Reliability of dipole models of epileptic spikes

Technical Considerations in EEG Source Imaging

SUMMARY

EEG source imaging is an established technique for identifying the origin of interictal and ictal epileptiform discharges in patients with epilepsy, and it is an important tool in neurophysiology research. Accurate and reliable EEG source imaging requires appropriate choices of how the head, skull, and scalp are modeled, and understanding of the different approaches to modeling is important to guide these choices. Similarly, numerous different approaches to modeling the electrical sources within the brain exist, and appropriate understanding of the strengths and limitations of each are essential to obtaining accurate, reliable, and interpretable solutions. This review aims to describe the essential theoretical basis for these head and source models while also discussing the practical implications of each in clinical or research applications.

Intracerebral Correlates of Scalp EEG Ictal Discharges Based on Simultaneous Stereo-EEG Recordings

BACKGROUND AND OBJECTIVES

It remains unknown to what extent ictal scalp EEG can accurately predict the localization of the intracerebral seizure onset in presurgical evaluation of drug-resistant epilepsies. In this study, we aimed to define homogeneous ictal scalp EEG profiles (based on their first ictal abnormality) and assess their localizing value using simultaneously recorded scalp EEG and stereo-EEG.

METHODS

We retrospectively included consecutive patients with drug-resistant focal epilepsy who had simultaneous stereo-EEG and scalp EEG recordings of at least 1 seizure in the epileptology unit in Nancy, France. We analyzed 1 seizure per patient and used hierarchical cluster analysis to group similar seizure profiles on scalp EEG and then performed a descriptive analysis of their intracerebral correlates.

RESULTS

We enrolled 129 patients in this study. The hierarchical cluster analysis showed 6 profiles on scalp EEG first modification. None were specific to a single intracerebral localization. The "normal EEG" and "blurred EEG" clusters (early muscle artifacts) comprised only 5 patients each and corresponded to no preferential intracerebral localization. The "temporal discharge" cluster (n = 46) was characterized by theta or delta discharges on ipsilateral anterior temporal scalp electrodes and corresponded to a preferential mesial temporal intracerebral localization. The "posterior discharge" cluster (n = 42) was characterized by posterior ipsilateral or contralateral rhythmic alpha discharges or slow waves on scalp and corresponded to a preferential temporal localization. However, this profile was the statistically most frequent scalp EEG correlate of occipital and parietal seizures. The "diffuse suppression" cluster (n = 9) was characterized by a bilateral and diffuse background activity suppression on scalp and corresponded to mesial, and particularly insulo-opercular, localization. Finally, the "frontal discharge" cluster (n = 22) was characterized by bilateral frontal rhythmic fast activity or preictal spike on scalp and corresponded to preferential ventrodorsal frontal intracerebral localizations.

DISCUSSION

The hierarchical cluster analysis identified 6 seizure profiles regarding the first abnormality on scalp EEG. None of them were specific of a single intracerebral localization. Nevertheless, the strong relationships between the "temporal," "frontal," "diffuse suppression," and "posterior" profiles and intracerebral discharge localizations may contribute to hierarchize hypotheses derived from ictal scalp EEG analysis regarding intracerebral seizure onset.

Neurophysiology, Neuropsychology, and Epilepsy, in 2022: Hills We Have Climbed and Hills Ahead. Neurophysiology in epilepsy

Since the discovery of the human electroencephalogram (EEG), neurophysiology techniques have become indispensable tools in our armamentarium to localize epileptic seizures. New signal analysis techniques and the prospects of artificial intelligence and big data will offer unprecedented opportunities to further advance the field in the near future, ultimately resulting in improved quality of life for many patients with drug-resistant epilepsy. This article summarizes selected presentations from Day 1 of the two-day symposium "Neurophysiology, Neuropsychology, Epilepsy, 2022: Hills We Have Climbed and the Hills Ahead". Day 1 was dedicated to highlighting and honoring the work of Dr. Jean Gotman, a pioneer in EEG, intracranial EEG, simultaneous EEG/ functional magnetic resonance imaging, and signal analysis of epilepsy. The program focused on two main research directions of Dr. Gotman, and was dedicated to "High-frequency oscillations, a new biomarker of epilepsy" and "Probing the epileptic focus from inside and outside". All talks were presented by colleagues and former trainees of Dr. Gotman. The extended summaries provide an overview of historical and current work in the neurophysiology of epilepsy with emphasis on novel EEG biomarkers of epilepsy and source imaging and concluded with an outlook on the future of epilepsy research, and what is needed to bring the field to the next level.

Beamforming Seizures from the Temporal Lobe Using Magnetoencephalography

BACKGROUND

Surgical treatment of drug-resistant temporal lobe epilepsy (TLE) depends on proper identification of the seizure onset zone (SOZ) and differentiation of mesial, temporolimbic seizure onsets from temporal neocortical seizure onsets. Noninvasive source imaging using electroencephalography (EEG) and magnetoencephalography (MEG) can provide accurate information on interictal spike localization; however, EEG and MEG have low sensitivity for epileptiform activity restricted to deep temporolimbic structures. Moreover, in mesial temporal lobe epilepsy (MTLE), interictal spikes frequently arise in neocortical foci distant from the SOZ, rendering interictal spike localization potentially misleading for presurgical planning.

METHODS

In this study, we used two different beamformer techniques applied to the MEG signal of ictal events acquired during EEG-MEG recordings in six patients with TLE (three neocortical, three MTLE) in whom the ictal source localization results could be compared to ground truth SOZ localizations determined from intracranial EEG and/or clinical, neuroimaging, and postsurgical outcome evidence.

RESULTS

Beamformer analysis proved to be highly accurate in all cases and was able to identify focal SOZs in mesial, temporolimbic structures. In three patients, interictal spikes were absent, too complex for dipole modeling, or localized to anterolateral temporal neocortex distant to a mesial temporal SOZ, and thus unhelpful in presurgical investigation.

CONCLUSIONS

MEG beamformer source reconstruction is suitable for analysis of ictal events in TLE and can complement or supersede the traditional analysis of interictal spikes. The method outlined is applicable to any type of epileptiform event, expanding the information value of MEG and broadening its utility for presurgical recording in epilepsy.

Manifestation of Hippocampal Interictal Discharges on Clinical Scalp EEG Recordings

PURPOSE

Epileptiform activity limited to deep sources such as the hippocampus currently lacks reliable scalp correlates. Recent studies, however, have found that a subset of hippocampal interictal discharges may be associated with visible scalp signals, suggesting that some types of hippocampal activity may be monitored noninvasively. The purpose of this study is to characterize the relationship between these scalp waveforms and the underlying intracranial activity.

METHODS

Paired intracranial and scalp EEG recordings obtained from 16 patients were used to identify hippocampal interictal discharges. Discharges were grouped by waveform shape, and spike-triggered averages of the intracranial and scalp signals were calculated for each group. Cross-correlation of intracranial and scalp spike-triggered averages was used to determine their temporal relationship, and topographic maps of the scalp were generated for each group.

RESULTS

Cross-correlation of intracranial and scalp correlates resulted in two classes of scalp waveforms-those with and without time delays from the associated hippocampal discharges. Scalp signals with no delay showed topographies with a broad field with higher amplitudes on the side ipsilateral to the discharges and a left-right flip in polarity-observations consistent with the volume conduction of a single unilateral deep source. In contrast, scalp correlates with time lags showed rotational dynamics, suggesting synaptic propagation mechanisms.

CONCLUSIONS

The temporal relationship between the intracranial and scalp signals suggests that both volume conduction and synaptic propagation contribute to these scalp manifestations. Furthermore, the topographic evolution of these scalp waveforms may be used to distinguish spikes that are limited to the hippocampus from those that travel to or engage other brain areas.

Comparison of beamformer and ICA for dynamic connectivity analysis: A simultaneous MEG-SEEG study

Magnetoencephalography (MEG) is a powerful tool for estimating brain connectivity with both good spatial and temporal resolution. It is particularly helpful in epilepsy to characterize non-invasively the epileptic networks. However, using MEG to map brain networks requires solving a difficult inverse problem that introduces uncertainty in the activity localization and connectivity measures. Our goal here was to compare independent component analysis (ICA) followed by dipole source localization and the linearly constrained minimum-variance beamformer (LCMV-BF) for characterizing regions with interictal epileptic activity and their dynamic connectivity. After a simulation study, we compared ICA and LCMV-BF results with intracerebral EEG (stereotaxic EEG, SEEG) recorded simultaneously in 8 epileptic patients, which provide a unique 'ground truth' to which non-invasive results can be confronted. We compared the signal time courses extracted applying ICA and LCMV-BF on MEG data to that of SEEG, both for the actual signals and the dynamic connectivity computed using cross-correlation (evolution of links in time). With our simulations, we illustrated the different effect of the temporal and spatial correlation among sources on the two methods. While ICA was more affected by the temporal correlation but robust against spatial configurations, LCMV-BF showed opposite behavior. Moreover, ICA seems more suited to retrieve the simulated networks. In case of real patient data, good MEG/SEEG correlation and good localization were obtained in 6 out of 8 patients. In 4 of them ICA had the best performance (higher correlation, lower localization distance). In terms of dynamic connectivity, the evolution in time of the cross-correlation links could be retrieved in 5 patients out of 6, however, with more variable results in terms of correlation and distance. In two patients LCMV-BF had better results than ICA. In one patient the two methods showed equally good outcomes, and in the remaining two patients ICA performed best. In conclusion, our results obtained by exploiting simultaneous MEG/SEEG recordings suggest that ICA and LCMV-BF have complementary qualities for retrieving the dynamics of interictal sources and their network interactions.

Validation of semi-automated anatomically labeled SEEG contacts in a brain atlas for mapping connectivity in focal epilepsy

OBJECTIVE

Stereotactic electroencephalography (SEEG) has been widely used to explore the epileptic network and localize the epileptic zone in patients with medically intractable epilepsy. Accurate anatomical labeling of SEEG electrode contacts is critically important for correctly interpreting epileptic activity. We present a method for automatically assigning anatomical labels to SEEG electrode contacts using a 3D-segmented cortex and coregistered postoperative CT images.

METHOD

Stereotactic electroencephalography electrode contacts were spatially localized relative to the brain volume using a standard clinical procedure. Each contact was then assigned an anatomical label by clinical epilepsy fellows. Separately, each contact was automatically labeled by coregistering the subject's MRI to the USCBrain atlas using the BrainSuite software and assigning labels from the atlas based on contact locations. The results of both labeling methods were then compared, and a subsequent vetting of the anatomical labels was performed by expert review.

RESULTS

Anatomical labeling agreement between the two methods for over 17 000 SEEG contacts was 82%. This agreement was consistent in patients with and without previous surgery (P = .852). Expert review of contacts in disagreement between the two methods resulted in agreement with the atlas based over manual labels in 48% of cases, agreement with manual over atlas-based labels in 36% of cases, and disagreement with both methods in 16% of cases. Labels deemed incorrect by the expert review were then categorized as either in a region directly adjacent to the correct label or as a gross error, revealing a lower likelihood of gross error from the automated method.

SIGNIFICANCE

The method for semi-automated atlas-based anatomical labeling we describe here demonstrates potential to assist clinical workflow by reducing both analysis time and the likelihood of gross anatomical error. Additionally, it provides a convenient means of intersubject analysis by standardizing the anatomical labels applied to SEEG contact locations across subjects.

Towards the Automatic Localization of the Irritative Zone Through Magnetic Source Imaging

The present work aims at validating a Bayesian multi-dipole modeling algorithm (SESAME) in the clinical scenario consisting of localizing the generators of single interictal epileptiform discharges from resting state magnetoencephalographic recordings. We use the results of Equivalent Current Dipole fitting, performed by an expert user, as a benchmark, and compare the results of SESAME with those of two widely used source localization methods, RAP-MUSIC and wMNE. In addition, we investigate the relation between post-surgical outcome and concordance of the surgical plan with the cerebral lobes singled out by the methods. Unlike dipole fitting, the tested algorithms do not rely on any subjective channel selection and thus contribute towards making source localization more unbiased and automatic. We show that the two dipolar methods, SESAME and RAP-MUSIC, generally agree with dipole fitting in terms of identified cerebral lobes and that the results of the former are closer to the fitted equivalent current dipoles than those of the latter. In addition, for all the tested methods and particularly for SESAME, concordance with surgical plan is a good predictor of seizure freedom while discordance is not a good predictor of poor post-surgical outcome. The results suggest that the dipolar methods, especially SESAME, represent a reliable and more objective alternative to manual dipole fitting for clinical applications in the field of epilepsy surgery.

Enhanced Fast-VESTAL for Magnetoencephalography Source Imaging: From Theory to Clinical Application in Epilepsy

A novel magnetoencephalography source imaging approach called Fast Vector-based Spatio-Temporal Analysis (Fast-VESTAL) has been successfully applied in creating source images from evoked and resting-state data from both healthy subjects and individuals with neurological and/or psychiatric disorders, but its reconstructed source images may show false-positive activations, especially under low signal-to-noise ratio conditions. Here, to effectively reduce false-positive artifacts, we introduced an enhanced Fast-VESTAL (eFast-VESTAL) approach that adopts generalized second-order cone programming. We compared the spatiotemporal characteristics of the eFast-VESTAL approach to those of the popular distributed source approaches (e.g., the minimum L2-norm/ mixed-norm methods) using computer simulations and auditory experiments. More importantly, we applied eFast-VESTAL to the presurgical evaluation of epilepsy. Our results demonstrated that eFast-VESTAL exhibited a lower dipole localization error and/or a higher correlation coefficient (CC) between the estimated source time series and ground truth under various conditions of source waveforms. Experimentally, eFast-VESTAL displayed more focal activation maps and a higher CC between the raw and predicted sensor data in response to auditory stimulation. Notably, eFast-VESTAL was the most accurate method for noninvasively detecting the epileptic zones determined using more invasive stereo-electroencephalography in the comparison.

Effects of Independent Component Analysis on Magnetoencephalography Source Localization in Pre-surgical Frontal Lobe Epilepsy Patients

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.

Electrophysiological Brain Connectivity: Theory and Implementation

We review the theory and algorithms of electrophysiological brain connectivity analysis. This tutorial is aimed at providing an introduction to brain functional connectivity from electrophysiological signals, including electroencephalography (EEG), magnetoencephalography (MEG), electrocorticography (ECoG), stereoelectroencephalography (SEEG). Various connectivity estimators are discussed, and algorithms introduced. Important issues for estimating and mapping brain functional connectivity with electrophysiology are discussed.

Focal epilepsies and focal disorders

Electroencephalographic (EEG) investigations are crucial in the diagnosis and management of patients with focal epilepsies. EEG may reveal different interictal epileptiform discharges (IEDs: abnormal spikes, sharp waves). The EEG visibility of a spike depends on the surface area of cortex involved (>10cm²) and the brain localization of cortical generators. Regions generating IEDs (defining the "irritative zone") are not necessarily equivalent to the seizure onset zone. Focal seizures are dynamic processes originating from one or several brain regions (that generate fast oscillations and are called the epileptogenic zone) before spreading to other structures (that generate lower frequency oscillations and are called the propagation zone). Several factors limit the expression of seizures on scalp EEG, such as the area involved, degree of synchronization, and depth of the cortical generators. Different scalp EEG seizure onset patterns may be observed: fast discharge, background flattening, rhythmic spikes, sinusoidal discharge, or sharp activity. However, to a large extent EEG changes are linked to seizure propagation. Finally, in the context of presurgical evaluation, the combination of interictal and ictal EEG features is crucial to provide an optimal hypothesis concerning the epileptogenic zone.

Reproducibility of EEG-MEG fusion source analysis of interictal spikes: Relevance in presurgical evaluation of epilepsy

Fusion of electroencephalography (EEG) and magnetoencephalography (MEG) data using maximum entropy on the mean method (MEM-fusion) takes advantage of the complementarities between EEG and MEG to improve localization accuracy. Simulation studies demonstrated MEM-fusion to be robust especially in noisy conditions such as single spike source localizations (SSSL). Our objective was to assess the reliability of SSSL using MEM-fusion on clinical data. We proposed to cluster SSSL results to find the most reliable and consistent source map from the reconstructed sources, the so-called consensus map. Thirty-four types of interictal epileptic discharges (IEDs) were analyzed from 26 patients with well-defined epileptogenic focus. SSSLs were performed on EEG, MEG, and fusion data and consensus maps were estimated using hierarchical clustering. Qualitative (spike-to-spike reproducibility rate, SSR) and quantitative (localization error and spatial dispersion) assessments were performed using the epileptogenic focus as clinical reference. Fusion SSSL provided significantly better results than EEG or MEG alone. Fusion found at least one cluster concordant with the clinical reference in all cases. This concordant cluster was always the one involving the highest number of spikes. Fusion yielded highest reproducibility (SSR EEG = 55%, MEG = 71%, fusion = 90%) and lowest localization error. Also, using only few channels from either modality (21EEG + 272MEG or 54EEG + 25MEG) was sufficient to reach accurate fusion. MEM-fusion with consensus map approach provides an objective way of finding the most reliable and concordant generators of IEDs. We, therefore, suggest the pertinence of SSSL using MEM-fusion as a valuable clinical tool for presurgical evaluation of epilepsy.

Clinical yield of magnetoencephalography distributed source imaging in epilepsy: A comparison with equivalent current dipole method

OBJECTIVE

Source localization of interictal epileptic discharges (IEDs) is clinically useful in the presurgical workup of epilepsy patients. It is usually obtained by equivalent current dipole (ECD) which localizes a point source and is the only inverse solution approved by clinical guidelines. In contrast, magnetic source imaging using distributed methods (dMSI) provides maps of the location and the extent of the generators, but its yield has not been clinically validated. We systematically compared ECD versus dMSI performed using coherent Maximum Entropy on the Mean (cMEM), a method sensitive to the spatial extent of the generators.

METHODS

340 source localizations of IEDs derived from 49 focal epilepsy patients with foci well-defined through intracranial EEG, MRI lesions, and surgery were analyzed. The comparison was based on the assessment of the sublobar concordance with the focus and of the distance between the source and the focus.

RESULTS

dMSI sublobar concordance was significantly higher than ECD (81% vs 69%, P < 0.001), especially for extratemporal lobe sources (dMSI = 84%; ECD = 67%, P < 0.001) and for seizure free patients (dMSI = 83%; ECD = 70%, P < 0.001). The median distance from the focus was 4.88 mm for ECD and 3.44 mm for dMSI (P < 0.001). ECD dipoles were often wrongly localized in deep brain regions.

CONCLUSIONS

dMSI using cMEM exhibited better accuracy. dMSI also offered the advantage of recovering more realistic maps of the generator, which could be exploited for neuronavigation aimed at targeting invasive EEG and surgical resection. Therefore, dMSI may be preferred to ECD in clinical practice. Hum Brain Mapp 39:218-231, 2018. © 2017 Wiley Periodicals, Inc.

SISSY: An efficient and automatic algorithm for the analysis of EEG sources based on structured sparsity

Over the past decades, a multitude of different brain source imaging algorithms have been developed to identify the neural generators underlying the surface electroencephalography measurements. While most of these techniques focus on determining the source positions, only a small number of recently developed algorithms provides an indication of the spatial extent of the distributed sources. In a recent comparison of brain source imaging approaches, the VB-SCCD algorithm has been shown to be one of the most promising algorithms among these methods. However, this technique suffers from several problems: it leads to amplitude-biased source estimates, it has difficulties in separating close sources, and it has a high computational complexity due to its implementation using second order cone programming. To overcome these problems, we propose to include an additional regularization term that imposes sparsity in the original source domain and to solve the resulting optimization problem using the alternating direction method of multipliers. Furthermore, we show that the algorithm yields more robust solutions by taking into account the temporal structure of the data. We also propose a new method to automatically threshold the estimated source distribution, which permits to delineate the active brain regions. The new algorithm, called Source Imaging based on Structured Sparsity (SISSY), is analyzed by means of realistic computer simulations and is validated on the clinical data of four patients.

Temporal lobe spikes: EEG-fMRI contributions to the "mesial vs. lateral" debate

OBJECTIVE

It has been reported that interictal epileptic discharges (IEDs) recorded in temporal regions on scalp EEG are unlikely to originate from mesial temporal structures. However, EEG-fMRI sometimes show mesial temporal activation. We hypothesized that BOLD activation in the temporal neocortex is weaker than in the mesial structures, reflecting the fact that propagated activity has less metabolic demand than the original discharge.

METHODS

Twelve patients with epilepsy who have BOLD response in mesial temporal structures were selected from our EEG-fMRI database. We searched the temporal lobe ipsilateral to IEDs and checked whether there is positive BOLD response in the neocortex.

RESULTS

All IED types showed a BOLD response in the temporal neocortex ipsilateral to the mesial temporal BOLD response. T-values were higher in mesial temporal structures than in neocortex in 13/16 cases.

CONCLUSIONS

Hemodynamic changes were observed in the mesial temporal lobe at the time of IEDs recorded from the temporal region on the scalp. The finding of smaller BOLD changes in the ipsilateral neocortex is in agreement with our hypothesis.

SIGNIFICANCE

Our study indicates that scalp-recorded temporal lobe spikes are likely to result from mesial temporal spikes propagating neuronally to the neocortex.

Identification of Interictal Epileptic Networks from Dense-EEG

Epilepsy is a network disease. The epileptic network usually involves spatially distributed brain regions. In this context, noninvasive M/EEG source connectivity is an emerging technique to identify functional brain networks at cortical level from noninvasive recordings. In this paper, we analyze the effect of the two key factors involved in EEG source connectivity processing: (i) the algorithm used in the solution of the EEG inverse problem and (ii) the method used in the estimation of the functional connectivity. We evaluate four inverse solutions algorithms (dSPM, wMNE, sLORETA and cMEM) and four connectivity measures (r ², h ², PLV, and MI) on data simulated from a combined biophysical/physiological model to generate realistic interictal epileptic spikes reflected in scalp EEG. We use a new network-based similarity index to compare between the network identified by each of the inverse/connectivity combination and the original network generated in the model. The method will be also applied on real data recorded from one epileptic patient who underwent a full presurgical evaluation for drug-resistant focal epilepsy. In simulated data, results revealed that the selection of the inverse/connectivity combination has a significant impact on the identified networks. Results suggested that nonlinear methods (nonlinear correlation coefficient, phase synchronization and mutual information) for measuring the connectivity are more efficient than the linear one (the cross correlation coefficient). The wMNE inverse solution showed higher performance than dSPM, cMEM and sLORETA. In real data, the combination (wMNE/PLV) led to a very good matching between the interictal epileptic network identified from noninvasive EEG recordings and the network obtained from connectivity analysis of intracerebral EEG recordings. These results suggest that source connectivity method, when appropriately configured, is able to extract highly relevant diagnostic information about networks involved in interictal epileptic spikes from non-invasive dense-EEG data.

Correlation of invasive EEG and scalp EEG

Ever since the implementation of invasive EEG recordings in the clinical setting, it has been perceived that a considerable proportion of epileptic discharges present at a cortical level are missed by routine scalp EEG recordings. Several in vitro, in vivo, and simulation studies have been performed in the past decades aiming to clarify the interrelations of cortical sources with their scalp and invasive EEG correlates. The amplitude ratio of cortical potentials to their scalp EEG correlates, the extent of the cortical area involved in the discharge, as well as the localization of the cortical source and its geometry have been each independently linked to the recording of the cortical discharge with scalp electrodes. The need to elucidate these interrelations has been particularly imperative in the field of epilepsy surgery with its rapidly growing EEG-based localization technologies. Simultaneous multiscale EEG recordings with scalp, subdural and/or depth electrodes, applied in presurgical epilepsy workup, offer an excellent opportunity to shed some light to this fundamental issue. Whereas past studies have considered predominantly neocortical sources in the context of temporal lobe epilepsy, current investigations have included deep sources, as in mesial temporal epilepsy, as well as extratemporal sources. Novel computational tools may serve to provide surrogates for the shortcomings of EEG recording methodology and facilitate further developments in modern electrophysiology.

The Role of Skull Modeling in EEG Source Imaging for Patients with Refractory Temporal Lobe Epilepsy

We investigated the influence of different skull modeling approaches on EEG source imaging (ESI), using data of six patients with refractory temporal lobe epilepsy who later underwent successful epilepsy surgery. Four realistic head models with different skull compartments, based on finite difference methods, were constructed for each patient: (i) Three models had skulls with compact and spongy bone compartments as well as air-filled cavities, segmented from either computed tomography (CT), magnetic resonance imaging (MRI) or a CT-template and (ii) one model included a MRI-based skull with a single compact bone compartment. In all patients we performed ESI of single and averaged spikes marked in the clinical 27-channel EEG by the epileptologist. To analyze at which time point the dipole estimations were closer to the resected zone, ESI was performed at two time instants: the half-rising phase and peak of the spike. The estimated sources for each model were validated against the resected area, as indicated by the postoperative MRI. Our results showed that single spike analysis was highly influenced by the signal-to-noise ratio (SNR), yielding estimations with smaller distances to the resected volume at the peak of the spike. Although averaging reduced the SNR effects, it did not always result in dipole estimations lying closer to the resection. The proposed skull modeling approaches did not lead to significant differences in the localization of the irritative zone from clinical EEG data with low spatial sampling density. Furthermore, we showed that a simple skull model (MRI-based) resulted in similar accuracy in dipole estimation compared to more complex head models (based on CT- or CT-template). Therefore, all the considered head models can be used in the presurgical evaluation of patients with temporal lobe epilepsy to localize the irritative zone from low-density clinical EEG recordings.

EEG Source Imaging in Partial Epilepsy in Comparison with Presurgical Evaluation and Magnetoencephalography

Background and Purpose

The aim of this study was to determine the usefulness of three-dimensional (3D) scalp EEG source imaging (ESI) in partial epilepsy in comparison with the results of presurgical evaluation, magnetoencephalography (MEG), and electrocorticography (ECoG).

Methods

The epilepsy syndrome of 27 partial epilepsy patients was determined by presurgical evaluations. EEG recordings were made using 70 scalp electrodes, and the 3D coordinates of the electrodes were digitized. ESI images of individual and averaged spikes were analyzed by Curry software with a boundary element method. MEG and ECoG were performed in 23 and 9 patients, respectively.

Results

ESI and MEG source imaging (MSI) results were well concordant with the results of presurgical evaluations (in 96.3% and 100% cases for ESI and MSI, respectively) at the lobar level. However, there were no spikes in the MEG recordings of three patients. The ESI results were well concordant with MSI results in 90.0% of cases. Compared to ECoG, the ESI results tended to be localized deeper than the cortex, whereas the MSI results were generally localized on the cortical surface. ESI was well concordant with ECoG in 8 of 9 (88.9%) cases, and MSI was also well concordant with ECoG in 4 of 5 (80.0%) cases. The EEG single dipoles in one patient with mesial temporal lobe epilepsy were tightly clustered with the averaged dipole when a 3 Hz high-pass filter was used.

Conclusions

The ESI results were well concordant with the results of the presurgical evaluation, MSI, and ECoG. The ESI analysis was found to be useful for localizing the seizure focus and is recommended for the presurgical evaluation of intractable epilepsy patients.

[French guidelines on electroencephalogram]

Electroencephalography allows the functional analysis of electrical brain cortical activity and is the gold standard for analyzing electrophysiological processes involved in epilepsy but also in several other dysfunctions of the central nervous system. Morphological imaging yields complementary data, yet it cannot replace the essential functional analysis tool that is EEG. Furthermore, EEG has the great advantage of being non-invasive, easy to perform and allows control tests when follow-up is necessary, even at the patient's bedside. Faced with the advances in knowledge, techniques and indications, the Société de Neurophysiologie Clinique de Langue Française (SNCLF) and the Ligue Française Contre l'Épilepsie (LFCE) found it necessary to provide an update on EEG recommendations. This article will review the methodology applied to this work, refine the various topics detailed in the following chapters. It will go over the summary of recommendations for each of these chapters and underline proposals for writing an EEG report. Some questions could not be answered by the review of the literature; in those cases, an expert advice was given by the working and reading groups in addition to the guidelines.

EEG extended source localization: tensor-based vs. conventional methods

The localization of brain sources based on EEG measurements is a topic that has attracted a lot of attention in the last decades and many different source localization algorithms have been proposed. However, their performance is limited in the case of several simultaneously active brain regions and low signal-to-noise ratios. To overcome these problems, tensor-based preprocessing can be applied, which consists in constructing a space-time-frequency (STF) or space-time-wave-vector (STWV) tensor and decomposing it using the Canonical Polyadic (CP) decomposition. In this paper, we present a new algorithm for the accurate localization of extended sources based on the results of the tensor decomposition. Furthermore, we conduct a detailed study of the tensor-based preprocessing methods, including an analysis of their theoretical foundation, their computational complexity, and their performance for realistic simulated data in comparison to conventional source localization algorithms such as sLORETA, cortical LORETA (cLORETA), and 4-ExSo-MUSIC. Our objective consists, on the one hand, in demonstrating the gain in performance that can be achieved by tensor-based preprocessing, and, on the other hand, in pointing out the limits and drawbacks of this method. Finally, we validate the STF and STWV techniques on real measurements to demonstrate their usefulness for practical applications.

Sparse MEG source imaging for reconstructing dynamic sources of interictal spikes in partial epilepsy

PURPOSE

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Interictal networks in magnetoencephalography

Epileptic networks involve complex relationships across several brain areas. Such networks have been shown on intracerebral EEG (stereotaxic EEG, SEEG), an invasive technique. Magnetoencephalography (MEG) is a noninvasive tool, which was recently proven to be efficient for localizing the generators of epileptiform discharges. However, despite the importance of characterizing non-invasively network aspects in partial epilepsies, only few studies have attempted to retrieve fine spatiotemporal dynamics of interictal discharges with MEG. Our goal was to assess the relevance of magnetoencephalography for detecting and characterizing the brain networks involved in interictal epileptic discharges. We propose here a semi-automatic method based on independent component analysis (ICA) and on co-occurrence of events across components. The method was evaluated in a series of seven patients by comparing its results with networks identified in SEEG. On both MEG and SEEG, we found that interictal discharges can involve remote regions which are acting in synchrony. More regions were identified in SEEG (38 in total) than in MEG (20). All MEG regions were confirmed by SEEG when an electrode was present in the vicinity. In all patients, at least one region could be identified as leading according to our criteria. A majority (71%) of MEG leaders were confirmed by SEEG. We have therefore shown that MEG measurements can extract a significant proportion of the networks visible in SEEG. This suggests that MEG can be a useful tool for defining noninvasively interictal epileptic networks, in terms of regions and patterns of connectivity, in search for a "primary irritative zone".

Contribution of EEG/fMRI to the definition of the epileptic focus

OBJECTIVES

To evaluate the clinical relevance of EEG/fMRI in patients with focal epilepsy, by assessing the information it adds to the scalp EEG in the definition of the epileptic focus.

METHODS

Forty-three patients with focal epilepsy were studied with EEG/fMRI using a 3-T scanner. Blood oxygen level-dependent (BOLD) signal changes related to interictal epileptic discharges (IEDs) were classified as concordant or not concordant with the scalp EEG spike field and as contributory if the BOLD signal provided additional information to the scalp EEG about the epileptic focus or not contributory if it did not. We considered patients having intracerebral EEG or a focal lesion on MRI as having independent validation.

RESULTS

Thirty-three patients had at least 3 IEDs during the EEG/fMRI acquisition (active EEG), and all had a BOLD response. In 29 of 33 (88%) patients, the BOLD response was concordant, and in 21 of 33 (64%) patients, the BOLD response was contributory. Fourteen patients had an independent validation: in 12 of these 14, the BOLD responses were validated and in 2 they were invalidated.

CONCLUSIONS

A BOLD response was present in all patients with active EEG, and more specific localization of the epileptic focus was gained from EEG/fMRI in half of the patients who were scanned, when compared with scalp EEG alone. This study demonstrates that EEG/fMRI, in the context of a clinical practice, may contribute to the localization of the interictal epileptic generator in patients with focal epilepsy.

Imag(in)ing seizure propagation: MEG-guided interpretation of epileptic activity from a deep source

Identification and accurate localization of seizure foci is vital in patients with medically-intractable focal epilepsy, who may be candidates for potentially curative resective epilepsy surgery. We present a patient with difficult-to-control seizures associated with an occult focal cortical dysplasia residing within the deeper left parietal operculum and underlying posterior insula, which was not detected by conventional MRI analysis. Propagated activities from this deeper generator produced misleading EEG patterns both on surface and subdural electrode recordings suggesting initial activation of the perirolandic and mesial frontal regions. However, careful spatio-temporal analysis of stereotyped interictal activities recorded during MEG, using sequential dipole modeling, revealed a consistent pattern of epileptic propagation originating from the deeper source and propagating within few milliseconds to the dorsal convexity. In this instance, careful dissection of noninvasive investigations (interictal MEG along with ictal SPECT findings) allowed clinicians to dismiss the inaccurate and misleading findings of the traditional "gold-standard" intracranial EEG. In fact, this multimodal noninvasive approach uncovered a subtle dysplastic lesion, resection of which rendered the patient seizure-free. This case highlights the potential benefits of dynamic analysis of interictal MEG in the appropriate clinical context. Pathways of interictal spike propagation may help elucidate essential neural networks underlying focal epilepsy.

Source connectivity analysis from MEG and its application to epilepsy source localization

We report an approach to perform source connectivity analysis from MEG, and initially evaluate this approach to interictal MEG to localize epileptogenic foci and analyze interictal discharge propagations in patients with medically intractable epilepsy. Cortical activities were reconstructed from MEG using individual realistic geometry boundary element method head models. Directional connectivity among cortical regions of interest was then estimated using directed transfer function. The MEG source connectivity analysis method was implemented in the eConnectome software, which is open-source and freely available at http://econnectome.umn.edu . As an initial evaluation, the method was applied to study MEG interictal spikes from five epilepsy patients. Estimated primary epileptiform sources were consistent with surgically resected regions, suggesting the feasibility of using cortical source connectivity analysis from interictal MEG for potential localization of epileptiform activities.

sLORETA allows reliable distributed source reconstruction based on subdural strip and grid recordings

Source localization based on invasive recordings by subdural strip and grid electrodes is a topic of increasing interest. This simulation study addresses the question, which factors are relevant for reliable source reconstruction based on sLORETA. MRI and electrode positions of a patient undergoing invasive presurgical epilepsy diagnostics were the basis of sLORETA simulations. A boundary element head model derived from the MRI was used for the simulation of electrical potentials and source reconstruction. Focal dipolar sources distributed on a regular three-dimensional lattice and spatiotemporal distributed patches served as input for simulation. In addition to the distance between original and reconstructed source maxima, the activation volume of the reconstruction and the correlation of time courses between the original and reconstructed sources were investigated. Simulations were supplemented by the localization of the patient's spike activity. For noise-free simulated data, sLORETA achieved results with zero localization error. Added noise diminished the percentage of reliable source localizations with a localization error ≤15 mm to 67.8%. Only for source positions close to the electrode contacts the activation volume correctly represented focal generators. Time-courses of original and reconstructed sources were significantly correlated. The case study results showed accurate localization. sLORETA is a distributed source model, which can be applied for reliable grid and strip based source localization. For distant source positions, overestimation of the extent of the generator has to be taken into account. sLORETA-based source reconstruction has the potential to improve the localization of distributed generators in presurgical epilepsy diagnostics and cognitive neuroscience.

EEG and MEG in mesial temporal lobe epilepsy: where do the spikes really come from?

OBJECTIVE

There is persistent debate as to whether or not EEG and MEG recordings in patients with mesial temporal lobe epilepsy (MTLE) can detect mesial temporal interictal epileptiform discharges (spikes), and this issue is particularly relevant for source localization studies. With the aim of providing direct evidence pertinent to this debate we present detailed examples of the intracranial sources of spikes recorded with EEG and MEG in MTLE.

METHODS

Spikes recorded in five different patients with MTLE during intracranial EEG (n=2), intraoperative electrocorticography (ECOG; n=1), combined scalp-intracranial EEG (n=2) and combined EEG-MEG (n=1) were analyzed and the intracranial sources of the spike foci were matched with their corresponding extracranial EEG and/or MEG fields. EEG and MEG dipole source localization was performed on six independent spike foci identified in one representative patient with bilateral MTLE.

RESULTS

Spikes with an electrical field maximal at F7/8, F9/10≥T3/4 were generated in the anterolateral temporal neocortex. The absence of coincident spiking at mesial locations indicated that these were not propagated from or to the hippocampus. Spikes with an electrical field maximal at T3/4≥T9/10 were generated in the lateral temporal neocortex and likewise did not involve the hippocampus. Individual spikes generated in the mesiobasal temporal neocortex, including the fusiform gyrus, were difficult to detect with EEG (low amplitude diphasic waves most apparent after spike averaging at T3/4, T9/10≥T5/6, P9/10) and only slightly more identifiable with MEG. Spikes generated within and confined to the mesial temporal structures, as confirmed by intracranial recordings, could not be detected with EEG or MEG. Notably, such spikes could not be detected even at intracranial recording sites on the lateral surface of the temporal lobe.

CONCLUSIONS

We present detailed evidence in a small case series showing that typical anterior temporal spikes recorded with EEG and MEG in MTLE arose from the anterolateral temporal neocortex and were neither propagated from nor to the hippocampus. Mid temporal EEG spikes were localized to the lateral temporal neocortex. Intracranially detected mesial temporal spikes were not detected with EEG or MEG.

SIGNIFICANCE

The spikes recorded with EEG and MEG in MTLE are localized to neocortical foci, and not to the mesial temporal structures. Current noninvasive EEG and MEG source localization studies cannot accurately identify true mesial temporal spikes.

Noninvasive multimodal neuroimaging for Rasmussen encephalopathy surgery: simultaneous EEG-fMRI recording

Rasmussen syndrome is characterized by continuous partial seizures with progressive neurological/cognitive impairment. Currently the only effective treatment is surgery (hemispherectomy). The objective of our study is to detect the exact epileptogenic focus through the analysis of multimodal noninvasive and innocuous functional neuroimaging. The subject is a 5-year-old female patient with Rasmussen encephalopathy. Continuous and simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) was recorded. The sources of background and paroxysmal activity of EEG were computed by low resolution electromagnetic tomography (LORETA). Image analysis (SPM: statistic parametric mapping) was obtained for the areas where statistically significant differences in the fMRI BOLD response were computed, and the results from both techniques were compared. The main source of paroxysmal activity by EEG analysis was found in the anterolateral left hemisphere, with a significant increase in absolute and relative energies of slow frequency bands (theta-delta): Z > or = 3. The fMRI BOLD signal (basal vs. paroxysmal activity) was significantly different in the same region (t-test > or = 2.39). The generators of propagated paroxysmal activity were found in similar areas for both techniques. In conclusion, simultaneous EEG-fMRI recording allows the analysis of two harmless functional neuroimaging techniques separately and together in the same time period. In our case, it allowed the accurate delineation of epileptogenic foci and areas of spread with high spatiotemporal resolution, which is crucial for epilepsy surgery.

Decrease in propagation of interictal epileptiform activity after introduction of levetiracetam visualized with electric source imaging

Different neuroimaging techniques (fMRI, spectroscopy, PET) are being used to evaluate candidate drugs in pharmacological development. In patients with epilepsy fast propagation of the epileptiform activity between different brain areas occurs. Electric Source Imaging (ESI), in contrast to the aforementioned techniques, has a millisecond time resolution, allowing visualization of this fast propagation. The purpose of the current project was to use ESI to investigate whether introduction of an antiepileptic drug (levetiracetam, LEV) would change the propagation patterns of the interictal epileptiform activity. Thirty patients with epilepsy were subject to an EEG recording before (pre-LEV) and after (in-LEV) introduction of LEV. Interictal spikes with similar topographic distribution were averaged within each subject, and a distributed source model was used to localize the EEG sources of the epileptiform activity. The temporal development of the activity within 20 regions of interest (ROIs) was determined, and source propagation between different regions was compared between the pre-LEV and in-LEV recordings. Patients with epileptic seizures showed propagation in 22/24 identified spike types in the pre-LEV recordings. In the in-LEV recordings only 7/15 spike types showed propagation, and six of these seven propagating spikes were recorded in patients with poor effect of treatment. Also in patients without seizures LEV tended to suppress propagation. We conclude that the observed suppression of source propagation can be considered as an indicator of effective antiepileptic treatment. ESI might thus become a useful tool in the early clinical evaluation of new candidate drugs in pharmacological development.