ipsilateral motor areas. This is in agreement with general expectations of movement related ERD/ERS (Graimann and Pfurtscheller, 2006;da Silva, 2006;Srinivasan et al, 2006). The ECoG signatures (ERD/ERS) of non-directional sustained isometric contractions of body parts over several regions of brain (Crone et al, 1998a,b) also show notable trends: There is α and β band ERD in transient and (to lesser extent) in sustained form over motor areas, in both ipsilateral and especially contralateral sides.…”

“…Future work is expected to apply source localisation techniques (Srinivasan et al, 2006), network analysis (Lindsay and Rosenberg 2011) and also more accurate time-frequency representations (Boashash, 2003;Cohen, 1995;Hlawatsch & Auger, 2008) to localize the ERD/ERS sources more accurately in time and frequency. However, given that a degree of inter-subject variability exists in the sample presented here there is a need for caution in interpretation.…”

Frontal theta EEG activity correlates negatively with the default mode network in resting state

“…Srinivasan et al (2006) report that theta power is highest at frontal midline electrodes in resting state, indicating that the frontal theta rhythm is also detectable outside task conditions. Since most studies investigating the relation between oscillatory activity and the BOLD signal used the resting state paradigm, we decided to follow this line of research.…”

A review of channel selection algorithms for EEG signal processing

“…A total of 19 channels were used for recording the data with a sampling rate of 256 Hz that was passed through a band-pass Butterworth filter with cutoff frequencies of 0.5 and 60 Hz. To increase the spatial resolution of the recorded data and decrease its dependence on the reference location, the authors used two techniques: Laplacian derivation [56][57][58][59] and common average reference (CAR) [55]. They used a model-based autoregressive technique to extract the features.…”