Dipole localization for identification of neuronal generators in independent neighboring interictal EEG spike foci

Dipole source localization of mouse electroencephalogram using the Fieldtrip toolbox

The mouse model is an important research tool in neurosciences to examine brain function and diseases with genetic perturbation in different brain regions. However, the limited techniques to map activated brain regions under specific experimental manipulations has been a drawback of the mouse model compared to human functional brain mapping. Here, we present a functional brain mapping method for fast and robust in vivo brain mapping of the mouse brain. The method is based on the acquisition of high density electroencephalography (EEG) with a microarray and EEG source estimation to localize the electrophysiological origins. We adapted the Fieldtrip toolbox for the source estimation, taking advantage of its software openness and flexibility in modeling the EEG volume conduction. Three source estimation techniques were compared: Distribution source modeling with minimum-norm estimation (MNE), scanning with multiple signal classification (MUSIC), and single-dipole fitting. Known sources to evaluate the performance of the localization methods were provided using optogenetic tools. The accuracy was quantified based on the receiver operating characteristic (ROC) analysis. The mean detection accuracy was high, with a false positive rate less than 1.3% and 7% at the sensitivity of 90% plotted with the MNE and MUSIC algorithms, respectively. The mean center-to-center distance was less than 1.2 mm in single dipole fitting algorithm. Mouse microarray EEG source localization using microarray allows a reliable method for functional brain mapping in awake mouse opening an access to cross-species study with human brain.

Focal Peak Activities in Spread of Interictal-Ictal Discharges in Epilepsy with Beamformer MEG: Evidence for an Epileptic Network?

Non-invasive studies to predict regions of seizure onset are important for planning intracranial grid locations for invasive cortical recordings prior to resective surgery for patients with medically intractable epilepsy. The neurosurgeon needs to know both the seizure onset zone (SOZ) and the region of immediate cortical spread to determine the epileptogenic zone to be resected. The immediate zone of spread may be immediately adjacent, on a nearby gyrus, in a different lobe, and sometimes even in the contralateral cerebral hemisphere. We reviewed consecutive simultaneous EEG/MEG recordings on 162 children with medically intractable epilepsy. We analyzed the MEG signals in the bandwidth 20-70 Hz with a beamformer algorithm, synthetic aperture magnetometry, at a 2.5 mm voxel spacing throughout the brain (virtual sensor locations, VSLs) with the kurtosis statistic (g 2) to determine presence of excess kurtosis (γ2) consistent with intermittent increased high frequency spikiness of the background. The MEG time series was reconstructed (virtual sensor signals) at each of these VSLs. The VS signals were further examined with a relative peak amplitude spike detection algorithm. The time of VS spike detection was compared to the simultaneous EEG and MEG sensor signals for presence of conventional epileptiform spike morphology in the latter signals. The time of VS spike detection was compared across VSLs to determine earliest and last VSL to show a VS spike. Seven subjects showed delay in activation across VS locations detectable on visual examination. We compared the VS locations that showed earliest and later VS spikes with the locations on intracranial grid locations by electrocorticography (ECoG) that showed spikes and both onset and spread of seizures. We compared completeness of resection of VS locations to postoperative outcome. The VS locations for spike onset and spread were similar to locations for ictal onset and spread by ECoG.

Review on solving the inverse problem in EEG source analysis

In this primer, we give a review of the inverse problem for EEG source localization. This is intended for the researchers new in the field to get insight in the state-of-the-art techniques used to find approximate solutions of the brain sources giving rise to a scalp potential recording. Furthermore, a review of the performance results of the different techniques is provided to compare these different inverse solutions. The authors also include the results of a Monte-Carlo analysis which they performed to compare four non parametric algorithms and hence contribute to what is presently recorded in the literature. An extensive list of references to the work of other researchers is also provided. This paper starts off with a mathematical description of the inverse problem and proceeds to discuss the two main categories of methods which were developed to solve the EEG inverse problem, mainly the non parametric and parametric methods. The main difference between the two is to whether a fixed number of dipoles is assumed a priori or not. Various techniques falling within these categories are described including minimum norm estimates and their generalizations, LORETA, sLORETA, VARETA, S-MAP, ST-MAP, Backus-Gilbert, LAURA, Shrinking LORETA FOCUSS (SLF), SSLOFO and ALF for non parametric methods and beamforming techniques, BESA, subspace techniques such as MUSIC and methods derived from it, FINES, simulated annealing and computational intelligence algorithms for parametric methods. From a review of the performance of these techniques as documented in the literature, one could conclude that in most cases the LORETA solution gives satisfactory results. In situations involving clusters of dipoles, higher resolution algorithms such as MUSIC or FINES are however preferred. Imposing reliable biophysical and psychological constraints, as done by LAURA has given superior results. The Monte-Carlo analysis performed, comparing WMN, LORETA, sLORETA and SLF, for different noise levels and different simulated source depths has shown that for single source localization, regularized sLORETA gives the best solution in terms of both localization error and ghost sources. Furthermore the computationally intensive solution given by SLF was not found to give any additional benefits under such simulated conditions.

Magnetoencephalography Is More Successful for Screening and Localizing Frontal Lobe Epilepsy than Electroencephalography

PURPOSE

The diagnosis of frontal lobe epilepsy may be compounded by poor electroclinical localization, due to distributed or rapidly propagating epileptiform activity. This study aimed at developing optimal procedures for localizing interictal epileptiform discharges (IEDs) of patients with localization related epilepsy in the frontal lobe. To this end the localization results obtained for magnetoencephalography (MEG) and electroencephalography (EEG) were compared systematically using automated analysis procedures.

METHODS

Simultaneous recording of interictal EEG and MEG was successful for 18 out of the 24 patients studied. Visual inspection of these recordings revealed IEDs with varying morphology and topography. Cluster analysis was used to classify these discharges on the basis of their spatial distribution followed by equivalent dipole analysis of the cluster averages. The locations of the equivalent dipoles were compared with the location of the epileptogenic lesions of the patient or, if these were not visible at MRI with the location of the interictal onset zones identified by subdural electroencephalography.

RESULTS

Generally IEDs were more abundantly in MEG than in the EEG recordings. Furthermore, the duration of the MEG spikes, measured from the onset till the spike maximum, was in most patients shorter than the EEG spikes. In most patients, distinct spike subpopulations were found with clearly different topographical field maps. Cluster analysis of MEG spikes followed by dipole localization was successful (n = 14) for twice as many patients as for EEG source analysis (n = 7), indicating that the localizability of interictal MEG is much better than of interictal EEG.

CONCLUSIONS

The automated procedures developed in this study provide a fast screening method for identifying the distinct categories of spikes and the brain areas responsible for these spikes. The results show that MEG spike yield and localization is superior compared with EEG. This finding is of importance for the diagnosis and preoperative evaluation of patients with frontal lobe epilepsy.

Analysis of EEG–fMRI data in focal epilepsy based on automated spike classification and Signal Space Projection

Simultaneous acquisition of EEG and fMRI data enables the investigation of the hemodynamic correlates of interictal epileptiform discharges (IEDs) during the resting state in patients with epilepsy. This paper addresses two issues: (1) the semi-automation of IED classification in statistical modelling for fMRI analysis and (2) the improvement of IED detection to increase experimental fMRI efficiency. For patients with multiple IED generators, sensitivity to IED-correlated BOLD signal changes can be improved when the fMRI analysis model distinguishes between IEDs of differing morphology and field. In an attempt to reduce the subjectivity of visual IED classification, we implemented a semi-automated system, based on the spatio-temporal clustering of EEG events. We illustrate the technique's usefulness using EEG-fMRI data from a subject with focal epilepsy in whom 202 IEDs were visually identified and then clustered semi-automatically into four clusters. Each cluster of IEDs was modelled separately for the purpose of fMRI analysis. This revealed IED-correlated BOLD activations in distinct regions corresponding to three different IED categories. In a second step, Signal Space Projection (SSP) was used to project the scalp EEG onto the dipoles corresponding to each IED cluster. This resulted in 123 previously unrecognised IEDs, the inclusion of which, in the General Linear Model (GLM), increased the experimental efficiency as reflected by significant BOLD activations. We have also shown that the detection of extra IEDs is robust in the face of fluctuations in the set of visually detected IEDs. We conclude that automated IED classification can result in more objective fMRI models of IEDs and significantly increased sensitivity.

Identifying the primary epileptogenic hemisphere from electroencephalographic (EEG) and magnetoencephalographic dipole lateralizations in children with intractable epilepsy

We used electroencephalographic (EEG) and magnetoencephalographic dipole lateralizations to identify the primary epileptogenic hemisphere in 41 children with intractable localization-related epilepsy. We compared EEG and magnetoencephalographic dipole lateralizations, EEG ictal onsets, and magnetic resonance images (MRIs). Concordant lateralization of EEG and magnetoencephalographic dipoles (> 50% of each lateralizing to the same hemisphere) occurred in 34 patients, with EEG ictal onsets in the same hemisphere in 23 (68%) and concordant MRI lesions in 23 (68%). Focal resection in 16 of 20 patients resulted in a good surgical outcome. Of the seven children with nonconcordant magnetoencephalographic and EEG lateralizations, one (14%) had EEG ictal onset and one (14%) had MRI lesions that lateralized; none had surgery. The relationship between lateralized EEG and magnetoencephalographic dipoles forecasts surgical candidacy. Concordant lateralizations predict good seizure control after surgery by identifying the primary epileptogenic hemisphere. Discordant lateralizations signify an undetermined epileptogenic hemisphere and contraindicate surgery without further testing.

Detection of Interictal Spikes and Artifactual Data Through Orthogonal Transformations

This study introduces an integrated algorithm based on the Walsh transform to detect interictal spikes and artifactual data in epileptic patients using recorded EEG data. The algorithm proposes a unique mathematical use of Walsh-transformed EEG signals to identify those criteria that best define the morphologic characteristics of interictal spikes. EEG recordings were accomplished using the 10-20 system interfaced with the Electrical Source Imaging System with 256 channels (ESI-256) for enhanced preprocessing and on-line monitoring and visualization. The merits of the algorithm are: (1) its computational simplicity; (2) its integrated design that identifies and localizes interictal spikes while automatically removing or discarding the presence of different artifacts such as electromyography, electrocardiography, and eye blinks; and (3) its potential implication to other types of EEG analysis, given the mathematical basis of this algorithm, which can be patterned or generalized to other brain dysfunctions. The mathematics that were applied here assumed a dual role, that of transforming EEG signals into mutually independent bases and in ascertaining quantitative measures for those morphologic characteristics deemed important in the identification process of interictal spikes. Clinical experiments involved 31 patients with focal epilepsy. EEG data collected from 10 of these patients were used initially in a training phase to ascertain the reliability of the observable and formulated features that were used in the spike detection process. Three EEG experts annotated spikes independently. On evaluation of the algorithm using the 21 remaining patients in the testing phase revealed a precision (positive predictive value) of 92% and a sensitivity of 82%. Based on the 20- to 30-minute epochs of continuous EEG recording per subject, the false detection rate is estimated at 1.8 per hour of continuous EEG. These are positive results that support further development of this algorithm for prolonged EEG recordings on ambulatory subjects and to serve as a support mechanism to the decisions made by EEG experts.

Dipole analysis in panayiotopoulos syndrome

Panayiotopoulos syndrome (PS) is a type of benign childhood partial epilepsy, which has a good prognosis despite the fact that it is frequently associated with abundant multifocal spikes on the electroencephalography (EEG). We investigated whether stable dipoles, as seen in rolandic epilepsy, were also present in PS. We performed dipole analysis of the interictal spike discharges seen in the interictal EEGs of eight children with PS. We chose more than 10 spikes for each kind of spike, and investigated whether or not more than three of these spikes showed consistently stable dipole locations. (1) We observed 15 different kinds of spikes in various regions in the EEGs of the eight children. (2) Twelve of the 15 kinds of spikes had dipoles with a high goodness of fit. Furthermore, 14 of the 15 spikes had stable dipoles with similar locations for more than three individual spikes. (3) Fourteen of the 15 spikes, including frontal spikes, showed dense dipole locations in the mesial occipital area. Thirteen of these 14 spikes also showed other dipole locations in the rolandic area and/or the vertex (Cz). Our study revealed that the various types of spikes observed in PS have similar and stable dipole locations. The dipoles showing high stability, were located in the mesial occipital area, and were accompanied by dipoles located in the rolandic area. The stability and location of these dipoles indicate that there may be a pathogenetic link between PS and rolandic epilepsy.

Controversies in clinical neurophysiology. MEG is superior to EEG in the localization of interictal epileptiform activity: Con

OBJECTIVE

To assess whether MEG is superior to scalp-EEG in the localization of interictal epileptiform activity and to stress the 'con' part in this controversy.

METHODS

Advantages and disadvantages of the two techniques were systematically reviewed.

RESULTS

While MEG and EEG complement each other for the detection of interictal epileptiform discharges, EEG offers the advantage of long-term recording significantly increasing its diagnostic yield which is not feasible with MEG. Localization accuracies of EEG and MEG are comparable once inaccuracies for the solution of the forward problem are eliminated. MEG may be more sensitive for the detection of neocortical spike sources. EEG and MEG source localizations show comparable agreement with invasive electrical recordings, can clarify the spatial relationship between the irritative zone and structural lesions, guide the placement of invasive electrodes and attribute epileptic activity to lobar subcompartments in temporal lobe epilepsy and to a lesser extent in extratemporal epilepsy.

CONCLUSIONS

A clear superiority of MEG over EEG for the localization of interictal epileptiform activity cannot be derived from the studies presently available.

SIGNIFICANCE

The combination of EEG and MEG provides information for the localization of interictal epileptiform activity which cannot be obtained with either technique alone.

A review of neurophysiological testing

The rapid advances in the technology of, and accumulation of pertinent data in, electrophysiological testing has increased exponentially in the past decade. This is attributable to continued advances in computer technology, biomedical engineering, and now the coregistration of the electrophysiological data with neuroimaging results. Knowledge of normal function and electrophysiological response at rest or on stimulation of the central and peripheral nervous systems is important to the neurosurgeon. Only by a basic understanding of normal and abnormal recordings may diagnoses and localizations be achieved. Intraspinal and intracranial surgical procedures are predicated on nontrauma to the neuraxis. This can be accomplished by performing electrophysiological testing to monitor the function of the spinal and cranial nerves, spinal cord, brainstem, basal ganglia, and cerebrum. If the surgeon cannot delineate critical cortex or pathways, he or she will be unable to avoid these areas in the patient.

Propagation of Interictal Epileptiform Activity Can Lead to Erroneous Source Localizations: A 128-Channel EEG Mapping Study

The relationship between interictal epileptiform activity and the epileptogenic zone is complex. Despite the fact that intraspike propagation may occur, the peak of the spike is often used as indicator of the site of ictal onset. In this investigation, spatio-temporal segmentation was used to demonstrate this intraspike propagation and to determine at which time point the voltage pattern corresponded best to the epileptogenic zone. Sixteen patients with focal epilepsy were recorded with 125-channel EEG. Between one and five different map topographies were identified during the rising phase of the spike. A distributed source model (EPIFOCUS) was used to localize the source of each map, and the distance from the EPIFOCUS maximum to the anatomic lesion was calculated. In only 3 of 16 cases was the entire rising phase of the spike accounted for by one single map. In another five patients, several maps were obtained, although all were located within the epileptogenic lesion. In the remaining eight patients, however, parts of the rising phase had locations outside the epileptogenic lesion. On the average, 80% of the rising time had within lesion locations the most reliable time period being halfway between onset and peak. The results illustrate that intraspike propagation has to be considered in source localizations, and they also illustrate the usefulness of spatio-temporal segmentation for visualizing this propagation.

MEG and EEG in epilepsy

Both EEG and magnetoencephalogram (MEG), with a time resolution of 1 ms or less, provide unique neurophysiologic data not obtainable by other neuroimaging techniques. MEG has now emerged as a mature clinical technology. While both EEG and MEG can be performed with more than 100 channels, MEG recordings with 100 to 300 channels are more easily done because of the time needed to apply a large number of EEG electrodes. EEG has the advantage of the long-term video EEG recordings, which facilitates extensive temporal sampling across all periods of the sleep/wake cycle. MEG and EEG seem to complement each other for the detection of interictal epileptiform discharges, because some spikes can be recorded only on MEG but not on EEG and vice versa. Most studies indicate that MEG seems to be more sensitive for neocortical spike sources. Both EEG and MEG source localizations show excellent agreement with invasive electrical recordings, clarify the spatial relationship between the irritative zone and structural lesions, and finally, attribute epileptic activity to lobar subcompartments in temporal lobe and to a lesser extent in extratemporal epilepsies. In temporal lobe epilepsy, EEG and MEG can differentiate between patients with mesial, lateral, and diffuse seizure onsets. MEG selectively detects tangential sources. EEG measures both radial and tangential activity, although the radial components dominate the EEG signals at the scalp. Thus, while EEG provides more comprehensive information, it is more complicated to model due to considerable influences of the shape and conductivity of the volume conductor. Dipole localization techniques favor MEG due to the higher accuracy of MEG source localization compared to EEG when using the standard spherical head shape model. However, if special care is taken to address the above issues and enhance the EEG, the localization accuracy of EEG and MEG actually are comparable, although these surface EEG analytic techniques are not typically approved for clinical use in the United States. MEG dipole analysis is approved for clinical use and thus gives information that otherwise usually requires invasive intracranial EEG monitoring. There are only a few dozen whole head MEG units in operation in the world. While EEG is available in every hospital, specialized EEG laboratories capable of source localization techniques are nearly as scarce as MEG facilities. The combined use of whole-head MEG systems and multichannel EEG in conjunction with advanced source modeling techniques is an area of active development and will allow a better noninvasive characterization of the irritative zone in presurgical epilepsy evaluation. Finally, additional information on epilepsy may be gathered by either MEG or EEG analysis of data beyond the usual bandwidths used in clinical practice, namely by analysis of activity at high frequencies and near-DC activity.

Characteristics of dipoles in clustered individual spikes and averaged spikes

The aim of this study is to analyze the characteristics of dipoles in clustered individual spikes and averaged spikes, we compared electroencephalography (EEG) dipole localizations from patients with intractable extratemporal lobe epilepsy (IETLE) and from patients with benign epilepsy with centrotemporal spikes (BECTS). We studied 10 patients; five with IETLE who underwent epilepsy surgery after subdural EEG and five with BECTS. We recorded 19-channel digital scalp EEGs and used clustering analysis for individual spikes to characterize interictal spikes. We selected and averaged one representative spike group at the maximum negative peak electrode. We used a single dipole method with three-shell spherical head model. We compared dipole localizations of both averaged and individual spikes.IETLE data had more identifiable spike clusters and fewer spikes in each cluster than BECTS (P<0.05). Dipole sources with goodness-of-fit >or=95% in averaged spikes were less frequent in IETLE than in BECTS (P<0.05). For IETLE, averaged spikes showed no dipoles (two patients), while individual spikes gave dipole sources reliably in the epileptic region. For BECTS, individual and averaged spike sources were clustered. More than 80% of dipoles in averaged spikes were stable, in close proximity, for prolonged periods in BECTS. More spike groups after clustering and fewer acceptable dipoles from averaged spikes in IETLE reflect variable spike activity over extensive epileptic regions. Fewer spike groups producing more acceptable dipoles in BECTS correlate with stable spike sources within the isolated epileptic central region. Characteristics of clustered interictal spikes need careful examination before the use of dipole analysis of averaged spikes for epilepsy evaluation.