Non-supervised spatio-temporal analysis of interictal magnetic spikes: comparison with intracerebral recordings

Comparison of Brain Networks During Interictal Oscillations and Spikes on Magnetoencephalography and Intracerebral EEG

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

Intracranial EEG potentials estimated from MEG sources: A new approach to correlate MEG and iEEG data in epilepsy

Detection of epileptic spikes in MagnetoEncephaloGraphy (MEG) requires synchronized neuronal activity over a minimum of 4cm2. We previously validated the Maximum Entropy on the Mean (MEM) as a source localization able to recover the spatial extent of the epileptic spike generators. The purpose of this study was to evaluate quantitatively, using intracranial EEG (iEEG), the spatial extent recovered from MEG sources by estimating iEEG potentials generated by these MEG sources. We evaluated five patients with focal epilepsy who had a pre-operative MEG acquisition and iEEG with MRI-compatible electrodes. Individual MEG epileptic spikes were localized along the cortical surface segmented from a pre-operative MRI, which was co-registered with the MRI obtained with iEEG electrodes in place for identification of iEEG contacts. An iEEG forward model estimated the influence of every dipolar source of the cortical surface on each iEEG contact. This iEEG forward model was applied to MEG sources to estimate iEEG potentials that would have been generated by these sources. MEG-estimated iEEG potentials were compared with measured iEEG potentials using four source localization methods: two variants of MEM and two standard methods equivalent to minimum norm and LORETA estimates. Our results demonstrated an excellent MEG/iEEG correspondence in the presumed focus for four out of five patients. In one patient, the deep generator identified in iEEG could not be localized in MEG. MEG-estimated iEEG potentials is a promising method to evaluate which MEG sources could be retrieved and validated with iEEG data, providing accurate results especially when applied to MEM localizations. Hum Brain Mapp 37:1661-1683, 2016. © 2016 Wiley Periodicals, Inc.

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".

Realistic synthetic background neuronal activity for the analysis of MEG probe configurations

Magnetoencephalography (MEG) sensors are capable of recording the tiny magnetic activity from the brain. They can be constituted of either magnetometers or gradiometers that respectively record the magnetic field or its gradient. In this paper, we present a framework for constructing realistic MEG signals. This framework can be used to test different probe configurations and source localization algorithms. The methodology of generation of synthetic signals is presented, and synthetic signals are compared to real signals. Paroxysmal activity generated with this model and originating from a deep cerebral source is determined with two different localization algorithms. Preliminary results show that gradiometers even with a short baseline perform close to magnetometer and that the use of hybrid systems should be further investigated.

Electric Source Imaging in Frontal Lobe Epilepsy

The objective of this study was to determine the validity of interictal spike (IIS) source localization in frontal lobe epilepsies (FLE) using stereoelectroencephalography as a validating method. Ten patients with drug-resistant FLE were studied with high-resolution EEG and stereoelectroencephalography. Sixty-four scalp channels, a realistic head model, and different algorithms were used. For each patient, the intracerebral interictal distribution was studied and classified into one of three groups: lateral, medial, and mixed (latero-medio-basal). Surface IIS were abundant or subcontinuous for 8 of 10 FLE patients. In lateral and medial groups, intracerebral interictal activities were accurately localized. In the mixed group, source localizations designated a part of the intracerebral interictal distribution. A high degree of source localization accuracy is obtained in FLE. False-positive results were never obtained, but the extent of interictal activity could be underestimated by source localization results. Geometrical and cytoarchitectonic characteristics of the generator appear crucial to explain why medial frontal IIS (anterior para-cingulate gyrus and anterior cingulate gyrus) may be localizable whereas only the lateral orbitofrontal IIS seems to be localizable.

Revisiting the role of magnetoencephalography in epilepsy

PURPOSE OF REVIEW

This review considers the current role of magnetoencephalography in clinical epileptology.

RECENT FINDINGS

While magnetoencephalography and electroencephalography complement each other for interictal spike detection, magnetoencephalography is more sensitive in neocortical epilepsy. In temporal lobe epilepsy, magnetoencephalography can attribute epileptic activity to subcompartments of the temporal lobe and differentiate between patients with mesial, lateral and diffuse seizure onsets. In extratemporal epilepsy, magnetoencephalography provides unique information in nonlesional cases and helps to define the relationship of epileptic activity with respect to lesions and eloquent cortex. Magnetoencephalography also contributes to the clinical decision process in patients with cortical dysplasias, Landau-Kleffner syndrome and recurrent seizures after prior epilepsy surgery. Magnetoencephalography-guided re-evaluation of magnetic resonance imaging helps to reveal previously unrecognized lesions. In a presurgical setting interictal magnetoencephalography was superior to scalp electroencephalography. Complete resection of the magnetoencephalography-defined irritative zone has prognostic implications on postoperative seizure control. Magnetoencephalography can reliably localize sensorimotor and language cortex. Disadvantages of this technique include the difficulties in obtaining ictal recordings and the considerable costs involved.

SUMMARY

Magnetoencephalography has been developed to a valuable noninvasive tool in clinical epileptology. The development of approaches which take into account both magnetoencephalography and electroencephalography simultaneously should provide more useful information in the future.

Electric Source Imaging in Temporal Lobe Epilepsy

The objective of this study was to determine the validity of interictal spike (IIS) source localization in temporal lobe epilepsies (TLE) using stereoelectroencephalography as a validating method. Twenty patients with drug-resistant TLE were studied with high-resolution EEG and stereoelectroencephalography. Sixty-four scalp channels, a realistic head model, and different algorithms were used. For each patient, the intracerebral interictal distribution was studied and classified into one of three groups: L (mainly lateral), ML (mediolateral), and M (medial). In group L (three patients), surface IIS were recorded with a high signal-to-noise ratio. Source localizations designated all or part of the intracerebral interictal distribution. In group ML (11 patients), 8 patients had surface IIS, only 5 of which were localizable. High-resolution EEG permitted localization of the more lateral portion and definition of its rostrocaudal extension. A common pattern was identified in three patients with a predominant role of the temporal pole. In group M (six patients), four patients had rare surface IIS, none of which were localizable. Surface EEG does not record IIS limited to medial temporal lobe structures. In TLE with a mediolateral or a lateral interictal distribution, only the lateral component is detectable on surface EEG and accurately localizable by source localization tools.

Predicting performance from functional imaging data: methods matter

In the standard approach to functional imaging studies, brain-behavior relationships are studied by contrasting data obtained during different behavioral states. It is generally assumed that relative change yields meaningful data about relevant brain processes, and that the magnitude of the change reflects the extent of a region's involvement in the behavior being studied. The present study takes a different approach by asking the question, Can functional imaging data predict performance? Regional cerebral blood flow was measured using positron emission tomography in a group of 13 right-handed, normal volunteers during speech production and quiet baseline. A number of methodological assumptions were addressed by examining the relationships between different imaging measures derived from the same raw data and performance on the speech task. The results demonstrate that several common assumptions are not necessarily true. First, although measures based on "activated" scans alone had predictive value with respect to speech rate, measures based on contrasts between "baseline" and "activated" states did not. This was true regardless of whether the contrast was based on subtraction or covariance analyses. Second, while many regions demonstrated large signal increases during speech, speech rate could be predicted by a linear combination of data from two regions, neither of which had the highest "activation" peak, and one of which had a negative relationship with performance. The results demonstrate that contrasting experimental conditions do not necessarily isolate or enhance brain activity related to performance, and that the current assumptions about activation in functional imaging need to be reconsidered.