Defining epileptogenic foci: past, present, future

EEG/MEG source imaging of deep brain activity within the maximum entropy on the mean framework: Simulations and validation in epilepsy

Electro/Magneto-EncephaloGraphy (EEG/MEG) source imaging (EMSI) of epileptic activity from deep generators is often challenging due to the higher sensitivity of EEG/MEG to superficial regions and to the spatial configuration of subcortical structures. We previously demonstrated the ability of the coherent Maximum Entropy on the Mean (cMEM) method to accurately localize the superficial cortical generators and their spatial extent. Here, we propose a depth-weighted adaptation of cMEM to localize deep generators more accurately. These methods were evaluated using realistic MEG/high-density EEG (HD-EEG) simulations of epileptic activity and actual MEG/HD-EEG recordings from patients with focal epilepsy. We incorporated depth-weighting within the MEM framework to compensate for its preference for superficial generators. We also included a mesh of both hippocampi, as an additional deep structure in the source model. We generated 5400 realistic simulations of interictal epileptic discharges for MEG and HD-EEG involving a wide range of spatial extents and signal-to-noise ratio (SNR) levels, before investigating EMSI on clinical HD-EEG in 16 patients and MEG in 14 patients. Clinical interictal epileptic discharges were marked by visual inspection. We applied three EMSI methods: cMEM, depth-weighted cMEM and depth-weighted minimum norm estimate (MNE). The ground truth was defined as the true simulated generator or as a drawn region based on clinical information available for patients. For deep sources, depth-weighted cMEM improved the localization when compared to cMEM and depth-weighted MNE, whereas depth-weighted cMEM did not deteriorate localization accuracy for superficial regions. For patients' data, we observed improvement in localization for deep sources, especially for the patients with mesial temporal epilepsy, for which cMEM failed to reconstruct the initial generator in the hippocampus. Depth weighting was more crucial for MEG (gradiometers) than for HD-EEG. Similar findings were found when considering depth weighting for the wavelet extension of MEM. In conclusion, depth-weighted cMEM improved the localization of deep sources without or with minimal deterioration of the localization of the superficial sources. This was demonstrated using extensive simulations with MEG and HD-EEG and clinical MEG and HD-EEG for epilepsy patients.

EEG Source Imaging-Clinical Considerations for EEG Acquisition and Signal Processing for Improved Temporo-Spatial Resolution

SUMMARY

EEG source imaging (ESI) has gained traction in recent years as a useful clinical tool for the noninvasive surgical work-up of patients with drug-resistant focal epilepsy. Despite its proven benefits for the temporo-spatial modeling of spike and seizure sources, ESI remains widely underused in clinical practice. This partly relates to a lack of clarity around an optimal approach to the acquisition and processing of scalp EEG data for the purpose of ESI. Here, we describe some of the practical considerations for the clinical application of ESI. We focus on patient preparation, the impact of electrode number and distribution across the scalp, the benefit of averaging raw data for signal analysis, and the relevance of modeling different phases of the interictal discharge as it evolves from take-off to peak. We emphasize the importance of recording high signal-to-noise ratio data for reliable source analysis. We argue that the accuracy of modeling cortical sources can be improved using higher electrode counts that include an inferior temporal array, by averaging interictal waveforms rather than limiting ESI to single spike analysis, and by careful interrogation of earlier phase components of these waveforms. No amount of postacquisition signal processing or source modeling sophistication, however, can make up for suboptimally recorded scalp EEG data in a poorly prepared patient.

EEG Source Imaging in Presurgical Evaluations

SUMMARY

Presurgical evaluations to plan intracranial EEG implantations or surgical therapies at most epilepsy centers in the United States currently depend on the visual inspection of EEG traces. Such analysis is inadequate and does not exploit all the localizing information contained in scalp EEG. Various types of EEG source modeling or imaging can provide sublobar localization of spike and seizure sources in the brain, and the software to do this with typical long-term monitoring EEG data are available to all epilepsy centers. This article reviews the fundamentals of EEG voltage fields that are used in EEG source imaging, the strengths and weakness of dipole and current density source models, the clinical situations where EEG source imaging is most useful, and the particular strengths of EEG source imaging for various cortical areas where spike/seizure sources are likely.

In vivo laser speckle contrast imaging of 4-aminopyridine- or pentylenetetrazole-induced seizures

Clinical and preclinical studies on epileptic seizures are closely linked to the study of neurovascular coupling. Obtaining reliable information about cerebral blood flow (CBF) in the area of epileptic activity through minimally invasive techniques is crucial for research in this field. In our studies, we used laser speckle contrast imaging (LSCI) to gather information about the local blood circulation in the area of epileptic activity. We used two models of epileptic seizures: one based on 4-aminopyridine (4-AP) and another based on pentylenetetrazole (PTZ). We verified the duration of an epileptic seizure using electrocorticography (ECoG). We applied the antiepileptic drug topiramate (TPM) to both models, but its effect was different in each case. However, in both models, TPM had an effect on neurovascular coupling in the area of epileptic activity, as shown by both LSCI and ECoG data. We demonstrated that TPM significantly reduced the amplitude of 4-AP-induced epileptic seizures (4-AP+TPM: 0.61 ± 0.13 mV vs 4-AP: 1.08 ± 0.19 mV; p < 0.05), and it also reduced gamma power in ECoG in PTZ-induced epileptic seizures (PTZ+TPM: 38.5% ± 11.9% of the peak value vs PTZ: 59.2% ± 3.0% of peak value; p < 0.05). We also captured the pattern of CBF changes during focal epileptic seizures induced by 4-AP. Our data confirm that the system of simultaneous cortical LSCI and registration of ECoG makes it possible to evaluate the effectiveness of pharmacological agents in various types of epileptic seizures in in vivo models and provides spatial and temporal information on the process of ictogenesis.

Personalized tDCS for Focal Epilepsy—A Narrative Review: A Data-Driven Workflow Based on Imaging and EEG Data

Conventional transcranial electric stimulation(tES) using standard anatomical positions for the electrodes and standard stimulation currents is frequently not sufficiently selective in targeting and reaching specific brain locations, leading to suboptimal application of electric fields. Recent advancements in in vivo electric field characterization may enable clinical researchers to derive better relationships between the electric field strength and the clinical results. Subject-specific electric field simulations could lead to improved electrode placement and more efficient treatments. Through this narrative review, we present a processing workflow to personalize tES for focal epilepsy, for which there is a clear cortical target to stimulate. The workflow utilizes clinical imaging and electroencephalography data and enables us to relate the simulated fields to clinical outcomes. We review and analyze the relevant literature for the processing steps in the workflow, which are the following: tissue segmentation, source localization, and stimulation optimization. In addition, we identify shortcomings and ongoing trends with regard to, for example, segmentation quality and tissue conductivity measurements. The presented processing steps result in personalized tES based on metrics like focality and field strength, which allow for correlation with clinical outcomes.

Fast periodic visual stimulation to highlight the relationship between human intracerebral recordings and scalp electroencephalography

Despite being of primary importance for fundamental research and clinical studies, the relationship between local neural population activity and scalp electroencephalography (EEG) in humans remains largely unknown. Here we report simultaneous scalp and intracerebral EEG responses to face stimuli in a unique epileptic patient implanted with 27 intracerebral recording contacts in the right occipitotemporal cortex. The patient was shown images of faces appearing at a frequency of 6 Hz, which elicits neural responses at this exact frequency. Response quantification at this frequency allowed to objectively relate the neural activity measured inside and outside the brain. The patient exhibited typical 6 Hz responses on the scalp at the right occipitotemporal sites. Moreover, there was a clear spatial correspondence between these scalp responses and intracerebral signals in the right lateral inferior occipital gyrus, both in amplitude and in phase. Nevertheless, the signal measured on the scalp and inside the brain at nearby locations showed a 10-fold difference in amplitude due to electrical insulation from the head. To further quantify the relationship between the scalp and intracerebral recordings, we used an approach correlating time-varying signals at the stimulation frequency across scalp and intracerebral channels. This analysis revealed a focused and right-lateralized correspondence between the scalp and intracerebral recordings that were specific to the face stimulation is more broadly distributed in various control situations. These results demonstrate the interest of a frequency tagging approach in characterizing the electrical propagation from brain sources to scalp EEG sensors and in identifying the cortical sources of brain functions from these recordings.

Atypical Interictal Epileptiform Discharges in Electroencephalography

Background and Purpose

A great deal of attention has been focused on “typical” interictal epileptiform discharges (IEDs) in the electroencephalography (EEG) literature. However, there is a paucity of data on “atypical” IEDs, namely, positive sharp waves (PSWs), focal triphasic sharp waves and spikes (FTSWs), sharp slow waves (SSWs), bifid spikes, and “notched” delta. In this present study, we sought to address the pathophysiology, characteristics, and diagnostic significance of “atypical” IEDs in clinical neuroscience.

Methods

We prospectively reviewed the EEGs of 1,250 patients from a heterogeneous population over a period of 2 years. We also documented demographic, clinical, and neuroimaging data.

Results

Thirty-one patients had PSWs, 26 had FTSWs, 30 had SSWs, 24 had notched delta, and four had bifid spikes in their EEG data. Ninety-six percent of patients with PSWs had epilepsy whereas 100% of the FTSW and SSW groups had this diagnosis. In the ND group the rate of epilepsy was 95% and in the bifid spike group 75%. Accordingly, “atypical” IEDs are potentially epileptogenic patterns with localizing significance, occurring primarily in younger age groups. We also found that a significant number of these patients had congenital central nervous system anomalies.

Conclusions

We conclude that “atypical” IEDs are rare and under-reported EEG patterns that potentially signify focal epileptogenicity. Our data also stresses the significance of neuroimaging in investigating the possibility of an underlying congenital central nervous system anomaly in this population.

Multi-Scale Neural Sources of EEG: Genuine, Equivalent, and Representative. A Tutorial Review

A biophysical framework needed to interpret electrophysiological data recorded at multiple spatial scales of brain tissue is developed. Micro current sources at membrane surfaces produce local field potentials, electrocorticography, and electroencephalography (EEG). We categorize multi-scale sources as genuine, equivalent, or representative. Genuine sources occur at the micro scale of cell surfaces. Equivalent sources provide identical experimental outcomes over a range of scales and applications. In contrast, each representative source distribution is just one of many possible source distributions that yield similar experimental outcomes. Macro sources ("dipoles") may be defined at the macrocolumn (mm) scale and depend on several features of the micro sources-magnitudes, micro synchrony within columns, and distribution through the cortical depths. These micro source properties are determined by brain dynamics and the columnar structure of cortical tissue. The number of representative sources underlying EEG data depends on the spatial scale of neural tissue under study. EEG inverse solutions (e.g. dipole localization) and high resolution estimates (e.g. Laplacian, dura imaging) have both strengths and limitations that depend on experimental conditions. The proposed theoretical framework informs studies of EEG source localization, source characterization, and low pass filtering. It also facilitates interpretations of brain dynamics and cognition, including measures of synchrony, functional connections between cortical locations, and other aspects of brain complexity.

Multivariate regression methods for estimating velocity of ictal discharges from human microelectrode recordings

OBJECTIVE

Epileptiform discharges, an electrophysiological hallmark of seizures, can propagate across cortical tissue in a manner similar to traveling waves. Recent work has focused attention on the origination and propagation patterns of these discharges, yielding important clues to their source location and mechanism of travel. However, systematic studies of methods for measuring propagation are lacking.

APPROACH

We analyzed epileptiform discharges in microelectrode array recordings of human seizures. The array records multiunit activity and local field potentials at 400 micron spatial resolution, from a small cortical site free of obstructions. We evaluated several computationally efficient statistical methods for calculating traveling wave velocity, benchmarking them to analyses of associated neuronal burst firing.

MAIN RESULTS

Over 90% of discharges met statistical criteria for propagation across the sampled cortical territory. Detection rate, direction and speed estimates derived from a multiunit estimator were compared to four field potential-based estimators: negative peak, maximum descent, high gamma power, and cross-correlation. Interestingly, the methods that were computationally simplest and most efficient (negative peak and maximal descent) offer non-inferior results in predicting neuronal traveling wave velocities compared to the other two, more complex methods. Moreover, the negative peak and maximal descent methods proved to be more robust against reduced spatial sampling challenges. Using least absolute deviation in place of least squares error minimized the impact of outliers, and reduced the discrepancies between local field potential-based and multiunit estimators.

SIGNIFICANCE

Our findings suggest that ictal epileptiform discharges typically take the form of exceptionally strong, rapidly traveling waves, with propagation detectable across millimeter distances. The sequential activation of neurons in space can be inferred from clinically-observable EEG data, with a variety of straightforward computation methods available. This opens possibilities for systematic assessments of ictal discharge propagation in clinical and research settings.

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.

Magnetoencephalography in Preoperative Epileptic Foci Localization: Enlightenment from Cognitive Studies

Over 30% epileptic patients are refractory to medication, who are amenable to neurosurgical treatment. Non-invasive brain imaging technologies including video-electroencephalogram (EEG), magnetic resonance imaging (MRI), and magnetoencephalography (MEG) are widely used in presurgical assessment of epileptic patients. This review mainly discussed the current development of clinical MEG imaging as a diagnose approach, and its correlations with the golden standard intracranial electroencephalogram (iEEG). More importantly, this review discussed the possible applications of functional networks in preoperative epileptic foci localization in future studies.

Magnetoencephalography and New Imaging Modalities in Epilepsy

The success of epilepsy surgery is highly dependent on correctly identifying the entire epileptogenic region. Current state-of-the-art for localizing the extent of surgically amenable areas involves combining high resolution three-dimensional magnetic resonance imaging (MRI) with electroencephalography (EEG) and magnetoencephalography (MEG) source modeling of interictal epileptiform activity. Coupling these techniques with newer quantitative structural MRI techniques, such as cortical thickness measurements, however, may improve the extent to which the abnormal epileptogenic region can be visualized. In this review we assess the utility of EEG, MEG and quantitative structural MRI methods for the evaluation of patients with epilepsy and introduce a novel method for the co-localization of a structural MRI measurement to MEG and EEG source modeling. When combined, these techniques may better identify the extent of abnormal structural and functional areas in patients with medically intractable epilepsy.

A study of the electro-haemodynamic coupling using simultaneously acquired intracranial EEG and fMRI data in humans

In current fMRI studies designed to map BOLD changes related to interictal epileptiform discharges (IED), which are recorded on simultaneous EEG, the information contained in the morphology and field extent of the EEG events is exclusively used for their classification. Usually, a BOLD predictor based on IED onset times alone is constructed, effectively treating all events as identical. We used intracranial EEG (icEEG)-fMRI data simultaneously recorded in humans to investigate the effect of including any of the features: amplitude, width (duration), slope of the rising phase, energy (area under the curve), or spatial field extent (number of contacts over which the sharp wave was observed) of the fast wave of the IED (the sharp wave), into the BOLD model, to better understand the neurophysiological origin of sharp wave-related BOLD changes, in the immediate vicinity of the recording contacts. Among the features considered, the width was the only one found to explain a significant amount of additional variance, suggesting that the amplitude of the BOLD signal depends more on the duration of the underlying field potential (reflected in the sharp wave width) than on the degree of neuronal activity synchrony (reflected in the sharp wave amplitude), and, consequently, that including inter-event variations of the sharp wave width in the BOLD signal model may increase the sensitivity of forthcoming EEG-fMRI studies of epileptic activity.

Spatial co-adaptation of cortical control columns in a micro-ECoG brain-computer interface

OBJECTIVE

Electrocorticography (ECoG) has been used for a range of applications including electrophysiological mapping, epilepsy monitoring, and more recently as a recording modality for brain-computer interfaces (BCIs). Studies that examine ECoG electrodes designed and implanted chronically solely for BCI applications remain limited. The present study explored how two key factors influence chronic, closed-loop ECoG BCI: (i) the effect of inter-electrode distance on BCI performance and (ii) the differences in neural adaptation and performance when fixed versus adaptive BCI decoding weights are used.

APPROACH

The amplitudes of epidural micro-ECoG signals between 75 and 105 Hz with 300 μm diameter electrodes were used for one-dimensional and two-dimensional BCI tasks. The effect of inter-electrode distance on BCI control was tested between 3 and 15 mm. Additionally, the performance and cortical modulation differences between constant, fixed decoding using a small subset of channels versus adaptive decoding weights using the entire array were explored.

MAIN RESULTS

Successful BCI control was possible with two electrodes separated by 9 and 15 mm. Performance decreased and the signals became more correlated when the electrodes were only 3 mm apart. BCI performance in a 2D BCI task improved significantly when using adaptive decoding weights (80%-90%) compared to using constant, fixed weights (50%-60%). Additionally, modulation increased for channels previously unavailable for BCI control under the fixed decoding scheme upon switching to the adaptive, all-channel scheme.

SIGNIFICANCE

Our results clearly show that neural activity under a BCI recording electrode (which we define as a 'cortical control column') readily adapts to generate an appropriate control signal. These results show that the practical minimal spatial resolution of these control columns with micro-ECoG BCI is likely on the order of 3 mm. Additionally, they show that the combination and interaction between neural adaptation and machine learning are critical to optimizing ECoG BCI performance.

Sharp Slow Waves in the EEG

There exists a paucity of data in the EEG literature on characteristics of "atypical" interictal epileptiform discharges (IEDs), including sharp slow waves (SSWs). This article aims to address the clinical, neurophysiological, and neuropathological significance of SSW The EEGs of 920 patients at a tertiary-care facility were prospectively reviewed over a period of one year. Thirty-six patients had SSWs in their EEG. Of these, 6 patients were excluded because of inadequate clinical data. The clinical and neuroimaging data of the remaining 30 patients were then retrospectively collected and reviewed, and the findings were correlated. The data revealed that SSWs were rare and age-related EEG events occurring primarily in the first two decades of life. All patients with SSWs had documented epilepsy, presenting clinically with partial or generalized epilepsy. It is notable that one-third of the patients with SSWs had chronic or static central nervous system (CNS) pathology, particularly congenital CNS anomalies. Though more than one mechanism may be involved in the pathogenesis of SSWs, this research indicates that the most compelling theory is a deeply seated cortical generator giving rise to this EEG pattern. The presence of SSWs should alert clinicians to the presence of partial or generalized epilepsy or an underlying chronic or static CNS pathology, in particular congenital CNS anomalies, underscoring the significance of brain magnetic resonance imaging in the work-up of this population.

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.

Rational manipulation of digital EEG: pearls and pitfalls

The advent of digital EEG has provided greater flexibility and more opportunities in data analysis to optimize the diagnostic yield. Changing the filter settings, sensitivity, montages, and time-base are possible rational manipulations to achieve this goal. The options to use polygraphy, video, and quantification are additional useful features. Aliasing and loss of data are potential pitfalls in the use of digital EEG. This review illustrates some common clinical scenarios where rational manipulations can enhance the diagnostic EEG yield and potential pitfalls in the process.

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.

Patient-specific detection of cerebral blood flow alterations as assessed by arterial spin labeling in drug-resistant epileptic patients

Electrophysiological and hemodynamic data can be integrated to accurately and precisely identify the generators of abnormal electrical activity in drug-resistant focal epilepsy. Arterial Spin Labeling (ASL), a magnetic resonance imaging (MRI) technique for quantitative noninvasive measurement of cerebral blood flow (CBF), can provide a direct measure of variations in cerebral perfusion associated with the epileptic focus. In this study, we aimed to confirm the ASL diagnostic value in the identification of the epileptogenic zone, as compared to electrical source imaging (ESI) results, and to apply a template-based approach to depict statistically significant CBF alterations. Standard video-electroencephalography (EEG), high-density EEG, and ASL were performed to identify clinical seizure semiology and noninvasively localize the epileptic focus in 12 drug-resistant focal epilepsy patients. The same ASL protocol was applied to a control group of 17 healthy volunteers from which a normal perfusion template was constructed using a mixed-effect approach. CBF maps of each patient were then statistically compared to the reference template to identify perfusion alterations. Significant hypo- and hyperperfused areas were identified in all cases, showing good agreement between ASL and ESI results. Interictal hypoperfusion was observed at the site of the seizure in 10/12 patients and early postictal hyperperfusion in 2/12. The epileptic focus was correctly identified within the surgical resection margins in the 5 patients who underwent lobectomy, all of which had good postsurgical outcomes. The combined use of ESI and ASL can aid in the noninvasive evaluation of drug-resistant epileptic patients.

Coating flexible probes with an ultra fast degrading polymer to aid in tissue insertion

We report a fabrication process for coating neural probes with an ultrafast degrading polymer to create consistent and reproducible devices for neural tissue insertion. The rigid polymer coating acts as a probe insertion aid, but resorbs within hours post-implantation. Despite the feasibility for short term neural recordings from currently available neural prosthetic devices, most of these devices suffer from long term gliosis, which isolates the probes from adjacent neurons, increasing the recording impedance and stimulation threshold. The size and stiffness of implanted probes have been identified as critical factors that lead to this long term gliosis. Smaller, more flexible probes that match the mechanical properties of brain tissue could allow better long term integration by limiting the mechanical disruption of the surrounding tissue during and after probe insertion, while being flexible enough to deform with the tissue during brain movement. However, these small flexible probes inherently lack the mechanical strength to penetrate the brain on their own. In this work, we have developed a micromolding method for coating a non-functional miniaturized SU-8 probe with an ultrafast degrading tyrosine-derived polycarbonate (E5005(2K)). Coated, non-functionalized probes of varying dimensions were reproducibly fabricated with high yields. The polymer erosion/degradation profiles of the probes were characterized in vitro. The probes were also mechanically characterized in ex vivo brain tissue models by measuring buckling and insertion forces during probe insertion. The results demonstrate the ability to produce polymer coated probes of consistent quality for future in vivo use, for example to study the effects of different design parameters that may affect tissue response during long term chronic intra-cortical microelectrode neural recordings.

Simultaneous EEG-fMRI in Human Epilepsy

Electroencephalography (EEG) has been used to study and characterize epilepsy for decades, but has a limited ability to localize epileptiform activity to a specific brain region. With recent technological advances, high-quality EEG can now be recorded during functional magnetic resonance imaging (fMRI), which characterizes brain activity through local changes in blood oxygenation. By combining these techniques, the specific timing of interictal events can be identified on the EEG at millisecond resolution and spatially localized with fMRI at millimeter resolution. As a result, simultaneous EEG-fMRI provides the opportunity to better investigate the spatiotemporal mechanisms of the generation of epileptiform activity in the brain. This article discusses the technical considerations and their solutions for recording simultaneous EEG-fMRI and the results of studies to date. It also addresses the application of EEG-fMRI to epilepsy in humans, including clinical applications and ongoing challenges.

A method for the inclusion of sphenoidal electrodes in realistic EEG source imaging

SUMMARY

Although EEG source imaging (ESI) has become more popular over the last few years, sphenoidal electrodes (SPE) have never been incorporated in ESI using realistic head models. This is in part because of the true locations of these electrodes are not exactly known. In this study, we demonstrate the feasibility of determining the true locations of SPE and incorporating this information into realistic ESI. The impact of including these electrodes in ESI in mesial temporal lobe epilepsy is also discussed. Seventeen patients were retrospectively selected for this study. To determine the positions of SPE in each case, two orthogonal x-rays (sagittal and coronal) of the SPE needle stilette were taken in the presence of previously digitized scalp electrodes. An in-house computer program was then used to find the locations of the tip of the needle stilette relative to the surface electrodes. These locations were then incorporated in a realistic head model based on the finite element method. EEG source imaging was then performed using averaged spikes for included patients suspected of having mesial temporal lobe epilepsy. Including SPE significantly shifted the ESI result even in the presence of subtemporal electrodes, resulting in an inferior and mesial displacement.

Focal triphasic sharp waves and spikes in the electroencephalogram

There is a plethora of data in the EEG literature on the characteristics of the most prominent component of interictal epileptiform discharges (IED), namely the negative (fast) phase. Surprisingly, however, little attention has been drawn to the after-coming slow wave (ASW), and its pathological as well as clinical significance. In this paper, we will address the significance of prominent (high amplitude) ASW, giving rise to a triphasic morphology of the IED (focal triphasic sharp waves and spikes—FTSW). We will discuss this EEG pattern with respect to its clinical, neurophysiological, and neuropathological significance. This investigation was conducted on a heterogeneous group of patients at KKH, Ha'il, KSA. Our data revealed that FTSW were rare EEG events occurring primarily in the first two decades of life. Ninety percent of the patients with FTSW had epilepsy, presenting clinically with generalized convulsive seizures, often without partial onset. The majority of these patients responded favorably to anticonvulsant monotherapy. We were surprised to find that half of the patients with FTSW had chronic and/or static CNS pathology, particularly congenital CNS anomalies. Even though more than one mechanism may be involved in the pathogenesis of FTSW, we believe a deeply seated pacemaker as the source of this EEG pattern is the most compelling theory. The presence of FTSW should alert clinicians to the possibility of an underlying chronic and/or static CNS pathology, in particular congenital CNS anomalies, underscoring the significance of neuroimaging in the work-up of this population. Moreover, it is conceivable that the prominent ASW may contribute to the interictal intellectual dysfunction of these patients, justifying aggressive anticonvulsant therapy.

Classification of EEG abnormalities in partial epilepsy with simultaneous EEG-fMRI recordings

Scalp EEG recordings and the classification of interictal epileptiform discharges (IED) in patients with epilepsy provide valuable information about the epileptogenic network, particularly by defining the boundaries of the "irritative zone" (IZ), and hence are helpful during pre-surgical evaluation of patients with severe refractory epilepsies. The current detection and classification of epileptiform signals essentially rely on expert observers. This is a very time-consuming procedure, which also leads to inter-observer variability. Here, we propose a novel approach to automatically classify epileptic activity and show how this method provides critical and reliable information related to the IZ localization beyond the one provided by previous approaches. We applied Wave_clus, an automatic spike sorting algorithm, for the classification of IED visually identified from pre-surgical simultaneous Electroencephalogram-functional Magnetic Resonance Imagining (EEG-fMRI) recordings in 8 patients affected by refractory partial epilepsy candidate for surgery. For each patient, two fMRI analyses were performed: one based on the visual classification and one based on the algorithmic sorting. This novel approach successfully identified a total of 29 IED classes (compared to 26 for visual identification). The general concordance between methods was good, providing a full match of EEG patterns in 2 cases, additional EEG information in 2 other cases and, in general, covering EEG patterns of the same areas as expert classification in 7 of the 8 cases. Most notably, evaluation of the method with EEG-fMRI data analysis showed hemodynamic maps related to the majority of IED classes representing improved performance than the visual IED classification-based analysis (72% versus 50%). Furthermore, the IED-related BOLD changes revealed by using the algorithm were localized within the presumed IZ for a larger number of IED classes (9) in a greater number of patients than the expert classification (7 and 5, respectively). In contrast, in only one case presented the new algorithm resulted in fewer classes and activation areas. We propose that the use of automated spike sorting algorithms to classify IED provides an efficient tool for mapping IED-related fMRI changes and increases the EEG-fMRI clinical value for the pre-surgical assessment of patients with severe epilepsy.

EEG functional connectivity, axon delays and white matter disease

OBJECTIVE

Both structural and functional brain connectivities are closely linked to white matter disease. We discuss several such links of potential interest to neurologists, neurosurgeons, radiologists, and non-clinical neuroscientists.

METHODS

Treatment of brains as genuine complex systems suggests major emphasis on the multi-scale nature of brain connectivity and dynamic behavior. Cross-scale interactions of local, regional, and global networks are apparently responsible for much of EEG's oscillatory behaviors. Finite axon propagation speed, often assumed to be infinite in local network models, is central to our conceptual framework.

RESULTS

Myelin controls axon speed, and the synchrony of impulse traffic between distant cortical regions appears to be critical for optimal mental performance and learning. Several experiments suggest that axon conduction speed is plastic, thereby altering the regional and global white matter connections that facilitate binding of remote local networks.

CONCLUSIONS

Combined EEG and high resolution EEG can provide distinct multi-scale estimates of functional connectivity in both healthy and diseased brains with measures like frequency and phase spectra, covariance, and coherence.

SIGNIFICANCE

White matter disease may profoundly disrupt normal EEG coherence patterns, but currently these kinds of studies are rare in scientific labs and essentially missing from clinical environments.

Positive sharp waves in the EEG of children and adults

Interictal epileptiform discharges (IEDs) with negative polarity have been extensively studied in the EEG literature. However, little attention has been drawn to IED with positive polarity [positive sharp waves (PSWs)]. In this paper, we discuss pathophysiological, neuroimaging, and clinical correlates of this pattern in a heterogeneous group of children and adults who demonstrated PSW in their scalp EEG. We prospectively reviewed the EEGs of 1,250 patients from a heterogeneous population over a period of 1 year. Thirty-one patients had PSW in their EEG. We documented EEG parameters as well as demographic, clinical, and neuroimaging data. Statistical analysis was performed to correlate the aforementioned data. The analysis showed that PSW is an epileptogenic pattern with localizing significance, occurring primarily in the younger age groups. Furthermore, there was a strong association of PSW with chronic and/or static CNS pathology, in particular, congenital CNS anomalies, often accompanied by psychomotor retardation. Patients with "multifocal'' PSW invariably exhibited severe intellectual and motor deficits associated consistently with a variety of congenital CNS insults. PSW is a rare and under-reported EEG abnormality which, similar to negative IED, signifies focal epileptogenecity. The presence of PSW should prompt neuroimaging studies to investigate an associated chronic/static CNS pathology, in particular, congenital CNS anomalies. This association is particularly strong when PSW is multifocal in which case patients present with severe intellectual and motor deficits.

Correlation between intra- and extracranial background EEG

Scalp EEG is the most widely used modality to record the electrical signals of the brain. It is well known that the volume conduction of these brain waves through the brain, cerebrospinal fluid, skull and scalp reduces the spatial resolution and the signal amplitude. So far the volume conduction has primarily been investigated by realistic head models or interictal spike analysis. We have set up a novel and more realistic experiment that made it possible to compare the information in the intra- and extracranial EEG. We found that intracranial EEG channels contained correlated patterns when placed less than 30 mm apart, that intra- and extracranial channels were partly correlated when placed less than 40 mm apart, and that extracranial channels probably were correlated over larger distances. The underlying cortical area that influences the extracranial EEG is found to be up to 45 cm(2). This area is larger than previously reported.

Networks underlying paroxysmal fast activity and slow spike and wave in Lennox-Gastaut syndrome

OBJECTIVE

To use EEG-fMRI to determine which structures are critically involved in the generation of paroxysmal fast activity (PFA) and slow spike and wave (SSW) (1.5-2.5 Hz), the characteristic interictal discharges of Lennox-Gastaut syndrome (LGS).

METHODS

We studied 13 well-characterized patients with LGS using structural imaging and EEG-fMRI at 3 tesla. Ten patients had cortical structural abnormalities. PFA and SSW were considered as separate events in the fMRI analysis.

RESULTS

Simultaneous with fMRI, PFA was recorded in 6 patients and SSW in 9 (in 2, both were recorded). PFA events showed almost uniform increases in blood oxygen level-dependent (BOLD) signal in "association" cortical areas, as well as brainstem, basal ganglia, and thalamus. SSW showed a different pattern of BOLD signal change with many areas of decreased BOLD signal, mostly in primary cortical areas. Two patients with prior callosotomy had lateralized as well as generalized PFA. The lateralized PFA was associated with a hemispheric version of the PFA pattern we report here.

CONCLUSION

PFA is associated with activity in a diffuse network that includes association cortices as well as an unusual pattern of simultaneous activation of subcortical structures (brainstem, thalamus, and basal ganglia). By comparison, the SSW pattern is quite different, with cortical and subcortical activations and deactivations. Regardless of etiology, it appears that 2 key, but distinct, patterns of diffuse brain network involvement contribute to the defining electrophysiologic features of LGS.

Disrupted causal connectivity in mesial temporal lobe epilepsy

Although mesial temporal lobe epilepsy (mTLE) is characterized by the pathological changes in mesial temporal lobe, function alteration was also found in extratemporal regions. Our aim is to investigate the information flow between the epileptogenic zone (EZ) and other brain regions. Resting-state functional magnetic resonance imaging (RS-fMRI) data were recorded from 23 patients with left mTLE and matched controls. We first identified the potential EZ using the amplitude of low-frequency fluctuation (ALFF) of RS-fMRI signal, then performed voxel-wise Granger causality analysis between EZ and the whole brain. Relative to controls, patients demonstrated decreased driving effect from EZ to thalamus and basal ganglia, and increased feedback. Additionally, we found an altered causal relation between EZ and cortical networks (default mode network, limbic system, visual network and executive control network). The influence from EZ to right precuneus and brainstem negatively correlated with disease duration, whereas that from the right hippocampus, fusiform cortex, and lentiform nucleus to EZ showed positive correlation. These findings demonstrate widespread brain regions showing abnormal functional interaction with EZ. In addition, increased ALFF in EZ was positively correlated with the increased driving effect on EZ in patients, but not in controls. This finding suggests that the initiation of epileptic activity depends not only on EZ itself, but also on the activity emerging in large-scale macroscopic brain networks. Overall, this study suggests that the causal topological organization is disrupted in mTLE, providing valuable information to understand the pathophysiology of this disorder.

A switching multi-scale dynamical network model of EEG/MEG

We introduce a new generative model of the Encephalography (EEG/MEG) data, the inversion of which allows for inferring the locations and temporal evolution of the underlying sources as well as their dynamical interactions. The proposed Switching Mesostate Space Model (SMSM) builds on the multi-scale generative model for EEG/MEG by Daunizeau and Friston (2007). SMSM inherits the assumptions that (1) bioelectromagnetic activity is generated by a set of distributed sources, (2) the dynamics of these sources can be modelled as random fluctuations about a small number of mesostates, and (3) the number of mesostates engaged by a cognitive task is small. Additionally, four generalising assumptions are now included: (4) the mesostates interact according to a full Dynamical Causal Network (DCN) that can be estimated; (5) the dynamics of the mesostates can switch between multiple approximately linear operating regimes; (6) each operating regime remains stable over finite periods of time (temporal clusters); and (7) the total number of times the mesostates' dynamics can switch is small. The proposed model adds, therefore, a level of flexibility by accommodating complex brain processes that cannot be characterised by purely linear and stationary Gaussian dynamics. Importantly, the SMSM furnishes a new interpretation of the EEG/MEG data in which the source activity may have multiple discrete modes of behaviour, each with approximately linear dynamics. This is modelled by assuming that the connection strengths of the underlying mesoscopic DCN are time-dependent but piecewise constant, i.e. they can undergo discrete changes over time. A Variational Bayes inversion scheme is derived to estimate all the parameters of the model by maximising a (Negative Free Energy) lower bound on the model evidence. This bound is used to select among different model choices that are defined by the number of mesostates as well as by the number of stationary linear regimes. The full model is compared to a simplified version that uses no dynamical assumptions as well as to a standard EEG inversion technique. The comparison is carried out using an extensive set of simulations, and the application of SMSM to a real data set is also demonstrated. Our results show that for experimental situations in which we have some a priori belief that there are multiple approximately linear dynamical regimes, the proposed SMSM provides a natural modelling tool.

MEG source localization of spatially extended generators of epileptic activity: comparing entropic and hierarchical bayesian approaches

Localizing the generators of epileptic activity in the brain using Electro-EncephaloGraphy (EEG) or Magneto-EncephaloGraphy (MEG) signals is of particular interest during the pre-surgical investigation of epilepsy. Epileptic discharges can be detectable from background brain activity, provided they are associated with spatially extended generators. Using realistic simulations of epileptic activity, this study evaluates the ability of distributed source localization methods to accurately estimate the location of the generators and their sensitivity to the spatial extent of such generators when using MEG data. Source localization methods based on two types of realistic models have been investigated: (i) brain activity may be modeled using cortical parcels and (ii) brain activity is assumed to be locally smooth within each parcel. A Data Driven Parcellization (DDP) method was used to segment the cortical surface into non-overlapping parcels and diffusion-based spatial priors were used to model local spatial smoothness within parcels. These models were implemented within the Maximum Entropy on the Mean (MEM) and the Hierarchical Bayesian (HB) source localization frameworks. We proposed new methods in this context and compared them with other standard ones using Monte Carlo simulations of realistic MEG data involving sources of several spatial extents and depths. Detection accuracy of each method was quantified using Receiver Operating Characteristic (ROC) analysis and localization error metrics. Our results showed that methods implemented within the MEM framework were sensitive to all spatial extents of the sources ranging from 3 cm² to 30 cm², whatever were the number and size of the parcels defining the model. To reach a similar level of accuracy within the HB framework, a model using parcels larger than the size of the sources should be considered.

Computing sources of epileptic discharges using the novel BMA approach: comparison with other distributed inverse solution methods

Electroencephalography (EEG) source localization in epileptology continues to be a challenge for neuroscientists. A number of inverse solution (IS) methodologies have been proposed to solve this problem, and their advantages and limitations have been described. In the present work, a previously developed IS approach called Bayesian model averaging (BMA) is introduced in clinical practice in order to improve the localization accuracy of epileptic discharge sources. For this study, 31 patients with the diagnosis of partial epilepsies were studied: 14 had benign childhood epilepsy with centrotemporal spikes and 17 had temporal lobe epilepsy (TLE). The underlying epileptic sources were localized using the BMA approach, and the results were compared with those expected from the clinical diagnosis. Additional comparisons with results obtained from 3 of the most commonly used distributed IS methods for these purposes (minimum norm [MN], weighted minimum norm [WMN], and low-resolution electromagnetic tomography [LORETA]) were carried out in terms of source localization accuracy and spatial resolutions. The BMA approach estimated discharge sources that were consistent with the clinical diagnosis, and this method outperformed LORETA, MN, and WMN in terms of both localization accuracy and spatial resolution. The BMA was able to localize deeper generators with high accuracy. In conclusion, the BMA methodology has a great potential for the noninvasive accurate localization of epileptic sources, even those located in deeper structures. Therefore, it could be a promising tool for clinical practice in epileptology, although additional studies in other types of epileptic syndromes are necessary.

Pitfalls in the dipolar model for the neocortical EEG sources

For about six decades, primary current sources of the electroencephalogram (EEG) have been assumed dipolar in nature. In this study, we used electrophysiological recordings from anesthetized Wistar rats undergoing repeated whisker deflections to revise the biophysical foundations of the EEG dipolar model. In a first experiment, we performed three-dimensional recordings of extracellular potentials from a large portion of the barrel field to estimate intracortical multipolar moments generated either by single spiking neurons (i.e., pyramidal cells, PC; spiny stellate cells, SS) or by populations of them while experiencing synchronized postsynaptic potentials. As expected, backpropagating spikes along PC dendrites caused dipolar field components larger in the direction perpendicular to the cortical surface (49.7 ± 22.0 nA·mm). In agreement with the fact that SS cells have “close-field” configurations, their dipolar moment at any direction was negligible. Surprisingly, monopolar field components were detectable both at the level of single units (i.e., −11.7 ± 3.4 nA for PC) and at the mesoscopic level of mixed neuronal populations receiving extended synaptic inputs within either a cortical column (−0.44 ± 0.20 μA) or a 2.5-m3-voxel volume (−3.32 ± 1.20 μA). To evaluate the relationship between the macroscopically defined EEG equivalent dipole and the mesoscopic intracortical multipolar moments, we performed concurrent recordings of high-resolution skull EEG and laminar local field potentials. From this second experiment, we estimated the time-varying EEG equivalent dipole for the entire barrel field using either a multiple dipole fitting or a distributed type of EEG inverse solution. We demonstrated that mesoscopic multipolar components are altogether absorbed by any equivalent dipole in both types of inverse solutions. We conclude that the primary current sources of the EEG in the neocortex of rodents are not precisely represented by a single equivalent dipole and that the existence of monopolar components must be also considered at the mesoscopic level.

Intracranial EEG-fMRI analysis of focal epileptiform discharges in humans

PURPOSE

Combining intracranial electroencephalography (iEEG) with functional magnetic resonance imaging (fMRI) is of interest in epilepsy studies as it would allow the detection of much smaller interictal epileptiform discharges than can be recorded using scalp EEG-fMRI. This may help elucidate the spatiotemporal mechanisms underlying the generation of interictal discharges. To our knowledge, iEEG-fMRI has never been performed at 3 Tesla (3T) in humans. We report our findings relating to spike-associated blood oxygen level-dependent (BOLD) signal changes in two subjects.

METHODS

iEEG-fMRI at 3T was performed in two subjects. Twelve channels of iEEG were recorded from subdural strips implanted on the left posterior temporal and middle frontal lobes in a 20-year-old female with bilateral periventricular gray matter heterotopia. Twenty channels of iEEG were recorded bilaterally from two subdural strips laid anterior-posterior along mesial temporal surfaces in a 29-year-old woman with bilateral temporal seizures and mild left amygdalar enlargement on MRI. Functional MRI (fMRI) statistical maps were generated and thresholded at p = 0.01.

KEY FINDINGS

No adverse events were noted. A total of 105 interictal discharges were recorded in the posterior middle temporal gyrus of Subject 1. In Subject 2, 478 discharges were recorded from both mesial temporal surfaces (n = 194 left, 284 right). The right and left discharges were modeled separately, as they were independent. Subject 1 showed spike-associated BOLD signal increases in the left superior temporal region, left middle frontal gyrus, and right parietal lobe. BOLD decreases were seen in the right frontal and parietal lobes. In Subject 2, BOLD signal increases were seen in both mesial temporal lobes, which when left and right spikes were modeled independently, were greater on the side of the discharge. In addition, striking BOLD signal decreases were observed in the thalamus and posterior cingulate gyrus.

SIGNIFICANCE

iEEG-fMRI can be performed at 3T with low risk. Notably, runs of only 5 or 10 min of EEG-fMRI were performed as part of our implementation protocol, yet a significant number of epileptiform discharges were recorded, allowing meaningful analyses. With these studies, we have shown that deactivation can be seen in individual subjects with focal epileptiform discharges. These preliminary observations suggest a novel mechanism through which focal interictal discharges may have widespread cortical and subcortical influences.

Functional MRI applications in epilepsy surgery

Functional magnetic resonance imaging (fMRI) is a non-invasive neuroimaging technique that has grown rapidly in popularity over the past decade. It is already prevalent in psychology, cognitive and basic neuroscience research and is being used increasingly as a tool for clinical decision-making in epilepsy. It has been used to determine language location and laterality in patients, sometimes eliminating the need for invasive tests. fMRI can been used pre-surgically to guide resection margins, preserving eloquent cortex. Other fMRI paradigms assessing memory, visual and somatosensory systems have limited clinical applications currently, but show great promise. Simultaneous recording of electroencephalogram (EEG) and fMRI has also provided insights into the networks underlying seizure generation and is increasingly being used in epilepsy centres. In this review, we present some of the current clinical applications for fMRI in the pre-surgical assessment of epilepsy patients, and examine a number of new techniques that may soon become clinically relevant.

Sphenoidal electrodes significantly change the results of source localization of interictal spikes for a large percentage of patients with temporal lobe epilepsy

Although scalp EEG is a very useful tool for presurgical evaluation in epilepsy, the 10-20 system of electrodes in many cases fails to accurately localize the source of the epileptic seizures. One suggested solution to this problem is to use additional electrodes. Sphenoidal electrodes especially have been suggested to be helpful in identifying the irritative and seizure onset zones in patients with temporal lobe epilepsy. However, the value of these electrodes has been debated, and in many epilepsy centers they are not used. In this study, we investigate the impact of sphenoidal electrodes by comparing the results of EEG source localization with and without sphenoidal recordings. We retrospectively selected patients with temporal lobe epilepsy based on their clinical semiology and electrophysiologic data. For each patient, a prototype spike was used as a template for an automatic pattern search to find similar activities. The identified spikes were then averaged and analyzed by fitting a dipole to the data. The recordings from sphenoidal electrodes were then excluded and the analysis was repeated. It was found that in more than half of the patients inclusion of sphenoidal electrodes resulted in a shift of more than 2 cm in the location of the fitted dipole, and in some cases moved the dipole from the frontal lobe or the insula to the temporal lobe. Our results suggest that sphenoidal electrodes are helpful in the analysis of the EEG recordings of patients suspected of having temporal lobe epilepsy.

Noninvasive approach to focal cortical dysplasias: clinical, EEG, and neuroimaging features

Purpose. The main purpose is to define more accurately the epileptogenic zone (EZ) with noninvasive methods in those patients with MRI diagnosis of focal cortical dysplasia (FCD) and epilepsy who are candidates of epilepsy surgery. Methods. Twenty patients were evaluated prospectively between 2007 and 2010 with comprehensive clinical evaluation, video-electroencephalography, diffusion tensor imaging (DTI), and high-resolution EEG to localize the equivalent current dipole (ECD). Key Findings. In 11 cases with white matter asymmetries in DTI the ECDs were located next to lesion on MRI with mean distance of 14.63 millimeters with topographical correlation with the EZ. Significance. We could establish a hypothesis of EZ based on Video-EEG, high-resolution EEG, ECD method, MRI, and DTI. These results are consistent with the hypothesis that the EZ in the FCD is complex and is often larger than visible lesion in MRI.

Imag(in)ing seizure propagation: MEG-guided interpretation of epileptic activity from a deep source

Identification and accurate localization of seizure foci is vital in patients with medically-intractable focal epilepsy, who may be candidates for potentially curative resective epilepsy surgery. We present a patient with difficult-to-control seizures associated with an occult focal cortical dysplasia residing within the deeper left parietal operculum and underlying posterior insula, which was not detected by conventional MRI analysis. Propagated activities from this deeper generator produced misleading EEG patterns both on surface and subdural electrode recordings suggesting initial activation of the perirolandic and mesial frontal regions. However, careful spatio-temporal analysis of stereotyped interictal activities recorded during MEG, using sequential dipole modeling, revealed a consistent pattern of epileptic propagation originating from the deeper source and propagating within few milliseconds to the dorsal convexity. In this instance, careful dissection of noninvasive investigations (interictal MEG along with ictal SPECT findings) allowed clinicians to dismiss the inaccurate and misleading findings of the traditional "gold-standard" intracranial EEG. In fact, this multimodal noninvasive approach uncovered a subtle dysplastic lesion, resection of which rendered the patient seizure-free. This case highlights the potential benefits of dynamic analysis of interictal MEG in the appropriate clinical context. Pathways of interictal spike propagation may help elucidate essential neural networks underlying focal epilepsy.

Artifact: recording EEG in special care units

Artifacts may be obtained during routine recording but are more common in special care units (SCUs) outside of the EEG laboratory, where complex electrical currents are present that create a "hostile" environment. Special care units include the epilepsy monitoring unit, neurologic intensive care unit, and operating room, where artifact is present in virtually every recording, increasing with prolonged use. Nonepileptic attacks treated as epileptic seizures have been incorrectly diagnosed and treated due to a misinterpreted EEG. The recent emergence of continuous EEG as a neurophysiologic surrogate for brain function in the neurologic intensive care unit and operating room has also brought a greater amount and new types of EEG artifact. The artifacts encountered in special care units during continuous EEG are becoming more complex and may have adverse therapeutic implications. Our knowledge of artifact needs to parallel our growth in technology to avoid the pitfalls that may be incurred during visual analysis of the EEG.

Computational modeling of epileptic activity: from cortical sources to EEG signals

In epileptic patients candidate to surgery, the interpretation of EEG signals recorded either within (depth EEG) or at the surface (scalp EEG) of the head is a crucial issue to determine epileptogenic brain regions and to define subsequent surgical strategy. This task remains difficult as there is no simple relationship between the spatiotemporal features of neuronal generators (convoluted cortical dipole layers) and the electric field potentials recorded by the electrodes. Indeed, this relationship depends on the complex interaction of several factors regarding involved cortical sources: location, area, geometry, and synchronization of neuronal activity. A computational model is proposed to address this issue. It relies on a neurophysiologically relevant model of EEG signals, which combines an accurate description of both the intracerebral sources of activity and the transfer function between dipole layers and recorded field potentials. The model is used, on the one hand, to quantitatively study the influence of source-related parameters on the properties of simulated signals, and on the other hand, to jointly analyze depth EEG and scalp EEG signals. In this article, the authors review some of the results obtained from the model with respect to the literature on the interpretation of EEG signals in the context of epilepsy.