Interictal Epileptic Spikes Research Articles

F07. Using ultra-high field 7T MRI for evaluation of EEG findings in patients with temporal lobe epilepsy

Introduction Assessment of patients for temporal lobe epilepsy (TLE) surgery requires multimodality input, including anatomical MRI, neuropsychological evaluation, functional neuroimaging, scalp electroencephalography (EEG) and invasive EEG recordings to ensure optimal surgical planning. Often EEG demonstrates abnormal foci that are not detected on 1.5T MRI. Ultra high-field MRI at 7T provides much improved resolution of the brain. We investigated the utility of 7T MRI to detect potential anatomical abnormalities associated with functional abnormalities detected by scalp and/or invasive EEG recordings. Methods Ultra-high-field data were acquired on a 7T neuroimaging optimized MRI scanner for 13 patients with a history of drug resistant TLE during evaluation for epilepsy surgery. All patients had video-EEG telemetry recordings in our Epilepsy Monitoring Unit. Additionally, 9 patients underwent invasive EEG recordings including subdural and/or depth electrodes. Qualitative evaluation of 7T imaging for scan quality and presence of focal abnormalities detected on EEG was performed. The correlation of 7T MRI findings with EEG recordings of focal slowing or interictal epileptic spikes (IEDs), and seizures was performed. Results Assessment of 7T MRI demonstrated concordance with the clinically suspected TLE in 8 out of 13 cases. Among these, 3 exhibited supportive abnormal 7T MRI abnormalities not detected by the clinical 1.5T MRI. Eleven out of 13 cases had scalp and/or invasive electrode EEG findings with no anatomic correlates on 1.5T or 7T MRI. Findings included IEDs localizing to the contralateral temporal lobe in 6 patients, frontal lobes in 3 patients, and parieto-occipital lobes in 2 patients. Qualitative assessment of 7T images did not reveal any focal anatomical abnormalities to account for the EEG findings in these patients. Conclusion To our knowledge, this is the first study to investigate the utility of 7T MRI in combination with scalp and invasive. Qualitative ultra high-field 7T MRI findings show a moderate concordance with clinical data. However, 7T MRI did not reveal focal anatomical findings to account for all the abnormalities detected by the scalp EEG recordings in patients with temporal lobe epilepsy.

F121. Patterns of propagation in parietal lobe epilepsy

Parietal lobe epilepsy accounts for about 5% of all the focal epilepsies. Seizures of the parietal lobe origin can be difficult to diagnose because of the diverse ictal manifestations. Moreover, the ictal semiology may be related to the propagation from the epileptogenic zone (EZ) to other areas of the brain, such as the motor cortex or temporolimbic area. The scalp EEG often doesn’t accurately localize the EZ requiring the use of Stereo-EEG (SEEG).The parietal lobe resection is the least commonly performed resective surgery for drug-resistant epilepsy (DRE) with limited publications. We present a case of parietal lobe epilepsy in a patient with previous history of hemorrhagic stroke affecting the left parietal lobe secondary to a cerebral venous thrombosis who was admitted to our epilepsy monitor unit for scalp and SEEG. Patient was a 66 years old right-handed woman who experienced hemorrhagic stroke over the left parietal-posterior frontal area, while she was receiving chemotherapy for her acute lymphoblastic leukemia. She was 62 years old when she acutely presented with clonic movements of the right arm consistent with epilepsia partialis continua (EPC) recurred for several hours at a time and was followed by aphasia. She was treated with levetiracetam with good control of her seizures for two years. After that she had recurrent episodes of clonic movements in the right arm with/without prolonged aphasia. She tried lacosamide, clobazam, clonazepam, on top of the levetiracetam, which did not result in control of the seizures. Video-EEG telemetry showed interictal epileptic spikes (IEDs) in the left temporal region and one typical EPC followed by aphasia with diffuse onset over the left hemisphere. SEEG was required with depth electrodes into the left temporal, frontal, parietal, insular, cingulate cortex and 4 lines surrounding the hemorrhagic lesion in the left parietal lobe. IEDs were abundant in the lines posterior and lateral to the lesion followed by the cingulate and temporal neocortex. Many electrographic seizures were captured manifesting with low voltage fast activity (LVFA) in the lines lateral and posterior without clinical symptoms. One typical EPC that lasted for 3 h was captured. SEEG showed onset as LVFA in the electrodes lateral and posterior to the lesion without clinical symptoms. Then it spread to the electrodes anterior to the lesion (behind the central sulcus) that caused clonic jerking of the right arm and then aphasia when spread to the neocortical temporal. Low voltage stimulation of the electrodes anterior to the lesion produced prolonged afterdischarges and typical clonic movements of the right arm. Seizures of the parietal lobe origin can be a silent at onset, not expressing symptoms until they propagate to the other lobes. In this case, SEEG confirmed parietal lobe epilepsy with spread to the Rolandic cortex to cause clonic movements/EPC and to the posterior temporal neocortex to cause receptive aphasia.

Effect of interictal epileptic spikes on sleep spindles in medial temporal regions during NREM sleep: are there consequences on memory long-term consolidation? A SEEG study

Effect of interictal epileptic spikes on sleep spindles in medial temporal regions during NREM sleep: are there consequences on memory long-term consolidation? A SEEG study

Detecting sub-second changes in brain activation patterns during interictal epileptic spike using simultaneous EEG-fMRI

ObjectiveEpileptic spikes are associated with rapidly changing brain activation involving the epileptic foci and other brain regions in the “epileptic network”. We aim to resolve these activation changes using simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings. MethodsSimultaneous EEG-fMRI recordings from 9 patients with epilepsy were used in the analysis. Our method employed the whole scalp EEG data to generate regressors for the analysis of fMRI data using the general linear model. ResultsWe were able to resolve, with milliseconds temporal resolution, changes in activation patterns involving suspected epileptic foci and other brain regions in the epileptic network during spike and slow wave. Using summary maps (called SSWAS maps) which show the activation frequency of voxels, we found that suspected epileptic foci tend to be significantly active during this interval. SSWAS maps also enabled the detection of the epileptic foci in 4 of 5 patients where the conventional event-timing-based analysis failed to identify. ConclusionThese findings demonstrated the efficacy of the method and the potential application of SSWAS maps to identify epileptic foci. SignificanceThe method could help resolve activation changes during epileptic spike and could provide insights into the underlying pathophysiology of these changes.

Cortical light scattering during interictal epileptic spikes in frontal lobe epilepsy in children: A fast optical signal and electroencephalographic study

Interictal epileptic spikes (IES) represent a signature of the transient synchronous and excessive discharge of a large ensemble of cortical heterogeneous neurons. Epilepsy cannot be reduced to a hypersynchronous activation of neurons whose functioning is impaired, resulting on electroencephalogram (EEG) in epileptic seizures or IES. The complex pathophysiological mechanisms require a global approach to the interactions between neural synaptic and nonsynaptic, vascular, and metabolic systems. In the present study, we focused on the interaction between synaptic and nonsynaptic mechanisms through the simultaneous noninvasive multimodal multiscale recording of high-density EEG (HD-EEG; synaptic) and fast optical signal (FOS; nonsynaptic), which evaluate rapid changes in light scattering related to changes in membrane configuration occurring during neuronal activation of IES. To evaluate changes in light scattering occurring around IES, three children with frontal IES were simultaneously recorded with HD-EEG and FOS. To evaluate change in synchronization, time-frequency representation analysis of the HD-EEG was performed simultaneously around the IES. To independently evaluate our multimodal method, a control experiment with somatosensory stimuli was designed and applied to five healthy volunteers. Alternating increase-decrease-increase in optical signals occurred 200 ms before to 180 ms after the IES peak. These changes started before any changes in EEG signal. In addition, time-frequency domain EEG analysis revealed alternating decrease-increase-decrease in the EEG spectral power concomitantly with changes in the optical signal during IES. These results suggest a relationship between (de)synchronization and neuronal volume changes in frontal lobe epilepsy during IES. These changes in the neuronal environment around IES in frontal lobe epilepsy observed in children, as they have been in rats, raise new questions about the synaptic/nonsynaptic mechanisms that propel the neurons to hypersynchronization, as occurs during IES. We further demonstrate that this noninvasive multiscale multimodal approach is suitable for studying the pathophysiology of the IES in patients.

P233 Local and distant dysregulation of synchronization around interictal spikes in bects

Introduction High Density electroencephalography (HD EEG) is the reference non-invasive technique to investigate the dynamics of neuronal networks in Benign Epilepsy with Centro-Temporal Spikes (BECTS). Analysis of local dynamic changes surrounding Interictal Epileptic Spikes (IES) might improve our knowledge of the mechanisms that propel neurons to the hypersynchronization of IES in BECTS. Transient distant changes in the dynamics of neurons populations may also interact with neuronal networks involved in various functions that are impaired in BECTS patients. Methods HD EEG (64 electrodes) of eight well characterized BECTS patients (8 males; mean age: 7.2 years, range: 5–9 years) were analyzed. Unilateral IES were selected in 6 patients. They were bilateral and independent in 2 other patients. This resulted in a total of 10 groups of IES. Time–frequency analysis was performed on HD EEG epochs around the peak of the IES (±1000 ms), including phase-locked and non-phase-locked activities to the IES. The time frequency analyses were calculated for the frequencies between 4 and 200 Hz Results Time–frequency analysis revealed two patterns of dysregulation of the synchronization between neuronal networks preceding and following hypersynchronization of interictal spikes (±400 ms) in the epileptogenic zone. Dysregulation consists of either desynchronization (n = 6) or oscillating synchronization (n = 4) (4–50 Hz) surrounding the IES. The 2 patients with bilateral IES exhibited only local desynchronization whatever the IES considered. Distant desynchronization in low frequencies within the same window occurs simultaneously in bilateral frontal, temporal and occipital areas (n = 7). Conclusion Using time–frequency analysis of HD EEG data in a well-defined population of BECTS, we demonstrated repeated complex changes in the dynamics of neuronal networks not only during, but also, before and after the IES. In the epileptogenic zone, our results found more complex reorganization of the local network than initially thought. In line with previous results obtained at a microscopic or macroscopic level, these changes suggested the variability strategies of neuronal assemblies to raise IES. Distant changes from the epileptogenic zone in desynchronization observed in the same time window suggested interactions between larger embedded networks and opened new avenues about their possible role in the underlying mechanism leading to cognitive deficits.

P280 Dynamical changes associated with interictal epileptic spikes: An in vivo study using multimodal recording in rats

The mechanisms of neuronal hypersynchronization during Interictal Epileptic Spikes (IES) remain unsolved. IES’s multimodal analysis figure out the dynamic of the neurovascular unit considering the interactions between the neuronal, vascular networks and the extra cellular space occurring around the IES. To evaluate these multiscale interactions, a multimodal approach is developed in epileptic rats with Penicillin-G-induced IES. Changes in neuronal vascular and extracellular environment were monitored by simultaneous ElectroCorticoGraphy (ECoG), Multi-Unit-Activity (MUA) together with Fast and Slow Near-InfraRed-Spectroscopy (NIRS) recordings. MUA recordings provide the information about cellular changes occurring at different level of the cortical network. MUA are highly correlated with the triphasic IESs (ECoG) but differ according to the layers which are sampled. Slow NIRS returns changes in light absorption related to [HbO] and [HbR]. It reflects hemodynamic changes starting few seconds before the IES of Fast NIRS returns changes in light scattering related to membrane configuration. It reflects changes in the cellular space like (shrinking-swelling-shrinking) starting 500msec before the IES. The multimodal-multiscale analysis highlights the dynamical changes complexity of the different compartments starting before the IES that participates in the mechanisms that propels the neurons to IES hypersynchronization. (i) Such multimodal design provides an original approach to the complex interactions at different level (neuronal, vascular and extracellular) that might initiate the hypersynchronization of the IESs. (ii) Our simultaneous acquisition setup can be easily transferred to clinic to evaluate the specificity of such approach in different types of epilepsy.

P366 Multimodal EEG/ECOG and fast optical signal measurements in interictal epileptic spikes

Objectives Although many studies in epilepsy have examined the synaptic mechanisms constituting the basis for most of the current principles of brain activity, relatively less studies have tried to characterize changes in the cellular environment that might predispose a network to pathologic synchronization. Methods In this study, near-infrared optical imaging was used with ECoG and EEG to investigate variations in the optical properties of cortical tissue directly associated with neuronal activity in 15 rats and 3 human epileptic patients. Time-frequency analysis was also used to track variations of (de) synchronization concomitantly with changes in optical signals during IES. Results Changes in Fast optical signals (FOS) occurred 320 ms before to 370 ms after the IES peak. These changes started before any changes in ECoG signal. In addition, time-frequency domain ECoG revealed an alternating decrease-increase-decrease in the ECoG spectral power (pointing to desynchronization-synchronization-desynchronization), which occurred concomitantly with an increase-decrease-increase in relative optical signal (pointing to shrinking-swelling-shrinking of the neuronal assembly) during the IES. Discussion These relationships between electrical and optical changes highlights the complexity of the interplay between the neuronal network activity and its environment around an IES. Conclusions These changes in the neuronal environment around IESs raise new questions about the mechanisms that provides the suitable conditions for the neuronal synchronization during IESs. Significance The multimodal-multiscale FOS-ECoG approach opens new avenues to better analyze the mechanisms of neuronal synchronization in the pathologic epileptic brain, which is applicable in clinic.

MEG and EEG dipole clusters from extended cortical sources.

Data from magnetoencephalography (MEG) and electroencephalography (EEG) suffer from a rather limited signal-to-noise-ratio (SNR) due to cortical background activities and other artifacts. In order to study the effect of the SNR on the size and distribution of dipole clusters reconstructed from interictal epileptic spikes, we performed simulations using realistically shaped volume conductor models and extended cortical sources with different sensor configurations. Head models and cortical surfaces were derived from an averaged magnetic resonance image dataset (Montreal Neurological Institute). Extended sources were simulated by spherical patches with Gaussian current distributions on the folded cortical surface. Different patch sizes were used to investigate cancellation effects from opposing walls of sulcal foldings and to estimate corresponding changes in MEG and EEG sensitivity distributions. Finally, white noise was added to the simulated fields and equivalent current dipole reconstructions were performed to determine size and shape of the resulting dipole clusters. Neuronal currents are oriented perpendicular to the local cortical surface and show cancellation effects of source components on opposing sulcal walls. Since these mostly tangential aspects from large cortical patches cancel out, large extended sources exhibit more radial components in the head geometry. This effect has a larger impact on MEG data as compared to EEG, because in a spherical head model radial currents do not yield any magnetic field. Confidence volumes of single reconstructed dipoles from simulated data at different SNRs show a good correlation with the extension of clusters from repeated dipole reconstructions. Size and shape of dipole clusters reconstructed from extended cortical sources do not only depend on spike and timepoint selection, but also strongly on the SNR of the measured interictal MEG or EEG data. In a linear approximation the size of the clusters is proportional to the inverse SNR.

Local and Distant Dysregulation of Synchronization Around Interictal Spikes in BECTS.

Objective: High Density electroencephalography (HD EEG) is the reference non-invasive technique to investigate the dynamics of neuronal networks in Benign Epilepsy with Centro-Temporal Spikes (BECTS). Analysis of local dynamic changes surrounding Interictal Epileptic Spikes (IES) might improve our knowledge of the mechanisms that propel neurons to the hypersynchronization of IES in BECTS. Transient distant changes in the dynamics of neurons populations may also interact with neuronal networks involved in various functions that are impaired in BECTS patients.Methods: HD EEG (64 electrodes) of eight well-characterized BECTS patients (8 males; mean age: 7.2 years, range: 5–9 years) were analyzed. Unilateral IES were selected in 6 patients. They were bilateral and independent in 2 other patients. This resulted in a total of 10 groups of IES. Time-frequency analysis was performed on HD EEG epochs around the peak of the IES (±1000 ms), including phase-locked and non-phase-locked activities to the IES. The time frequency analyses were calculated for the frequencies between 4 and 200 Hz.Results: Time-frequency analysis revealed two patterns of dysregulation of the synchronization between neuronal networks preceding and following hypersynchronization of interictal spikes (±400 ms) in the epileptogenic zone. Dysregulation consists of either desynchronization (n = 6) or oscillating synchronization (n = 4) (4–50 Hz) surrounding the IES. The 2 patients with bilateral IES exhibited only local desynchronization whatever the IES considered. Distant desynchronization in low frequencies within the same window occurs simultaneously in bilateral frontal, temporal and occipital areas (n = 7).Significance: Using time-frequency analysis of HD EEG data in a well-defined population of BECTS, we demonstrated repeated complex changes in the dynamics of neuronal networks not only during, but also, before and after the IES. In the epileptogenic zone, our results found more complex reorganization of the local network than initially thought. In line with previous results obtained at a microscopic or macroscopic level, these changes suggested the variability strategies of neuronal assemblies to raise IES. Distant changes from the epileptogenic zone in desynchronization observed in the same time window suggested interactions between larger embedded networks and opened new avenues about their possible role in the underlying mechanism leading to cognitive deficits.

Shedding light on interictal epileptic spikes: An in vivo study using fast optical signal and electrocorticography.

Interictal epileptic spikes (IESs), apart from being a key marker of epileptic neuronal networks, constitute a nice model of the widespread endogenous phenomenon of neuronal hypersynchronization. Many questions concerning the mechanisms that drive neurons to hypersynchronize remain unresolved, but synaptic as well as nonsynaptic events are likely to be involved. In this study, changes in optical properties of neural tissues were observed in rats with penicillin-induced IES using fast optical signal (FOS) concomitantly with electrocorticography (ECoG). In this study, near-infrared optical imaging was used with ECoG to investigate variations in the optical properties of cortical tissue directly associated with neuronal activity in 15 rats. FOS changes correspond to variations of scattered light from neuronal tissue when neurons are activated. To independently evaluate our method, a control experiment on somatosensory was designed and applied to seven different rats. Time-frequency analysis was also used to track variations of (de)synchronization concomitantly with changes in optical signals during IES. FOS responses revealed that changes in optical signals occurred 320 msec before to 370 msec after the IES peak. These changes started before any changes in ECoG signal. In addition, time-frequency domain electrocorticography revealed an alternating decrease-increase-decrease in the ECoG spectral power (pointing to desynchronization-synchronization-desynchronization), which occurred concomitantly with an increase-decrease-increase in relative optical signal during the IES. These results suggest a relationship between (de)synchronization and optical changes. These changes in the neuronal environment around IESs raise new questions about the mechanisms that induce changes in optical properties of neural tissues before the IES, which may provide suitable conditions for neuronal synchronization during IESs. FOS-ECoG constitutes a multimodal approach and opens new avenues to study the mechanisms of neuronal synchronization in the pathologic brain, which has clinical implications, at least in epilepsy.

Localization of Interictal Epileptic Spikes With MEG: Optimization of an Automated Beamformer Screening Method (SAMepi) in a Diverse Epilepsy Population.

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 patients with medically refractory epilepsy. Synthetic aperture magnetometry with g2 averaged over a sliding time window (SAMepi) was performed in seven patients with focal epilepsy and five healthy volunteers. The effect of varied window lengths on detection of spiking activity was evaluated. Sliding window lengths of 0.5 to 10 seconds performed similarly, with 0.5- and 1-second windows detecting spiking activity in 1 of the 3 virtual sensor locations with highest kurtosis. These locations were concordant with the region of eventual surgical resection in these seven patients who remained seizure-free at 1 year. Average g2 values increased with increasing sliding window length in all subjects. In healthy volunteers, kurtosis values stabilized in data sets longer than 2 minutes. SAMepi using g2 averaged over 1-second sliding time windows in data sets of at least 2 minutes of duration reliably identified interictal spiking and the presumed seizure focus in these seven patients. Screening the five locations with highest kurtosis values for spiking activity is an efficient and accurate technique for localizing interictal activity using magnetoencephalography. 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 magnetoencephalography analysis if clinically validated.

Identification of Interictal Epileptic Networks from Dense-EEG.

Epilepsy is a network disease. The epileptic network usually involves spatially distributed brain regions. In this context, noninvasive M/EEG source connectivity is an emerging technique to identify functional brain networks at cortical level from noninvasive recordings. In this paper, we analyze the effect of the two key factors involved in EEG source connectivity processing: (i) the algorithm used in the solution of the EEG inverse problem and (ii) the method used in the estimation of the functional connectivity. We evaluate four inverse solutions algorithms (dSPM, wMNE, sLORETA and cMEM) and four connectivity measures (r 2, h 2, PLV, and MI) on data simulated from a combined biophysical/physiological model to generate realistic interictal epileptic spikes reflected in scalp EEG. We use a new network-based similarity index to compare between the network identified by each of the inverse/connectivity combination and the original network generated in the model. The method will be also applied on real data recorded from one epileptic patient who underwent a full presurgical evaluation for drug-resistant focal epilepsy. In simulated data, results revealed that the selection of the inverse/connectivity combination has a significant impact on the identified networks. Results suggested that nonlinear methods (nonlinear correlation coefficient, phase synchronization and mutual information) for measuring the connectivity are more efficient than the linear one (the cross correlation coefficient). The wMNE inverse solution showed higher performance than dSPM, cMEM and sLORETA. In real data, the combination (wMNE/PLV) led to a very good matching between the interictal epileptic network identified from noninvasive EEG recordings and the network obtained from connectivity analysis of intracerebral EEG recordings. These results suggest that source connectivity method, when appropriately configured, is able to extract highly relevant diagnostic information about networks involved in interictal epileptic spikes from non-invasive dense-EEG data.

Dual array EEG-fMRI: An approach for motion artifact suppression in EEG recorded simultaneously with fMRI

ObjectiveAlthough simultaneous recording of EEG and MRI has gained increasing popularity in recent years, the extent of its clinical use remains limited by various technical challenges. Motion interference is one of the major challenges in EEG-fMRI. Here we present an approach which reduces its impact with the aid of an MR compatible dual-array EEG (daEEG) in which the EEG itself is used both as a brain signal recorder and a motion sensor. MethodsWe implemented two arrays of EEG electrodes organized into two sets of nearly orthogonally intersecting wire bundles. The EEG was recorded using referential amplifiers inside a 3T MR-scanner. Virtual bipolar measurements were taken both along bundles (creating a small wire loop and therefore minimizing artifact) and across bundles (creating a large wire loop and therefore maximizing artifact). Independent component analysis (ICA) was applied. The resulting ICA components were classified into brain signal and noise using three criteria: 1) degree of two-dimensional spatial correlation between ICA coefficients along bundles and across bundles; 2) amplitude along bundles vs. across bundles; 3) correlation with ECG. The components which passed the criteria set were transformed back to the channel space. Motion artifact suppression and the ability to detect interictal epileptic spikes following daEEG and Optimal Basis Set (OBS) procedures were compared in 10 patients with epilepsy. ResultsThe SNR achieved by daEEG was 11.05±3.10 and by OBS was 8.25±1.01 (p<0.00001). In 9 of 10 patients, more spikes were detected after daEEG than after OBS (p<0.05). SignificancedaEEG improves signal quality in EEG-fMRI recordings, expanding its clinical and research potential.

A Penalized Semialgebraic Deflation ICA Algorithm for the Efficient Extraction of Interictal Epileptic Signals.

As a noninvasive technique, electroencephalography (EEG) is commonly used to monitor the brain signals of patients with epilepsy such as the interictal epileptic spikes. However, the recorded data are often corrupted by artifacts originating, for example, from muscle activities, which may have much higher amplitudes than the interictal epileptic signals of interest. To remove these artifacts, a number of independent component analysis (ICA) techniques were successfully applied. In this paper, we propose a new deflation ICA algorithm, called penalized semialgebraic unitary deflation (P-SAUD) algorithm, that improves upon classical ICA methods by leading to a considerably reduced computational complexity at equivalent performance. This is achieved by employing a penalized semialgebraic extraction scheme, which permits us to identify the epileptic components of interest (interictal spikes) first and obviates the need of extracting subsequent components. The proposed method is evaluated on physiologically plausible simulated EEG data and actual measurements of three patients. The results are compared to those of several popular ICA algorithms as well as second-order blind source separation methods, demonstrating that P-SAUD extracts the epileptic spikes with the same accuracy as the best ICA methods, but reduces the computational complexity by a factor of 10 for 32-channel recordings. This superior computational efficiency is of particular interest considering the increasing use of high-resolution EEG recordings, whose analysis requires algorithms with low computational cost.

What is the concordance between the seizure onset zone and the irritative zone? A SEEG quantified study

ObjectiveIn focal epilepsies, the accurate delineation of the epileptogenic network is a fundamental step before surgery. For years, the relationship between the interictal epileptic spikes (defining the “irritative zone”, IZ) and the sites of seizure initiation (SOZ) has been a matter of debate. MethodsOur goal was to investigate from intracerebral recordings (stereoelectroencephalography, SEEG) the distribution of interictal epileptic spikes (based on a spike frequency index, SI) and the topography of the SOZ (based on the Epileptogenicity Index, EI) in patients having focal neocortical epilepsies. Thirty-one patients were studied. A total of 539 brain regions were quantified in term of both spike generation (SI) and seizure initiation (EI). ResultsWe found a 56% (18/32) rate of agreement between maximal EI and maximal SI values. When considering separately patients with focal cortical dysplasia (FCD), the proportion of patients with good concordance was ∼75% (15/20), whereas it was only 33% (4/12) in the non FCD group. ConclusionsOur results show that a significant part of patients have some dissociation between regions showing pronounced spiking activity and those showing high epileptogenicity. e is clinically important. SignificanceFor patients with these dissociations, other markers than spiking frequency remain to be investigated. In the FCD group, the good concordance between SI and EI confirms that the mapping of the irritative zone is clinically important.

Functional Brain Dysfunction in Patients with Benign Childhood Epilepsy as Revealed by Graph Theory.

There is growing evidence that brain networks are altered in epileptic subjects. In this study, we investigated the functional connectivity and brain network properties of benign childhood epilepsy with centrotemporal spikes using graph theory. Benign childhood epilepsy with centrotemporal spikes is the most common form of idiopathic epilepsy in young children under the age of 16 years. High-density EEG data were recorded from patients and controls in resting state with eyes closed. Data were preprocessed and spike and spike-free segments were selected for analysis. Phase locking value was calculated for all paired combinations of channels and for five frequency bands (δ, θ, α, β1 and β2). We computed the degree and small-world parameters—clustering coefficient (C) and path length (L)—and compared the two patient conditions to controls. A higher degree at epileptic zones during interictal epileptic spikes (IES) was observed in all frequency bands. Both patient conditions reduced connection at the occipital and right frontal regions close to the epileptic zone in the α band. The “small-world” features (high C and short L) were deviated in patients compared to controls. A changed from an ordered network in the δ band to a more randomly organized network in the α band was observed in patients compared to healthy controls. These findings show that the benign epileptic brain network is disrupted not only at the epileptic zone, but also in other brain regions especially frontal regions.

Identification of epileptogenic networks from dense EEG: A model-based study.

Epilepsy is a network disease. Identifying the epileptogenic networks from noninvasive recordings is a challenging issue. In this context, M/EEG source connectivity is a promising tool to identify brain networks with high temporal and spatial resolution. In this paper, we analyze the impact of the two main factors that intervene in EEG source connectivity processing: i) the algorithm used to solve the EEG inverse problem and ii) the method used to measure the functional connectivity. We evaluate three inverse solutions algorithms (dSPM, wMNE and cMEM) and three connectivity measures (r(2), h(2) and MI) on data simulated from a combined biophysical/physiological model able to generate realistic interictal epileptic spikes reflected in scalp EEG. The performance criterion used here is the similarity between the network identified by each of the inverse/connectivity combination and the original network used in the source model. Results show that the choice of the combination has a high impact on the identified network. Results suggest also that nonlinear methods (nonlinear correlation coefficient and mutual information) for measuring the connectivity are more efficient than the linear one (the cross correlation coefficient). The dSPM as inverse solution shows the lowest performance compared to cMEM and wMNE.

Relationships between interictal epileptic spikes and ripples in surface EEG

ObjectiveRipples (80–250Hz) have been shown to be a more specific biomarker for the epileptogenic zone than epileptic spikes in intracranial EEG and even surface EEG. Ripples often co-occur with spikes. We investigated the spatiotemporal relation between spikes and ripples, and differences between spikes that do and do not co-occur with ripples. MethodsWe marked 50 time points with spikes in bipolar surface EEG during NREM sleep in patients with focal or multifocal epilepsy. We marked ripples that occurred with spikes and calculated parameters relating spikes and ripples: the duration, amplitude and slope of spikes, the timing of the start of ripples and spikes and the proportion of overlap. ResultsIn total 219 ripples and 5995 individual spikes were marked in 31 patients. Spikes with ripples were on average shorter, had higher amplitude and higher slope than spikes without ripples. 64% of ripples started before spikes started. Spikes occurred on 13 (5–26) channels per patient, and ripples on 3 (0–14) channels, which were also spike channels. ConclusionRipples precede rather than follow spikes, so ripples are unlikely to result from spikes. SignificanceRipples and spikes seem not one-on-one coupled, but certain states of the brain can accommodate both.

Fast fMRI Sequence Allows for Analysis of BOLD Responses to Single Interictal Epileptic Spikes

Fast fMRI Sequence Allows for Analysis of BOLD Responses to Single Interictal Epileptic Spikes