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. 2016 Sep;37(9):3250-61.
doi: 10.1002/hbm.23238. Epub 2016 May 24.

Magnetoencephalographic signatures of insular epileptic spikes based on functional connectivity

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Magnetoencephalographic signatures of insular epileptic spikes based on functional connectivity

Younes Zerouali et al. Hum Brain Mapp. 2016 Sep.

Abstract

Failure to recognize insular cortex seizures has recently been identified as a cause of epilepsy surgeries targeting the temporal, parietal, or frontal lobe. Such failures are partly due to the fact that current noninvasive localization techniques fare poorly in recognizing insular epileptic foci. Our group recently demonstrated that magnetoencephalography (MEG) is sensitive to epileptiform spikes generated by the insula. In this study, we assessed the potential of distributed source imaging and functional connectivity analyses to distinguish insular networks underlying the generation of spikes. Nineteen patients with operculo-insular epilepsy were investigated. Each patient underwent MEG as well as T1-weighted magnetic resonance imaging (MRI) as part of their standard presurgical evaluation. Cortical sources of MEG spikes were reconstructed with the maximum entropy on the mean algorithm, and their time courses served to analyze source functional connectivity. The results indicate that the anterior and posterior subregions of the insula have specific patterns of functional connectivity mainly involving frontal and parietal regions, respectively. In addition, while their connectivity patterns are qualitatively similar during rest and during spikes, couplings within these networks are much stronger during spikes. These results show that MEG can establish functional connectivity-based signatures that could help in the diagnosis of different subtypes of insular cortex epilepsy. Hum Brain Mapp 37:3250-3261, 2016. © 2016 Wiley Periodicals, Inc.

Keywords: brain disorders; brain imaging; cortical phase synchronization; epilepsies; nonparametric statistics; partial.

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Figures

Figure 1
Figure 1
Representation of the spatial distribution of analyzed interictal insular spikes labeled with sECD for further analysis. Each spike is represented by a dot, the color of which indicates if it is labeled as an anterior (blue), posterior (green), or inferior (red) insular spike. Left panel: right hemisphere, right panel: left hemisphere.
Figure 2
Figure 2
FC of insular subregions in the beta band (12–30 Hz) during interictal spikes. Each insular subregion is represented in 3 panels (left, top, and right views), with insular seeds appearing in white. Top row: anterior subregion; middle row: posterior subregion; bottom row: inferior subregion. The color scale encodes the strength of coupling between insular seeds and the rest of the cortex, after statistical thresholding.
Figure 3
Figure 3
FC of insular subregions in the beta band (12–30 Hz) during rest. Each insular subregion is represented in 3 panels (left, top, and right views), with the insular seeds appearing in white.
Figure 4
Figure 4
Comparison of unthresholded coupling strengths within insular connectivity subnetworks observed during interictal spikes in the beta band. Significance levels were Bonferroni‐corrected for multiple comparisons.
Figure 5
Figure 5
FC of insular subregions in the beta band (12–30 Hz) during shuffled spike epochs. Shuffling was done at the sensor level to disrupt spatial structure of the data.
Figure 6
Figure 6
Propagation patterns observed at the scalp level of interictal spikes generated by (a) anterior, (b) posterior, and (c) inferior subregions of the insula. Left panel: left insula; right panel: right insula. The color scale encodes propagation rank and is scaled to the local maxima and minima of each map.

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