Methods for Examining Electrophysiological Coherence in Epileptic Networks

Jasmine Song,Chelsea Mattson,Don M Tucker,Phan Luu,Jidong Hou,Tara Gilbert,Mark D Holmes

doi:10.3389/fneur.2013.00055

Abstract

Epilepsy may reflect a focal abnormality of cerebral tissue, but the generation of seizures typically involves propagation of abnormal activity through cerebral networks. We examined epileptiform discharges (spikes) with dense array electroencephalography (dEEG) in five patients to search for the possible engagement of pathological networks. Source analysis was conducted with individual electrical head models for each patient, including sensor position measurement for registration with MRI with geodesic photogrammetry; tissue segmentation and skull conductivity modeling with an atlas skull warped to each patient’s MRI; cortical surface extraction and tessellation into 1 cm2 equivalent dipole patches; inverse source estimation with either minimum norm or cortical surface Laplacian constraints; and spectral coherence computed among equivalent dipoles aggregated within Brodmann areas with 1 Hz resolution from 1 to 70 Hz. These analyses revealed characteristic source coherence patterns in each patient during the pre-spike, spike, and post-spike intervals. For one patient with both spikes and seizure onset localized to a single temporal lobe, we observed a cluster of apparently abnormal coherences over the involved temporal lobe. For the other patients, there were apparently characteristic coherence patterns associated with the discharges, and in some cases these appeared to reflect abnormal temporal lobe synchronization, but the coherence patterns for these patients were not easily related to an unequivocal epileptogenic zone. In contrast, simple localization of the site of onset of the spike discharge, and/or the site of onset of the seizure, with non-invasive 256 dEEG was useful in predicting the characteristic site of seizure onset for those cases that were verified by intracranial EEG and/or by surgical outcome.

Highlights

There is increasing evidence in the recent literature that functional networks of the human brain can be identified through correlation analysis of fluctuations in hemodynamic functional magnetic resonance imaging measures (Fox et al, 2005; Fair et al, 2007, 2008; Van Dijk et al, 2010)
One typical spike cluster is described for each patient; the set of spike clusters obtained for that patient and differences in coherence patterns for the other clusters is summarized in each case
Coherence analysis: cortical patch tessellation resulted in 2240 patch dipoles for Patient 1 which were classified into 82 Brodmann areas (41 per hemisphere)

Summary

Introduction

There is increasing evidence in the recent literature that functional networks of the human brain can be identified through correlation analysis of fluctuations in hemodynamic functional magnetic resonance imaging (fMRI) measures (Fox et al, 2005; Fair et al, 2007, 2008; Van Dijk et al, 2010). In a recent study from our laboratory (Ramon et al, 2008; Ramon and Holmes, 2012), non-linear dynamic measures of local correlation among the 256 dense array electroencephalography (dEEG) channels showed abnormally high levels of synchronization over cortical regions that later prove to be seizure onset zones. Because these analyses were conducted with the head surface (scalp) dEEG, they are less precise than synchronization analysis performed with cortical source analysis, assuming, that the cortical source analysis is accurate. The goal was to apply the synchronization analysis (spectral coherence) to the waveforms of the cortical sources directly

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