Tangential and radial epileptic spike activity: different sensitivity in EEG and MEG (original) (raw)
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Tangential and Radial Epileptic Spike Activity
Journal of Clinical Neurophysiology, 2012
Objective: Observations in epileptic patients show that interictal spikes are sometimes only visible in electroencephalography (EEG) and sometimes only in magnetoencephalography (MEG). This observation cannot readily be explained by the theoretical sensitivities of EEG and MEG based on analytical models. In this context, we aimed to study the directional sensitivity of radial and tangential spike activity in numerical simulations using realistic head models. Methods: We calculated the signal-to-noise ratio (SNR) of simulated spikes at varying orientations and with varying background activity in 12 brain regions in 4 volunteers. Different levels of background activity were modeled by adjusting the amplitudes of several thousand dipoles distributed in the cortex. Results: For a fixed realistic background activity, we found a higher SNR for MEG spikes for spike orientations that deviated not .308 from the tangential direction. In contrast, we found a higher SNR for EEG spikes that deviated not .458 from the radial direction. When the radial background activity was selectively increased, the sensitivity of EEG for radially oriented spikes decreased; when the tangential background activity selectively increased, the sensitivity of MEG for tangentially oriented spikes was decreased. Conclusions: Our simulations provide a possible explanation for the clinically observed differences in epileptic spike detection between EEG and MEG. Epileptic spike detection can be improved by analyzing a combination of EEG and MEG data.
Multidipole Analysis of Simulated Epileptic Spikes With Real Background Activity
Journal of Clinical Neurophysiology, 2003
This simulated magnetoencephalographic study was designed to determine the variability in source parameters with real subject background activity when applying multidipole spatial-temporal dipole analyses, for which the correct model was compared with undermodeled and overmodeled cases. The simulated sources were created from patches of the cortical surface of each subject's MRI. One-and two-source frontal lobe spikes were generated in two cortical regions seen commonly in frontal lobe epilepsy patients tested at our site (orbital frontal and premotor cortex). In general, the modeling results were adequate for the correct model order and the correct model order plus one. In addition, if the localization error was less than 10 mm from the simulated source, the peak latency of the spike and orientation were very reliable, but the peak amplitude was not. The additional source in the overmodeled condition, on the other hand, was not localized reliably across the different epochs within subjects. The results suggest that consistency of the spike localization and inconsistency of other sources will allow one to determine reliably the appropriate model order in real data, and therefore determine single and multifocal spike generators.
What Does an Epileptiform Spike Look Like in MEG? Comparison Between Coincident EEG and MEG Spikes
Journal of Clinical Neurophysiology, 2005
Recent investigations suggest that there are differences between the characteristics of EEG and MEG epileptiform spikes. The authors performed an objective characterization of the morphology of epileptiform spikes recorded simultaneously in both EEG and MEG to determine whether they present the same morphologic characteristics. Based on a stepwise approach, the authors performed a computer analysis of EEG and MEG of a set of coincident epileptiform transients selected by a senior clinical neurophysiologist in recordings of three patients with drug-resistant epilepsy. A computer-based algorithm was applied to extract parameters that could be used to describe quantitatively the morphology of the transients, followed by a statistical comparison over the extracted metrics of the EEG and MEG waveforms. EEG and MEG coincident events were statistically different with respect to several morphologic characteristics, such as duration, sharpness, and shape. The differences found appear to be a consequence of MEG signals not being influenced by volume propagation through the tissues with different conductivities that surround the brain, compared with EEG, and of the different orientation of the underlying dipolar sources. The results indicate that visual inspection of MEG spikes and automatic spike-detector algorithms should use criteria adapted to the specific characteristics of the MEG, and not simply those used on conventional EEG. FIGURE 3. EEG versus MEG. Histograms of the duration (a) and sharpness (b) of 120 simultaneously recorded EEG and MEG spikes.
Clinical Neurophysiology, 2006
Objective: To evaluate whether the orientation of interictal spikes, localized in major sulci by magnetoencephalography (MEG), predicts the epileptogenic side of the sulcal wall. Methods: Sixteen epilepsy patients were analyzed in whom equivalent current dipoles (ECDs) of MEG spikes were localized on the central (four patients), interhemispheric (4), or sylvian fissure (8); and the epileptogenic side across the sulci had been confirmed by seizure semiology, structural lesions, or intracranial electroencephalography (EEG). ECD was classified as epileptogenic side or normal side oriented and correlated to the scalp EEG map. Results: All central (nZ50) and interhemispheric (nZ83) spike ECDs were oriented toward the epileptogenic side at peak latency. In scalp EEG, 91% of the spikes showed radial pattern of broad negativity above the sulcus whereas 9% showed tangential pattern with positive maximum above the epileptogenic side. Sylvian spikes were only found in patients with temporal lobe epilepsy (TLE). In sylvian spikes (nZ 220), 73% of ECDs were oriented toward the epileptogenic side, whereas 27% were oriented toward the normal side. Conclusions: In central and interhemispheric spikes, epileptogenic side cortex may be gross surface negative through the sulcal wall to the adjacent gyrus. Inconsistent orientation of the sylvian spikes suggests a complex pattern of spike propagation in TLE. Significance: ECD orientation of central and interhemispheric spikes in MEG may predict the epileptogenic side.
Sensitivity of scalp 10-20 EEG and magnetoencephalography
Epileptic disorders : international epilepsy journal with videotape, 2013
Although previous studies have investigated the sensitivity of electroencephalography (EEG) and magnetoencephalography (MEG) to detect spikes by comparing simultaneous recordings, there are no published reports that focus on the relationship between spike dipole orientation or sensitivity of scalp EEG/MEG and the "gold standard" of intracranial recording (stereotactic EEG). We evaluated two patients with focal epilepsy; one with lateral temporal focus and the other with insular focus. Two MEG recordings were performed for both patients, each recorded simultaneously with initially scalp EEG, based on international 10-20 electrode placement with additional electrodes for anterior temporal regions, and subsequently stereotactic EEG. Localisation of MEG spike dipoles from both studies was concordant and all MEG spikes were detected by stereotactic EEG. For the patient with lateral temporal epilepsy, spike sensitivity of MEG and scalp EEG (relative to stereotactic EEG) was 55 a...
The Tohoku Journal of Experimental Medicine, 2004
Interictal spikes in patients with epilepsy may be detected by either electroencephalography (EEG) (E-spikes) or magnetoencephalography (MEG) (M-spikes), or both MEG and EEG (E/M-spikes). Localization and amplitude were compared between E/M-spikes and M-spikes in 7 adult patients with extratemporal epilepsy to evaluate the clinical signiicance of MEG spikes. MEG and EEG were simultaneously measured using a helmet-shaped MEG system with planar-type gradiometers and scalp electrodes of the international 10-20 system. Sources of E/M-spikes and M-spikes were estimated by an equivalent current dipole (ECD) model for MEG at peak latency. Each subject showed 9 to 20 (mean 13.4) E/M-spikes and 9 to 31 (mean 16.3) M-spikes. No subjects showed signiicant differences in the ECD locations between E/M-and M-spikes. ECD moments of the E/M-spikes were signiicantly larger in 2 patients and not signiicantly different in the other 5 patients. The similar localizations of E/M-spikes and M-spikes suggest that combination of MEG and EEG is useful to detect more interictal spikes in patients with extratemporal epilepsy. The smaller tendency of ECD amplitude of the M-spikes than E/M-spikes suggests that scalp EEG may overlook small tangential spikes due to background brain noise. Localization value of M-spikes is clinically equivalent to that of E/M-spikes. magnetoencephalography; electroencephalography; epilepsy; interictal spike; equivalent current dipole
Neuromagnetic field modeling of multiple brain regions producing interictal spikes in human epilepsy
Electroencephalography and clinical neurophysiology, 1989
A method of spatiotemporal analysis, using multiple current dipoles to represent activity in multiple brain regions, was applied to the interpretation of extracranial neuromagnetic fields generated by epileptic spikes in patients with focal seizure disorders. This method permitted the identification and approximate localization of cellular currents within single and multiple brain regions engaged over the entire duration of the human epileptic spike complex. These results suggest that spatially and temporally overlapping electrical currents in human epileptic cortex may be investigated non-invasively in the magnetoencephalogram if appropriate physical models are applied.
MEG Versus EEG: Influence of Background Activity on Interictal Spike Detection
Journal of Clinical Neurophysiology, 2006
The comparative sensitivity of EEG and magnetoencephalography (MEG) in the visual detection of focal epileptiform activity in simultaneous interictal sleep recordings were investigated. The authors examined 14 patients aged 3.5 to 17 years with localization-related epilepsy. Simultaneous 122-channel whole-head MEG and 33-channel EEG were recorded for 20 to 40 minutes during spontaneous sleep. The EEG and MEG data were separated and four blinded independent reviewers marked the presence and timing of epileptic discharges (ED) in the 28 data segments. EEG and MEG data were matched and spikes identified by at least three reviewers were classified in three categories according to the following criteria: type 1 MEG Ͼ EEG, type 2 EEG Ͼ MEG (type 1/2: difference of three or more raters), and type 3 EEG ϭ MEG (three or more raters each). The presence of simultaneous sleep changes was visually determined for every single EEG-segment. Spikes with high spatiotemporal correlation were averaged and subjected to single dipole analysis of peak activity in EEG. Out of 4704 marked patterns, 1387 spikes fulfilled the above criteria. In fact, more spikes were unique to MEG (689) than to EEG (136) and to the combination of both modalities (562). ED were detected predominantly by MEG in eight patients and by EEG in two patients. The presence of vertex waves and spindles lead to a significantly higher number of spikes identified only in MEG. Averaging of type 1 spikes produced clear spike activity in EEG in 9 of 12 cases. On the contrary, only 2 of 10 type 2 spikes were visible in MEG after averaging. Dipoles of spikes visible in MEG showed a more tangential orientation compared with more radial dipoles of type 2 spikes. Spike characteristics, e.g., dipole orientation, are a key factor for a sole EEG representation. Exclusive MEG detection is more likely influenced by overlapping background activity in EEG. Because MEG is indifferent to radial activity, i.e., sleep changes, a higher ratio of spikes unique to MEG compared with EEG is detected in the case of overlapping sleep changes.
Localization of Interictal Epileptic Spikes With MEG
Journal of Clinical Neurophysiology, 2016
OBJECTIVE-To describe and optimize an automated beamforming technique followed by identification of locations with excess kurtosis (g2) for efficient detection and localization of interictal spikes in medically refractory epilepsy patients. METHODS-Synthetic Aperture Magnetometry with g2 averaged over a sliding time window (SAMepi) was performed in 7 focal epilepsy patients and 5 healthy volunteers. The effect of varied window lengths on detection of spiking activity was evaluated. RESULTS-Sliding window lengths of 0.5-10 seconds performed similarly, with 0.5 and 1 second windows detecting spiking activity in one of the 3 virtual sensor locations with highest kurtosis. These locations were concordant with the region of eventual surgical resection in these 7 patients who remained seizure free at one year. Average g2 values increased with increasing sliding window length in all subjects. In healthy volunteers kurtosis values stabilized in datasets longer than two minutes. CONCLUSIONS-SAMepi using g2 averaged over 1 second sliding time windows in datasets of at least 2 minutes duration reliably identified interictal spiking and the presumed seizure focus in these 7 patients. Screening the 5 locations with highest kurtosis values for spiking activity is an efficient and accurate technique for localizing interictal activity using MEG. SIGNIFICANCE-SAMepi should be applied using the parameter values and procedure described for optimal detection and localization of interictal spikes. Use of this screening procedure could significantly improve the efficiency of MEG analysis if clinically validated.
Neuroimage, 2008
Although interictal epileptic spikes are defined as fast transient activity, the spatial distribution of spike-related high-frequency power changes is unknown. In this study, we localized the sources of spikelocked power increases in the beta and gamma band with magnetoencephalography and an adaptive spatial filtering technique and tested the usefulness of these reconstructions for determining the epileptogenic zone in a population of 27 consecutive presurgical patients with medication refractory partial epilepsies. The reliability of this approach was compared to the performance of conventional MEG techniques such as equivalent current dipole (ECD) models. In patients with good surgical outcome after a mean follow-up time of 16 months (Engel class I or II), the surgically resected area was identified with an accuracy of 85% by sources of spike-locked beta/gamma activity, which compared favorably with the accuracy of 69% found for ECD models of single spikes. In patients with a total of more than 50 spikes in their recordings, the accuracies increased to 100% vs. 88%, respectively. Imaging of spike-locked beta/gamma power changes therefore seems to be a reliable and fast alternative to conventional MEG techniques for localizing epileptogenic tissue, in particular, if more than 50 interictal spikes can be recorded.