Comparison of Free Distribution Software for EEG Focal Epileptic Source Localization

Ossa, Alexander; Borrego, Camilo; Trujillo, Mario F.; López, José David

doi:10.1007/978-3-319-18914-7_39

Cited by 1 publication

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“…Compared to the more traditional approaches, where the sources are typically estimated that correspond to the spike peak, or to 50% of the spike peak during the rising phase of the spike ( Boon et al, 1997a , Boon et al, 1999a , Brodbeck et al, 2011 , Birot et al, 2014 ), the choice of the time epoch in order to localize the origin of the activity using the MSVP method is not clear. In the Ossa et al (2015) study, the authors already suggested to use the approach by limiting the inversion procedure to a specific time epoch before the spike. In this study, three different time epochs were chosen for inversion: (i) a window starting 50 ms before the spike peak and ending at 50% of the spike peak during the rising phase of the spike, (ii) a window starting 50 ms before the spike peak and ending at the spike peak and (iii) a window starting 50 ms before the spike peak and ending 230 ms after the spike peak.…”

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confidence: 99%

Electrical source imaging of interictal spikes using multiple sparse volumetric priors for presurgical epileptogenic focus localization

Strobbe

Carrette

López

et al. 2016

NeuroImage: Clinical

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Electrical source imaging of interictal spikes observed in EEG recordings of patients with refractory epilepsy provides useful information to localize the epileptogenic focus during the presurgical evaluation. However, the selection of the time points or time epochs of the spikes in order to estimate the origin of the activity remains a challenge. In this study, we consider a Bayesian EEG source imaging technique for distributed sources, i.e. the multiple volumetric sparse priors (MSVP) approach. The approach allows to estimate the time courses of the intensity of the sources corresponding with a specific time epoch of the spike. Based on presurgical averaged interictal spikes in six patients who were successfully treated with surgery, we estimated the time courses of the source intensities for three different time epochs: (i) an epoch starting 50 ms before the spike peak and ending at 50% of the spike peak during the rising phase of the spike, (ii) an epoch starting 50 ms before the spike peak and ending at the spike peak and (iii) an epoch containing the full spike time period starting 50 ms before the spike peak and ending 230 ms after the spike peak. To identify the primary source of the spike activity, the source with the maximum energy from 50 ms before the spike peak till 50% of the spike peak was subsequently selected for each of the time windows. For comparison, the activity at the spike peaks and at 50% of the peaks was localized using the LORETA inversion technique and an ECD approach. Both patient-specific spherical forward models and patient-specific 5-layered finite difference models were considered to evaluate the influence of the forward model. Based on the resected zones in each of the patients, extracted from post-operative MR images, we compared the distances to the resection border of the estimated activity. Using the spherical models, the distances to the resection border for the MSVP approach and each of the different time epochs were in the same range as the LORETA and ECD techniques. We found distances smaller than 23 mm, with robust results for all the patients. For the finite difference models, we found that the distances to the resection border for the MSVP inversions of the full spike time epochs were generally smaller compared to the MSVP inversions of the time epochs before the spike peak. The results also suggest that the inversions using the finite difference models resulted in slightly smaller distances to the resection border compared to the spherical models. The results we obtained are promising because the MSVP approach allows to study the network of the estimated source-intensities and allows to characterize the spatial extent of the underlying sources.

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