Tangential and radial epileptic spike activity: different sensitivity in EEG and MEG

A comprehensive study on electroencephalography and magnetoencephalography sensitivity to cortical and subcortical sources

Signal-to-noise ratio (SNR) maps are a good way to visualize electroencephalography (EEG) and magnetoencephalography (MEG) sensitivity. SNR maps extend the knowledge about the modulation of EEG and MEG signals by source locations and orientations and can therefore help to better understand and interpret measured signals as well as source reconstruction results thereof. Our work has two main objectives. First, we investigated the accuracy and reliability of EEG and MEG finite element method (FEM)-based sensitivity maps for three different head models, namely an isotropic three and four-compartment and an anisotropic six-compartment head model. As a result, we found that ignoring the cerebrospinal fluid leads to an overestimation of EEG SNR values. Second, we examined and compared EEG and MEG SNR mappings for both cortical and subcortical sources and their modulation by source location and orientation. Our results for cortical sources show that EEG sensitivity is higher for radial and deep sources and MEG for tangential ones, which are the majority of sources. As to the subcortical sources, we found that deep sources with sufficient tangential source orientation are recordable by the MEG. Our work, which represents the first comprehensive study where cortical and subcortical sources are considered in highly detailed FEM-based EEG and MEG SNR mappings, sheds a new light on the sensitivity of EEG and MEG and might influence the decision of brain researchers or clinicians in their choice of the best modality for their experiment or diagnostics, respectively.

Relative Yield of MEG and EEG Spikes in Simultaneous Recordings

PURPOSE

Most clinical magnetoencephalography (MEG) centers record both MEG and EEG, but model only MEG sources. This may be related to the belief that MEG spikes are more prevalent, MEG is more sensitive, or to proprietary software limitations. Biophysics would contend, however, that EEG, being sensitive to radial and tangential source orientations, would provide complementary data for analysis.

METHODS

We recorded 306 channels of MEG and 25 channels of EEG simultaneously in 297 consecutive patients over 3 years. We inspected the MEG and EEG recordings separately, identified spikes in both, determined whether their voltage and/or magnetometer magnetic fields were dipolar and thus model-worthy, and segregated them into types based on similar and distinct field topography. We placed for each patient their spike types into categories, including those with both a recognizable MEG and EEG signal and those with only an MEG and only an EEG signal.

RESULTS

Eighty-three percent of patients had spikes recorded, and these patients had an average of 2.7 spike types each. Fifty-six percent of spike types were present in both MEG and EEG. However, 36% of spike types were only evident in EEG, whereas 8% were noted in MEG alone. In 49% of patients with spikes, MEG review missed at least one spike type, whereas in 17% of patients, EEG review missed at least one spike type.

CONCLUSIONS

To obtain an optimal yield of diagnostic information, EEG should also be subjected to source analysis in any clinical MEG study. EEG and MEG data are indeed complementary.

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.

Epileptic spikes in Rasmussen's encephalitis: Migratory pattern and short-term evolution. A MEG study

OBJECTIVE

We aimed this study at identifying cortical areas involved in the generation of interictal spikes in Rasmussen's Encephalitis (RE) patients using magnetoencephalography (MEG), at comparing spike localization with the degree of cortical atrophy detected by MRI, and at identifying short-term changes during the follow-up.

METHODS

Five patients with RE underwent two MEG and magnetic resonance imaging (MRI) (six months interval). The sources of visually detected spikes were estimated using equivalent current dipoles technique; these were then superimposed on individual MRI and clustered; the locations of the clusters were related to the MRI stage of cortical atrophy.

RESULTS

All patients showed spikes and clusters located in different cortical areas in both recordings; the locations had a limited correspondence with cortical atrophy. The second recordings showed changes in the localisation of spikes and clusters, and confirmed the dissimilarities with neuroradiological abnormalities.

CONCLUSIONS

The presence of clusters of spikes of variable localisation suggests that RE progresses in a multifocal and fluctuating manner. The cortical areas most involved in epileptogenesis did not completely coincide with the most atrophic areas.

SIGNIFICANCE

MEG can contribute to evaluating multifocal hemispheric spikes in RE and to better understand the time course of epileptogenic process.

Added diagnostic value of magnetoencephalography (MEG) in patients suspected for epilepsy, where previous, extensive EEG workup was unrevealing

OBJECTIVE

To elucidate the possible additional diagnostic yield of MEG in the workup of patients with suspected epilepsy, where repeated EEGs, including sleep-recordings failed to identify abnormalities.

METHODS

Fifty-two consecutive patients with clinical suspicion of epilepsy and at least three normal EEGs, including sleep-EEG, were prospectively analyzed. The reference standard was inferred from the diagnosis obtained from the medical charts, after at least one-year follow-up. MEG (306-channel, whole-head) and simultaneous EEG (MEG-EEG) was recorded for one hour. The added sensitivity of MEG was calculated from the cases where abnormalities were seen in MEG but not EEG.

RESULTS

Twenty-two patients had the diagnosis epilepsy according to the reference standard. MEG-EEG detected abnormalities, and supported the diagnosis in nine of the 22 patients with the diagnosis epilepsy at one-year follow-up. Sensitivity of MEG-EEG was 41%. The added sensitivity of MEG was 18%. MEG-EEG was normal in 28 of the 30 patients categorized as 'not epilepsy' at one year follow-up, yielding a specificity of 93%.

CONCLUSIONS

MEG provides additional diagnostic information in patients suspected for epilepsy, where repeated EEG recordings fail to demonstrate abnormality.

SIGNIFICANCE

MEG should be included in the diagnostic workup of patients where the conventional, widely available methods are unrevealing.

Source localization of the seizure onset zone from ictal EEG/MEG data

INTRODUCTION

Surgical treatment of drug-resistant epilepsy relies on the identification of the seizure onset zone (SOZ) and often requires intracranial EEG (iEEG). We have developed a new approach for non-invasive magnetic and electric source imaging of the SOZ (MSI-SOZ and ESI-SOZ) from ictal magnetoencephalography (MEG) and EEG recordings, using wavelet-based Maximum Entropy on the Mean (wMEM) method. We compared the performance of MSI-SOZ and ESI-SOZ with interictal spike source localization (MSI-spikes and ESI-spikes) and clinical localization of the SOZ (i.e., based on iEEG or lesion topography, denoted as clinical-SOZ).

METHODS

A total of 46 MEG or EEG seizures from 13 patients were analyzed. wMEM was applied around seizure onset, centered on the frequency band showing the strongest power change. Principal component analysis applied to spatiotemporal reconstructed wMEM sources (0.4-1 s around seizure onset) identified the main spatial pattern of ictal oscillations. Qualitative sublobar concordance and quantitative measures of distance and spatial overlaps were estimated to compare MSI/ESI-SOZ with MSI/ESI-Spikes and clinical-SOZ.

RESULTS

MSI/ESI-SOZ were concordant with clinical-SOZ in 81% of seizures (MSI 90%, ESI 64%). MSI-SOZ was more accurate and identified sources closer to the clinical-SOZ (P = 0.012) and to MSI-Spikes (P = 0.040) as compared with ESI-SOZ. MSI/ESI-SOZ and MSI/ESI-Spikes did not differ in terms of concordance and distance from the clinical-SOZ.

CONCLUSIONS

wMEM allows non-invasive localization of the SOZ from ictal MEG and EEG. MSI-SOZ performs better than ESI-SOZ. MSI/ESI-SOZ can provide important additional information to MSI/ESI-Spikes during presurgical evaluation. Hum Brain Mapp 37:2528-2546, 2016. © 2016 Wiley Periodicals, Inc.

EEG-MEG Integration Enhances the Characterization of Functional and Effective Connectivity in the Resting State Network

At the sensor level many aspects, such as spectral power, functional and effective connectivity as well as relative-power-ratio ratio (RPR) and spatial resolution have been comprehensively investigated through both electroencephalography (EEG) and magnetoencephalography (MEG). Despite this, differences between both modalities have not yet been systematically studied by direct comparison. It remains an open question as to whether the integration of EEG and MEG data would improve the information obtained from the above mentioned parameters. Here, EEG (64-channel system) and MEG (275 sensor system) were recorded simultaneously in conditions with eyes open (EO) and eyes closed (EC) in 29 healthy adults. Spectral power, functional and effective connectivity, RPR, and spatial resolution were analyzed at five different frequency bands (delta, theta, alpha, beta and gamma). Networks of functional and effective connectivity were described using a spatial filter approach called the dynamic imaging of coherent sources (DICS) followed by the renormalized partial directed coherence (RPDC). Absolute mean power at the sensor level was significantly higher in EEG than in MEG data in both EO and EC conditions. At the source level, there was a trend towards a better performance of the combined EEG+MEG analysis compared with separate EEG or MEG analyses for the source mean power, functional correlation, effective connectivity for both EO and EC. The network of coherent sources and the spatial resolution were similar for both the EEG and MEG data if they were analyzed separately. Results indicate that the combined approach has several advantages over the separate analyses of both EEG and MEG. Moreover, by a direct comparison of EEG and MEG, EEG was characterized by significantly higher values in all measured parameters in both sensor and source level. All the above conclusions are specific to the resting state task and the specific analysis used in this study to have general conclusion multi-center studies would be helpful.

MEG-EEG Information Fusion and Electromagnetic Source Imaging: From Theory to Clinical Application in Epilepsy

The purpose of this study is to develop and quantitatively assess whether fusion of EEG and MEG (MEEG) data within the maximum entropy on the mean (MEM) framework increases the spatial accuracy of source localization, by yielding better recovery of the spatial extent and propagation pathway of the underlying generators of inter-ictal epileptic discharges (IEDs). The key element in this study is the integration of the complementary information from EEG and MEG data within the MEM framework. MEEG was compared with EEG and MEG when localizing single transient IEDs. The fusion approach was evaluated using realistic simulation models involving one or two spatially extended sources mimicking propagation patterns of IEDs. We also assessed the impact of the number of EEG electrodes required for an efficient EEG–MEG fusion. MEM was compared with minimum norm estimate, dynamic statistical parametric mapping, and standardized low-resolution electromagnetic tomography. The fusion approach was finally assessed on real epileptic data recorded from two patients showing IEDs simultaneously in EEG and MEG. Overall the localization of MEEG data using MEM provided better recovery of the source spatial extent, more sensitivity to the source depth and more accurate detection of the onset and propagation of IEDs than EEG or MEG alone. MEM was more accurate than the other methods. MEEG proved more robust than EEG and MEG for single IED localization in low signal-to-noise ratio conditions. We also showed that only few EEG electrodes are required to bring additional relevant information to MEG during MEM fusion.

Combined EEG/MEG can outperform single modality EEG or MEG source reconstruction in presurgical epilepsy diagnosis

We investigated two important means for improving source reconstruction in presurgical epilepsy diagnosis. The first investigation is about the optimal choice of the number of epileptic spikes in averaging to (1) sufficiently reduce the noise bias for an accurate determination of the center of gravity of the epileptic activity and (2) still get an estimation of the extent of the irritative zone. The second study focuses on the differences in single modality EEG (80-electrodes) or MEG (275-gradiometers) and especially on the benefits of combined EEG/MEG (EMEG) source analysis. Both investigations were validated with simultaneous stereo-EEG (sEEG) (167-contacts) and low-density EEG (ldEEG) (21-electrodes). To account for the different sensitivity profiles of EEG and MEG, we constructed a six-compartment finite element head model with anisotropic white matter conductivity, and calibrated the skull conductivity via somatosensory evoked responses. Our results show that, unlike single modality EEG or MEG, combined EMEG uses the complementary information of both modalities and thereby allows accurate source reconstructions also at early instants in time (epileptic spike onset), i.e., time points with low SNR, which are not yet subject to propagation and thus supposed to be closer to the origin of the epileptic activity. EMEG is furthermore able to reveal the propagation pathway at later time points in agreement with sEEG, while EEG or MEG alone reconstructed only parts of it. Subaveraging provides important and accurate information about both the center of gravity and the extent of the epileptogenic tissue that neither single nor grand-averaged spike localizations can supply.

Localization of the epileptogenic foci in tuberous sclerosis complex: a pediatric case report

Tuberous sclerosis complex (TSC) is a rare disorder of tissue growth and differentiation, characterized by benign hamartomas in the brain and other organs. Up to 90% of TSC patients develop epilepsy and 50% become medically intractable requiring resective surgery. The surgical outcome of TSC patients depends on the accurate identification of the epileptogenic zone consisting of tubers and the surrounding epileptogenic tissue. There is conflicting evidence whether the epileptogenic zone is in the tuber itself or in abnormally developed surrounding cortex. Here, we report the localization of the epileptiform activity among the many cortical tubers in a 4-year-old patient with TSC-related refractory epilepsy undergoing magnetoencephalography (MEG), electroencephalography (EEG), and diffusion tensor imaging (DTI). For MEG, we used a prototype system that offers higher spatial resolution and sensitivity compared to the conventional adult systems. The generators of interictal activity were localized using both EEG and MEG with equivalent current dipole (ECD) and minimum norm estimation (MNE) methods according to the current clinical standards. For DTI, we calculated four diffusion scalar parameters for the fibers passing through four ROIs defined: (i) at a large cortical tuber identified at the right quadrant, (ii) at the normal appearing tissue contralateral to the tuber, (iii) at the cluster formed by ECDs fitted at the peak of interictal spikes, and (iv) at the normal appearing tissue contralateral to the cluster. ECDs were consistently clustered at the vicinity of the large calcified cortical tuber. MNE and ECDs indicated epileptiform activity in the same areas. DTI analysis showed differences between the scalar values of the tracks passing through the tuber and the ECD cluster. In this illustrative case, we provide evidence from different neuroimaging modalities, which support the view that epileptiform activity may derive from abnormally developed tissue surrounding the tuber rather than the tuber itself.

Comparison of three-shell and simplified volume conductor models in magnetoencephalography

Experimental MEG source imaging studies have typically been carried out with either a spherically symmetric head model or a single-shell boundary-element (BEM) model that is shaped according to the inner skull surface. The concepts and comparisons behind these simplified models have led to misunderstandings regarding the role of skull and scalp in MEG. In this work, we assess the forward-model errors due to different skull/scalp approximations and due to differences and errors in model geometries. We built five anatomical models of a volunteer using a set of T1-weighted MR scans and three common toolboxes. Three of the models represented typical models in experimental MEG, one was manually constructed, and one contained a major segmentation error at the skull base. For these anatomical models, we built forward models using four simplified approaches and a three-shell BEM approach that has been used as reference in previous studies. Our reference model contained in addition the skull fine-structure (spongy bone). We computed signal topographies for cortically constrained sources in the left hemisphere and compared the topographies using relative error and correlation metrics. The results show that the spongy bone has a minimal effect on MEG topographies, and thus the skull approximation of the three-shell model is justified. The three-shell model performed best, followed by the corrected-sphere and single-shell models, whereas the local-spheres and single-sphere models were clearly worse. The three-shell model was the most robust against the introduced segmentation error. In contrast to earlier claims, there was no noteworthy difference in the computation times between the realistically-shaped and sphere-based models, and the manual effort of building a three-shell model and a simplified model is comparable. We thus recommend the realistically-shaped three-shell model for experimental MEG work. In cases where this is not possible, we recommend a realistically-shaped corrected-sphere or single-shell model.