Localization of cortico-peripheral coherence with electroencephalography

Abstract

BACKGROUND: The analysis of coherent networks from continuous recordings of neural activity with functional MRI or magnetoencephalography has provided important new insights into brain physiology and pathology. Here we assess whether valid localizations of coherent cortical networks can also be obtained from high-resolution electroencephalography (EEG) recordings. METHODS: EEG was recorded from healthy subjects and from patients with ischemic brain lesions during a tonic hand muscle contraction task and during continuous visual stimulation with an alternating checkerboard. These tasks induce oscillations in the primary hand motor area or in the primary visual cortex, respectively, which are coherent with extracerebral signals (hand muscle electromyogram or visual stimulation frequency). Cortical oscillations were reconstructed with different inverse solutions and the coherence between oscillations at each cortical voxel and the extracerebral signals was calculated. Moreover, simulations of coherent point sources were performed. RESULTS: Cortico-muscular coherence was correctly localized to the primary hand motor area and the steady-state visual evoked potentials to the primary visual cortex in all subjects and patients. Sophisticated head models tended to yield better localization accuracy than a single sphere model. A Minimum Variance Beamformer (MVBF) provided more accurate and focal localizations of simulated point sources than an L 2 Minimum Norm (MN) inverse solution. In the real datasets, the MN maps had less localization error but were less focal than MVBF maps. CONCLUSIONS: EEG can localize coherent cortical networks with sufficient accuracy.

EEG abnormalities in psychopath and non-psychopath violent offenders

“…The use of individual anatomical MRI to calculate sources of localization eliminates these limitations and it contributes to increase the accuracy of LORETA localization as has been demonstrated by different researches. 52,53 LORETA is a technique that facilitates a deeper understanding of the neurological findings present in the EEG. 21 In general, LORETA helped to define the structures related to the increase of beta activity as a sign of a dysfunctional (hyperexcitability) neuronal state, probably secondary to central nervous system injury.…”

The behavioral significance of coherent resting-state oscillations after stroke

“…Source FC was calculated in Matlab (The MathWorks Inc., Natick, USA) with NUTMEG (http://nutmeg.berkeley.edu) (Dalal et al, 2011) and its FCM toolbox . The detailed analysis steps and their validation have been described previously .…”

“…It is particularly fruitful when FC is not calculated between sensor or electrode pairs, but between reconstructions of cortical oscillations obtained with inverse solutions. This approach allows for instance to localize the cortical generators of cortico-muscular interaction (Gross et al, 2001;Guggisberg et al, 2011;Schoffelen et al, 2008), as well as to reconstruct cortical network interactions. Initial direct comparisons between resting-state networks obtained with fMRI and networks reconstructed from MEG suggested a more lateralized configuration of MEG networks (de Pasquale et al, 2010), but this difference disappeared in studies controlling for distortions of MEG/EEG FC due to spatial leakage of the inverse solutions (Brookes et al, 2011a;Brookes et al, 2011b).…”

Intrinsic Coupling Modes in Source-Reconstructed Electroencephalography

“…The forward model was solved with an analytical solution using a 3-layer conductor model. Despite being somewhat simplified, this head model allows an accurate and rapid analytical solution comparable to boundary element head models (Guggisberg et al, 2011). To determine the seed regions, the source space was subdivided into 90 anatomically defined regions of interest according to the macroscopic anatomical parcellation of the MNI template using the Automated Anatomic Labeling map (Tzourio-Mazoyer et al, 2002), available from the MRIcro software (Rorden and Brett, 2000).…”