Electric Source Imaging in Frontal Lobe Epilepsy

To determine the validity of scalp-electroencephalography (EEG)-interictal spike (IIS) source localization in posterior cortex epilepsies (PCE). Eleven patients with drug-resistant PCE were studied with high-resolution EEG (HR-EEG) and stereoelectroencephalography (SEEG). Sixty-four scalp channels, a realistic head model, and different algorithms [multiple signal classification (MUSIC) and equivalent current dipoles] were used. Results were compared to intracerebral SEEG recordings. For SEEG, a semiautomatic detection of intracerebral IIS was used, allowing a classification of intracerebral IIS into one of three groups: Medial, lateral, and mediolateral. In the medial group (two patients), scalp-EEG IIS were usually absent for one patient whereas for the other, scalp-EEG was misleading. Indeed, scalp-EEG IIS had a posterior projection, predominantly contralateral to the source. In the lateral group (two patients), scalp-EEG IIS were subcontinuous and accurately localized. In the mediolateral group (seven patients), intracerebral interictal distribution was complex and bilateral for four of seven patients. Source localizations were able to determine only a part, whether lateral or medial, of the intracerebral interictal distribution. The accuracy of scalp-EEG IIS source localization is dependant on the type of intracerebral interictal distribution. In the most frequent type of PCE, patients proved to have a complex interictal distribution between both medial and lateral cortices, and source localizations always underestimated intracerebral IIS. In cases where intracranial sources were quite focal, surface EEG sources were localized with accuracy, even in medial occipital lobe structures.

SummaryObjectiveElectrical source imaging (ESI) is used increasingly to estimate the epileptogenic zone (EZ) in patients with epilepsy. Directed functional connectivity (DFC) coupled to ESI helps to better characterize epileptic networks, but studies on interictal activity have relied on high‐density recordings. We investigated the accuracy of ESI and DFC for localizing the EZ, based on low‐density clinical electroencephalography (EEG).MethodsWe selected patients with the following: (a) focal epilepsy, (b) interictal spikes on standard EEG, (c) either a focal structural lesion concordant with the electroclinical semiology or good postoperative outcome. In 34 patients (20 temporal lobe epilepsy [TLE], 14 extra‐TLE [ETLE]), we marked interictal spikes and estimated the cortical activity during each spike in 82 cortical regions using a patient‐specific head model and distributed linear inverse solution. DFC between brain regions was computed using Granger‐causal modeling followed by network topologic measures. The concordance with the presumed EZ at the sublobar level was computed using the epileptogenic lesion or the resected area in postoperative seizure‐free patients.ResultsESI, summed outflow, and efficiency were concordant with the presumed EZ in 76% of the patients, whereas the clustering coefficient and betweenness centrality were concordant in 70% of patients. There was no significant difference between ESI and connectivity measures. In all measures, patients with TLE had a significantly higher (P < 0.05) concordance with the presumed EZ than patients with with ETLE. The brain volume accepted for concordance was significantly larger in TLE.SignificanceESI and DFC derived from low‐density EEG can reliably estimate the EZ from interictal spikes. Connectivity measures were not superior to ESI for EZ localization during interictal spikes, but the current validation of the localization of connectivity measure is promising for other applications.

Event Abstract Back to Event Localization of interictal spikes and high frequency oscillations (HFO) using magnetoencephalography (MEG) Vahe Poghosyan1* 1 King Fahad Medical City, Department of Neurophysiology, National Neuroscience Institute, Saudi Arabia Epidemiological data show that about 40% of the patients with epilepsy are refractory to pharmacological treatment. In many such patients with focal epilepsy, an alternative therapeutic option of choice is the surgical resection of the epileptogenic zone. At present, a variety of diagnostic tools (e.g. analysis of seizure semiology, electrophysiological and neuroimaging tools, functional testing etc.) are used to define the different epilepsy-related cortical zones (symptomatogenic, irritative, seizure onset and functional deficit zones, and epileptogenic lesion), each of which indexes to a certain extent the location and boundaries of the epileptogenic zone. Recently, high frequency oscillations (HFO, 80 – 500 Hz) have been proposed as accurate biomarkers of the epileptogenic zone in intracranial electroencephalography recordings (Jacobs et al. 2012). Magnetoencephalography (MEG) substantially contributes to the pre-surgical evaluation of patients with focal epilepsy. Currently, its primary application is to localize the cortical sources of interictal spikes (irritative zone) as an estimate for the epileptogenic zone. Recent studies have shown that MEG can also be used to identify and localize sources of HFOs (Papadelis et al., 2009; Rampp et al., 2010). Accurate identification and localization of MEG HFOs can provide an important non-invasive biomarker for epileptogenicity. We have used several source localization methods to estimate and compare the sources of MEG interictal spikes and HFOs, and correlate them with the clinical information and post-surgical outcome. In this presentation, I will describe the results of this analysis and provide relevant recommendations. References Jacobs J., Staba R., Asano E., Otsubo H., Wu J.Y., Zijlmans M., Mohamed I., Kahane P., Dubeau F., Navarro V., and Gotman J. (2012). High-frequency oscillations (HFOs) in clinical epilepsy. Progress in neurobiology, 98: 302–315 Papadelis C., Poghosyan V., Fenwick P.B.C., and Ioannides A.A. (2009). MEG’s ability to localize accurately weak transient neural sources. Clinical Neurophysiology, 120: 1958–1970 Rampp S., Kaltenhäuser M., Weigel D., Buchfelder M., Blümcke I., Dörfler A., and Stefan, H. (2010). MEG correlates of epileptic high gamma oscillations in invasive EEG. Epilepsia, 51: 1638–1642. Keywords: Epilepsy, interictal epileptiform discharges, interictal spikes, Magnetoencephalography (MEG), high frequency oscillation Conference: SAN2016 Meeting, Corfu, Greece, 6 Oct - 9 Oct, 2016. Presentation Type: Oral Presentation in the Symposium Epilepsy and Sleep Topic: Symposium Epilepsy and Sleep Citation: Poghosyan V (2016). Localization of interictal spikes and high frequency oscillations (HFO) using magnetoencephalography (MEG). Conference Abstract: SAN2016 Meeting. doi: 10.3389/conf.fnhum.2016.220.00122 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 01 Aug 2016; Published Online: 01 Aug 2016. * Correspondence: Dr. Vahe Poghosyan, King Fahad Medical City, Department of Neurophysiology, National Neuroscience Institute, Riyadh, Saudi Arabia, vpoghosyan@kfmc.med.sa Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Vahe Poghosyan Google Vahe Poghosyan Google Scholar Vahe Poghosyan PubMed Vahe Poghosyan Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

High-density electroencephalography (hdEEG) is an emerging brain imaging technique that can be used to investigate fast dynamics of electrical activity in the healthy and the diseased human brain. Its applications are however currently limited by a number of methodological issues, among which the difficulty in obtaining accurate source localizations. In particular, these issues have so far prevented EEG studies from reporting brain networks similar to those previously detected by functional magnetic resonance imaging (fMRI). Here, we report for the first time a robust detection of brain networks from resting state (256-channel) hdEEG recordings. Specifically, we obtained 14 networks previously described in fMRI studies by means of realistic 12-layer head models and exact low-resolution brain electromagnetic tomography (eLORETA) source localization, together with independent component analysis (ICA) for functional connectivity analysis. Our analyses revealed three important methodological aspects. First, brain network reconstruction can be improved by performing source localization using the gray matter as source space, instead of the whole brain. Second, conducting EEG connectivity analyses in individual space rather than on concatenated datasets may be preferable, as it permits to incorporate realistic information on head modeling and electrode positioning. Third, the use of a wide frequency band leads to an unbiased and generally accurate reconstruction of several network maps, whereas filtering data in a narrow frequency band may enhance the detection of specific networks and penalize that of others. We hope that our methodological work will contribute to rise of hdEEG as a powerful tool for brain research. Hum Brain Mapp 38:4631-4643, 2017. © 2017 Wiley Periodicals, Inc.

Electromagnetic source localization in electroencephalography (EEG) and magnetoencephalography (MEG) allows finding the generators of transient interictal epileptiform discharges ('interictal spikes'). In intracerebral EEG (iEEG), oscillatory activity (above 30Hz) has also been shown to be a marker of neuronal dysfunction. Still, the difference between networks involved in transient and oscillatory activities remains largely unknown. Our goal was thus to extract and compare the networks involved in interictal oscillations and spikes, and to compare the non-invasive results to those obtained directly within the brain. In five patients with both MEG and iEEG recordings, we computed correlation graphs across regions, for (1) interictal spikes and (2) epileptic oscillations around 30Hz. We show that the corresponding networks can involve a widespread set of regions (average of 10 per patient), with only partial overlap (38% of the total number of regions in MEG, 50% in iEEG). The non-invasive results were concordant with intracerebral recordings (79% for the spikes and 50% for the oscillations). We compared our interictal results to iEEG ictal data. The regions labeled as seizure onset zone (SOZ) belonged to interictal networks in a large proportion of cases: 75% (resp. 58%) for spikes and 58% (resp. 33%) for oscillations in iEEG (resp. MEG). A subset of SOZ regions were detected by one type of discharges but not the other (25% for spikes and 8% for oscillations). Our study suggests that spike and oscillatory activities involve overlapping but distinct networks, and are complementary for presurgical mapping.

Electrical, molecular and behavioral effects of interictal spiking in the rat

The present study aimed to test the feasibility of a novel neuroimaging technique, that is, variation-based sparse cortical current density (VB-SCCD) imaging algorithm, in noninvasively estimating location and extent of epileptic sources from interictal magnetoencephalography (MEG) data. A total of 108 interictal spikes from 3 partial epilepsy patients were selected to perform VB-SCCD source analysis. Cortical sources were identified at spike peaks, rising phases, and entire spikes, respectively, from all interictal spikes in each patient, to estimate source locations and extents, and validated using presurgical evaluation data. Other source analysis methods, that is, minimum norm estimate and sparse source imaging were also performed for comparison. Cortical sources reconstructed by VB-SCCD that are consistent with clinical presurgical evaluation outcomes have detection rates of 65.8% at spike peaks, 85.1% during rising phases, and 92.6% in entire spikes. Stable spatiotemporal patterns of reconstructed cortical sources were also obtained using VB-SCCD, which provide more insights about the formation and propagation of interictal epileptic activity. Our present results suggest that the VB-SCCD technique has the capability in estimating location and extent of epileptic sources of interictal spikes and is promising to become a valuable noninvasive tool in assisting presurgical planning for partial epilepsy patients.

Newton's method is one of the commonly used methods for acoustic emission partial discharge (AEPD) source localization in power transformers. The major problem in the AEPD source localization is the difficulty in accurately measuring the signal arrival time from the source to the multiple sensors. The exact instant at which the partial discharge (PD) occurs is not known. Therefore, instead of the absolute time, the time-delay in signal reception of each sensor with respect to the sensor nearest to the PD source is estimated. In the present study the effect of time-delay error on the accuracy of the PD source localization is analyzed through numerical experimentations. The solution of the Newtons's method in turn depends on the choice of the initial guess. Hence, different initial guesses are selected for Newton's method randomly. For a fixed set of coordinates for the four sensors and the PD source positions, the time-delays are theoretically calculated. The error is systematically increased in the calculated time-delay to form different groups of time-delays. The PD source is localized using each initial guess for all the groups of time-delays to analyze the effect of error in time-delay on accuracy of PD source localization. The error in time-delay greatly affects the AEPD source localization. Moreover, if Newton's method with a bad initial guess is used then the errors in AEPD source localizations are not systematic.

The view of brain activity is determined by the method used, for example, conventional scalp electroencephalography (EEG) provides a blurred vision, subdural invasive electrodes a view like a magnifying lens, and intracerebral electrodes, a tunnel view. The development of sophisticated algorithms for source localization of magnetoencephalography (MEG) and EEG provides a new approach to recognize and localize source attributes. Intracellular and extracellular currents are the sources of electric/magnetic fields. The intracellular current (primary current) is surrounded by a magnetic field, whereas extracellular currents are due to passive volume conduction induced by the electric field. EEG and MEG are complementary recording techniques because both methods have certain advantages and disadvantages. MEG has some favorable characteristics for source localizations; for example, secondary volume currents are in general not so important and the modeling of the conductivities of the different brain tissues (gray–white matter, skull, scalp) do not play a major role. Modern MEG–multichannel systems with up to 300 channels provide a fast and contact-less measurement of the predominantly tangential components of the brain activity. On the other hand, EEG records both radial and tangential components, but secondary volume conduction plays a significant role and must be considered adequately by a realistic head model (Boundary Element Model, Finite Element Model). For source localization, special electroanatomic and physical characteristics have to be considered, because the solution of the inverse problem is not unique. Therefore, additional assumptions have to be made for the source model and the allowed source space. Very often the equivalent current dipole (ECD), which describes the center of gravity of the electrical activity, is used for the description of focal epileptic activity. This model provides in many cases a good estimation of the underlying source but a careful evaluation of the results with respect to stability and reproducibility have to be considered. In addition to the ECD, more elaborate source models, for example, multiple dipoles, beam former, or current density analysis can be used. In addition, the coherence analysis provides a better understanding of the brain dynamics. As in all functional imaging methods, the extension of activity and noise artifacts require special consideration. The depth resolution of MEG recordings depends on technical conditions such as the use of gradiometers or magnetometers. In addition to scalp EEG/MEG recordings, also simultaneously recorded electrocorticography (ECoG) and MEG recordings can be performed offering a better three-dimensional view of deeper localized epileptic activities. Source localization aims to detect focal epileptic activity within the interictal or even ictal onset of the epileptic network. In addition to the localization of epileptic activity, its spatial relationship to functional important areas (e.g., motor/speech) is a major task with regard to surgical planning. For this task a multimodal coregistration of MEG/EEG and functional magnetic resonance imaging (fMRI) as well as tractography by means of diffusion tensor imaging (DTI) can be used (Fig. 1). (A) Streamtube visualization of the right optic radiation based on diffusion tensor imaging (DTI). (B) For navigation, a three-dimensional object representing the optic radiation (wrapping the individual fibers) and two distinct magnetic source imaging (MSI) foci (red) are generated. (C) Relation of optic radiation (visualized as streamlines) to MSI foci. (D–F) Sagittal/coronal (axial view of T1-weighted images with registered DTI. Localization of focal epileptic activity is below the optic tract. (Stefan et al., 2006). The sensitivity of MEG for specific epileptic activity is approximately 70%. The MEG, compared to video-EEG monitoring and MRI, provided additional information during presurgical evaluation in 35% (Stefan et al., 2003). In patients, for whom interictal and focal epileptic seizures during long-term scalp EEG recordings were inconclusive (25 of 105 patients) MEG was able to localize in the lobe, which has been resected later on, in 44%. All these patients had an improvement of seizure frequency postoperatively (six patients were seizure-free; five patients had a reduction >50%) (Paulini et al., 2007). When comparing noninvasive magnetic source imaging and invasive seizure-onset localization, a positive predictive value of magnetic source imaging (MSI) for seizure localization was 82–90% (Knowlton et al., 2006). MEG predicted outcome following surgery for intractable epilepsy in children with normal or nonfocal MRI findings (RamachandranNair et al., 2007). There are special situations during presurgical evaluation in which MSI is helpful: for example, patients after surgery, multiple stage surgery, patients with missing cooperation for prolonged invasive recordings or contraindications for invasive recordings. Furthermore, presurgical invasive recordings can be guided by MEG and in some cases might be even omitted. The combined multimodal use of MEG/EEG, MRI, fMRI, single photon emission computed tomography (SPECT), and functional neuronavigation can be used for functional preservation in epilepsy surgery (Ganslandt et al., 1999). The author has no conflict of interest to disclose.

Clinical Neurophysiology: EEG–Video Monitoring

Altered basal ganglia-cortical functional connections in frontal lobe epilepsy: A resting-state fMRI study

ID 168 – Source localization of ictal epileptic activity based on high density scalp EEG data

Non-invasive epileptic source localization techniques, relying on interictal activity in the EEG and mainly motivated by the need for presurgical localization of the epileptic focus in intractable focal epilepsy, have been widely studied and validated (Blume et al., 2001; Ebersole, 2000; Gavaret et al., 2009; Lantz et al., 2003; Michel et al., 2004; Zumsteg et al., 2005, 2006). Source localization methods most often utilize electric source imaging (ESI), a technique which applies various mathematical algorithms and constraining neurophysiological hypotheses on scalp electroencephalographic (EEG) recordings in order to reconstruct the three dimensional brain electrical activity (reviewed in Michel et al., 2004). Correlation of such modeling with actual intra-cerebral recordings is not always straightforward and some focal deep sources do not seem to have surface representation sufficient for stable modeling (Merlet & Gotman, 2001). Advantage may also be taken of extracranial magnetic fields (MEG) which like scalp electric potentials are due to current density distribution that arises from post-synaptic processes of underlying neuronal populations. The MEG forms the basis for the various versions of low resolution brain electromagnetic tomography (LORETA), which have been advanced to tackle the solution of the inverse problem (the 3D reconstruction of electric neuronal activity based on extracranial measurements) (Pascual-Marqui, 2002).

Epileptic networks are characterized by two outputs: brief interictal spikes and rarer, more prolonged seizures. Although either output state is readily modeled in silico and induced experimentally, the transition mechanisms are unknown, in part because no models exhibit both output states spontaneously. In silico small-world neural networks were built using single-compartment neurons whose physiological parameters were derived from dual whole-cell recordings of pyramidal cells in organotypic hippocampal slice cultures that were generating spontaneous seizure-like activity. In silico, neurons were connected by abundant local synapses and rare long-distance synapses. Activity-dependent synaptic depression and gradual recovery delimited synchronous activity. Full synaptic recovery engendered interictal population spikes that spread via long-distance synapses. When synaptic recovery was incomplete, postsynaptic neurons required coincident activation of multiple presynaptic terminals to reach firing threshold. Only local connections were sufficiently dense to spread activity under these conditions. This coalesced network activity into traveling waves whose velocity varied with synaptic recovery. Seizures were comprised of sustained traveling waves that were similar to those recorded during experimental and human neocortical seizures. Sustained traveling waves occurred only when wave velocity, network dimensions, and the rate of synaptic recovery enabled wave reentry into previously depressed areas at precisely ictogenic levels of synaptic recovery. Wide-field, cellular-resolution GCamP7b calcium imaging demonstrated similar initial patterns of activation in the hippocampus, although the anatomical distribution of traveling waves of synaptic activation was altered by the pattern of synaptic connectivity in the organotypic hippocampal cultures.SIGNIFICANCE STATEMENT When computerized distributed neural network models are required to generate both features of epileptic networks (i.e., spontaneous interictal population spikes and seizures), the network structure is substantially constrained. These constraints provide important new hypotheses regarding the nature of epileptic networks and mechanisms of seizure onset.

Objective: Magnetoencephalography source imaging (MSI) of interictal epileptiform discharges (IED) is a useful presurgical tool in the evaluation of drug-resistant frontal lobe epilepsy (FLE) patients. Yet, failures in MSI can arise related to artifacts and to interference of background activity. Independent component analysis (ICA) is a popular denoising procedure but its clinical application remains challenging, as the selection of multiple independent components (IC) is controversial, operator dependent, and time consuming. We evaluated whether selecting only one IC of interest based on its similarity with the average IED field improves MSI in FLE.Methods: MSI was performed with the equivalent current dipole (ECD) technique and two distributed magnetic source imaging (dMSI) approaches: minimum norm estimate (MNE) and coherent Maximum Entropy on the Mean (cMEM). MSI accuracy was evaluated under three conditions: (1) ICA of continuous data (Cont_ICA), (2) ICA at the time of IED (IED_ICA), and (3) without ICA (No_ICA). Localization performance was quantitatively measured as actual distance of the source maximum in relation to the focus (Dmin), and spatial dispersion (SD) for dMSI.Results: After ICA, ECD Dmin did not change significantly (p > 0.200). For both dMSI techniques, ICA application worsened the source localization accuracy. We observed a worsening of both MNE Dmin (p < 0.05, consistently) and MNE SD (p < 0.001, consistently) for both ICA approaches. A similar behaviour was observed for cMEM, for which, however, Cont_ICA seemed less detrimental.Conclusion: We demonstrated that a simplified ICA approach selecting one IC of interest in combination with distributed magnetic source imaging can be detrimental. More complex approaches may provide better results but would be rather difficult to apply in real-world clinical setting. In a broader perspective, caution should be taken in applying ICA for source localization of interictal activity. To ensure optimal and useful results, effort should focus on acquiring good quality data, minimizing artifacts, and determining optimal candidacy for MEG, rather than counting on data cleaning techniques.