Stereotaxic EEG Research Articles

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.

EpiTools, A software suite for presurgical brain mapping in epilepsy: Intracerebral EEG

BackgroundIn pharmacoresistant epilepsy, exploration with depth electrodes can be needed to precisely define the epileptogenic zone. Accurate location of these electrodes is thus essential for the interpretation of Stereotaxic EEG (SEEG) signals. As SEEG analysis increasingly relies on signal processing, it is crucial to make a link between these results and patient’s anatomy.Our aims were thus to develop a suite of software tools, called “EpiTools”, able to i) precisely and automatically localize the position of each SEEG contact and ii) display the results of signal analysis in each patient’s anatomy. New methodThe first tool, GARDEL (GUI for Automatic Registration and Depth Electrode Localization), is able to automatically localize SEEG contacts and to label each contact according to a pre-specified nomenclature (for instance that of FreeSurfer or MarsAtlas). The second tool, 3Dviewer, enables to visualize in the 3D anatomy of the patient the origin of signal processing results such as rate of biomarkers, connectivity graphs or Epileptogenicity Index. ResultsGARDEL was validated in 30 patients by clinicians and proved to be highly reliable to determine within the patient’s individual anatomy the actual location of contacts. Comparison with existing methodsGARDEL is a fully automatic electrode localization tool needing limited user interaction (only for electrode naming or contact correction). The 3Dviewer is able to read signal processing results and to display them in link with patient’s anatomy. ConclusionEpiTools can help speeding up the interpretation of SEEG data and improving its precision.

Cost-Effectiveness Analysis Of Stereotaxic Eeg (SEEG) As A Preoperative Diagnostic Procedure In Epilepsy Surgery

The aim of our study was to determine the health gain and the corresponding costs resulted from the introduction of stereotaxic EEG (SEEG) as a preoperative diagnostic procedure in epilepsy surgery for MRI negative refractory epilepsy patients. Furthermore, we analyzed the cost-effectiveness of the intervention compared to medical management as the standard of care in Hungary. The incremental health gains and costs of SEEG were determined with a Markov model over a 45 years’ time horizon. Transition probabilities and utilities have been derived from international literature. The intervention has not yet been financed by the National Healthcare Fund in Hungary, therefore the actual cost were determined from provider’s perspective, based on the relevant units costs and resource use at the Department of Neurology and Department of Neurosurgery regarding the intervention. Based on the result of our model the total cost of the SEEG intervention is 10,540 thousand HUF which represents a 4,490 thousand HUF additional cost and 3.086 QALY gain in 45 years compare to the standard medical management. The calculated preliminary incremental cost-effectiveness ratio is 1,455 thousand HUF/QALY. Based on our preliminary results in the treatment of patients with MR negative refractory epilepsy the preoperative SEEG diagnostic procedure in Hungary was cost-effective compared to the medical management. Based on our result we suggest the SEEG to be introduced into the Hungarian reimbursement system as a new procedure.

Technical solutions for simultaneous MEG and SEEG recordings: towards routine clinical use

Objective: The simultaneous recording of intracerebral EEG (stereotaxic EEG, SEEG) and magnetoencephalography (MEG) is a promising strategy that provides both local and global views on brain pathological activity. Yet, acquiring simultaneous signals poses difficult technical issues that hamper their use in clinical routine. Our objective was thus to develop a set of solutions for recording a high number of SEEG channels while preserving signal quality. Approach: We recorded data in a patient with drug resistant epilepsy during presurgical evaluation. We used dedicated insertion screws and optically insulated amplifiers. We recorded 137 SEEG contacts on 10 depth electrodes (5–15 contacts each) and 248 MEG channels (magnetometers). Signal quality was assessed by comparing the distribution of RMS values in different frequency bands to a reference set of MEG acquisitions. Main results: The quality of signals was excellent for both MEG and SEEG; for MEG, it was comparable to that of MEG signals without concurrent SEEG. Discharges involving several structures on SEEG were visible on MEG, whereas discharges limited in space were not seen at the surface. Significance: SEEG can now be recorded simultaneously with whole-head MEG in routine. This opens new avenues, both methodologically for understanding signals and improving signal processing methods, and clinically for future combined analyses.

Graph Measures of Node Strength for Characterizing Preictal Synchrony in Partial Epilepsy.

The reference electrophysiological pattern at seizure onset is the "rapid discharge," as visible on intracerebral electroencephalography (EEG). This discharge typically corresponds to a decrease of synchrony across brain areas. In contrast, the preictal period can exhibit patterns of increased synchrony, which can be quantified by network measures. Our objective was to compare preictal synchrony with a quantification of the rapid discharge as provided by the epileptogenicity index (EI). We investigated 24 seizures from 12 patients recorded by stereotaxic EEG (SEEG). Seizures were classified visually as containing preictal synchrony or not. We computed pairwise nonlinear correlation (h(2)) across channels in the 8 sec preceding the rapid discharge. The sum of ingoing and outgoing links (IN and OUT node strength), as well as the sum of all links (total strength, TOT) were computed for each region. We tested several filtering schemes, and quantified the capacity of each strength measure to serve as a detector of regions with high EI values using a receiver operating characteristic (ROC) analysis. We found that the best correspondence between node strength and EI was obtained for the OUT and TOT measures, for signals filtered in the 15-40 Hz band-that is, for the band corresponding to the spiky part of epileptic discharges. In agreement with these results, we also found that the ROC results were improved when considering only seizures with visible synchronous patterns in the preictal period. Our results suggest that measuring strength of preictal connectivity graphs can bring useful clinical information on the epileptogenic zone.

Using the connectome to predict epileptic seizure propagation in the human brain

Partial seizures in epileptic patients are generated in localized networks, so-called Epileptogenic Zone (EZ), before recruiting other regions, so-called Propagation Zone (PZ) [1]. For drug-resistant patients, surgical resection is sometimes possible. Correctly delineating the extent of the EZ and PZ is critical for a successful surgical resection, in order to remove enough of the epileptogenic tissue to prevent seizures while minimizing the cognitive collateral damages. EZ and PZ extents are evaluated using imaging tools such as M/EEG, MRI, PET and stereotaxic EEG (sEEG). In this modelisation work, we used the large-scale connectome to build a network of neural masses in order to reproduce seizure propagation through the human brain. In particular, we aimed at predicting the propagation of epileptic seizures, i.e. the PZ, using the localization of the EZ. We preprocessed data obtained from 18 different patients with different types of partial epilepsy. Using MRI and diffusion MRI data, we generated patient-specific connectomes along with cortical surfaces, using different parcellation resolutions. Epileptic dynamics of a single region was based on the Epileptor, a neural mass model able to autonomously generate epileptic seizures [2]. The different regions interacted via a permittivity coupling allowing to reproduce seizures propagation such as observed in sEEG [3]. Using a reduced Epileptor model, we performed a stability analysis at the edge of the seizure onset. We confirmed our results with simulations of the network of Epileptors using The Virtual Brain, a neuroinformatics platform to simulate large-scale dynamics [4]. The analytical prediction of seizure spatial extent correctly reproduces seizure simulations. We systematically predicted the spatial spread of the seizure, i.e. the PZ, for each patient, according to the spatial extent and localization of the EZ such as observed with sEEG, using different global connectivity and excitability parameters. An example of an EZ and PZ along with a simulation of the forward calculation on sEEG electrodes are shown in Figure ​Figure1.1. Our results show a good agreement with clinician predictions, surgery results, and sEEG signals. To confirm the determinant role of the connectome in spatial seizure propagation, we performed several surrogate analysis with other neural mass models (e.g. FitzHugh-Nagumo model), connectivity of control subjects and generic connectivities such as shuffled connectivities, random and small-world networks, again evaluated against clinical data. Real connectomes always performed better than generic connectivities. The connectome particular structure of a patient was often but not always better to predict seizure propagation than connectome of controls. Figure 1 A. Example of the EZ (red) and the calculated PZ (yellow) displayed on the patient cortical surface, along with sEEG electrodes (small spheres). B. Corresponding simulated time series. In conclusion, our results show that large-scale white matter tracts play an important role in the propagation of epileptic seizures. Better understanding of their exact role can help to significantly improve the success rate of surgical resections for epileptic patients.

Simultaneous recording of MEG, EEG and intracerebral EEG during visual stimulation: From feasibility to single-trial analysis

Electroencephalography (EEG), magnetoencephalography (MEG), and intracerebral stereotaxic EEG (SEEG) are the three neurophysiological recording techniques, which are thought to capture the same type of brain activity. Still, the relationships between non-invasive (EEG, MEG) and invasive (SEEG) signals remain to be further investigated. In early attempts at comparing SEEG with either EEG or MEG, the recordings were performed separately for each modality. However such an approach presents substantial limitations in terms of signal analysis. The goal of this technical note is to investigate the feasibility of simultaneously recording these three signal modalities (EEG, MEG and SEEG), and to provide strategies for analyzing this new kind of data. Intracerebral electrodes were implanted in a patient with intractable epilepsy for presurgical evaluation purposes. This patient was presented with a visual stimulation paradigm while the three types of signals were simultaneously recorded. The analysis started with a characterization of the MEG artifact caused by the SEEG equipment. Next, the average evoked activities were computed at the sensor level, and cortical source activations were estimated for both the EEG and MEG recordings; these were shown to be compatible with the spatiotemporal dynamics of the SEEG signals. In the average time–frequency domain, concordant patterns between the MEG/EEG and SEEG recordings were found below the 40Hz level. Finally, a fine-grained coupling between the amplitudes of the three recording modalities was detected in the time domain, at the level of single evoked responses. Importantly, these correlations have shown a high level of spatial and temporal specificity. These findings provide a case for the ability of trimodal recordings (EEG, MEG, and SEEG) to reach a greater level of specificity in the investigation of brain signals and functions.

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".

EEG–fMRI of epileptic spikes: Concordance with EEG source localization and intracranial EEG

Simultaneous EEG and fMRI recordings permit the non-invasive investigation of the generators of spontaneous brain activity such as epileptic spikes. Despite a growing interest in this technique, the precise relationship between its results and the actual regions of activated cortex is not clear. In this study, we have quantified for the first time the concordance between EEG–fMRI results and stereotaxic EEG (SEEG) recordings in 5 patients with partial epilepsy. We also compared fMRI and SEEG with other non-invasive maps based on scalp EEG alone. We found that SEEG measures largely validated the results of EEG and fMRI. Indeed, when there is an intracranial electrode in the vicinity of an EEG or fMRI peak (in the range 20–40 mm), then it usually includes one active contact. This was the case for both increases (‘activations’) and decreases (‘deactivations’) of the fMRI signal: in our patients, fMRI signal decrease could be as important in understanding the complete picture of activity as increase of fMRI signal. The concordance between EEG and fMRI was not as good as the concordance between either of these non-invasive techniques and SEEG. This shows that the two techniques can show different regions of activity: they are complementary for the localization of the areas involved in the generation of epileptic spikes. Moreover, we found that the sign of the fMRI response correlated with the low frequency content of the SEEG epileptic transients, this latter being a reflection of the slow waves. Thus, we observed a higher proportion of energy in the low frequencies for the SEEG recorded in regions with fMRI signal increase compared to the regions with fMRI signal decrease. This could reflect an increase of metabolism linked to the presence of slow waves, which suggests that fMRI is a new source of information on the mechanisms of spike generation.

An H(2) (15)O-PET study of cerebral blood flow changes during focal epileptic discharges induced by intracerebral electrical stimulation.

Partial epileptic seizures are known to cause a focal increase in cerebral blood flow (CBF). However, quantified studies of ictal CBF changes under intracranial EEG control are still needed to assess the relationships in time and space between CBF changes and electrical discharges. Ten patients undergoing an intracerebral stereotaxic EEG (stereo-EEG) investigation for epilepsy surgery were prospectively studied for local perfusion changes. These were measured by H(2)(15)O-PET during 12 subclinical or mild symptomatic focal epileptic discharges induced by intracerebral electrical stimulation of the hippocampus (eight), amygdala (two), temporal pole (one) and fusiform gyrus (one). This study aimed to assess whether a significant focal blood flow change reflected the geographical extent of the underlying coincident epileptic discharge, as measured by this method at seizure onset. No significant CBF change was observed on test-retest at rest or during ineffective electrical stimulations outside the epileptogenic area. Compared with the resting condition, a significant focal perfusion increase of 16-55% occurred during eight discharges, there was no CBF change in three and a significant CBF decrease in one. Ictal CBF increases were mostly associated with low-voltage fast activity, but their magnitude had no obvious link with the duration of the discharge (range 8-106 s). Regional analysis of ictal PET was performed in 10 anatomical areas during each of the 12 discharges. Of all the 120 regions, 59 were not explored by intracerebral electrodes and 14 (24%) of these demonstrated ictal CBF changes. In 43 of the 61 regions explored by stereo-EEG (70.5%), PET and depth EEG findings converged, showing either a CBF change in a discharging area or no CBF change in a region unaffected by the discharge. Areas of increased CBF indicated an underlying epileptic discharge in almost 100% of the cases. Conversely, of the 18 regions showing discrepancies between intracerebral recordings and PET data, 17 were discharging regions showing no ictal CBF changes. Thus, a focal CBF increase, when detected at the seizure onset concomitantly with the initial low-voltage fast activity, was a reliable marker of an underlying epileptic discharge. It emphasizes the importance of injecting blood-flow tracers as soon as possible after detection of the discharge in routine clinical studies, even at a subclinical stage of the seizure. However, the extent of significant ictal CBF changes can be more restricted than that of the electrical discharge, thus limiting the reliability of ictal CBF images for outlining the contours of a tailored cortectomy.