Interictal Epileptic Spikes Research Articles

N°146 – What triggers the interictal epileptic spike? A multimodal multiscale analysis of the dynamic of synaptic and non synaptic neuronal and vascular compartments using electrical and optical measurements

N°146 – What triggers the interictal epileptic spike? A multimodal multiscale analysis of the dynamic of synaptic and non synaptic neuronal and vascular compartments using electrical and optical measurements

Distinguishing TLE and TLE+ using magnetoencephalography virtual sensors (P8-9.010)

<h3>Objective:</h3> This study observes whether user-defined virtual sensors (UDvs) beamforming, using expert reader analysis, is superior to the conventional equivalent current dipole (ECD) for non-invasively differentiating between TLE and TLE+. This could result in decreased failure rates in temporal lobe epilepsy surgery and improved seizure-free outcomes. <h3>Background:</h3> Temporal lobe epilepsy (TLE) is the most common seizure disorder. 44% of TLE+ pediatric patients that undergo resective surgery fail to achieve seizure freedom. It is imperative to identify TLE vs TLE+ in children pre-surgically, since the invasive monitoring plan to identify the seizure onset zone (SOZ) would differ. <h3>Design/Methods:</h3> Ten patients who underwent magnetoencephalography (MEG) as part of non-invasive pre-surgical evaluation and intracranial electroencephalography (iEEG) monitoring were included in this retrospective analysis. Five patients each were assigned to two groups: TLE and TLE+. Virtual sensors were placed symmetrically in the bilateral mesial temporal structures, temporal gyri, and neighboring structures. We reconstructed virtual sensor waveforms and analyzed three ten-minute segments of MEG recordings to classify them as positive or negative for epileptiform activity. A chart review of iEEG data was also classified as either positive or negative spikes. The primary analysis calculated the sensitivity and specificity of each method to determine the predictive value of UDvs-beamforming. <h3>Results:</h3> Ten patients (mean age 9.8 ± 4.2 years) with TLE or TLE+ were included. Across the ten patients, the UDvs method had a mean sensitivity of 93.1% and specificity of 53.3% compared to the ECD method which had a sensitivity of 71.1% and specificity of 88.3% (P = 0.031, 0.002). <h3>Conclusions:</h3> The ECD method has greater specificity than UDvs while UDvs had greater sensitivity than ECD in determining the presence of interictal epileptic spikes compared to the gold standard, iEEG. Future work will examine increasing sample size, performing connectivity analysis of interictal spikes, and correlating surgical resection with patient outcomes. <b>Disclosure:</b> Miss Hong has nothing to disclose. The institution of Paul Horn has received research support from NIH. Dr. Tenney has received personal compensation in the range of $500-$4,999 for serving as an Expert Witness for Wilson Smith Cochran Dickerson. The institution of Dr. Tenney has received research support from NIH.

Mesial-Temporal Epileptic Ripples Correlate With Verbal Memory Impairment

RationaleHigh frequency oscillations (HFO; ripples = 80–200, fast ripples 200–500 Hz) are promising epileptic biomarkers in patients with epilepsy. However, especially in temporal epilepsies differentiation of epileptic and physiological HFO activity still remains a challenge. Physiological sleep-spindle-ripple formations are known to play a role in slow-wave-sleep memory consolidation. This study aimed to find out if higher rates of mesial-temporal spindle-ripples correlate with good memory performance in epilepsy patients and if surgical removal of spindle-ripple-generating brain tissue correlates with a decline in memory performance. In contrast, we hypothesized that higher rates of overall ripples or ripples associated with interictal epileptic spikes correlate with poor memory performance.MethodsPatients with epilepsy implanted with electrodes in mesial-temporal structures, neuropsychological memory testing and subsequent epilepsy surgery were included. Ripples and epileptic spikes were automatically detected in intracranial EEG and sleep-spindles in scalp EEG. The coupling of ripples to spindles was automatically analyzed. Mesial-temporal spindle-ripple rates in the speech-dominant-hemisphere (left in all patients) were correlated with verbal memory test results, whereas ripple rates in the non-speech-dominant hemisphere were correlated with non-verbal memory test performance, using Spearman correlation).ResultsIntracranial EEG and memory test results from 25 patients could be included. All ripple rates were significantly higher in seizure onset zone channels (p < 0.001). Patients with pre-surgical verbal memory impairment had significantly higher overall ripple rates in left mesial-temporal channels than patients with intact verbal memory (Mann–Whitney-U-Test: p = 0.039). Spearman correlations showed highly significant negative correlations of the pre-surgical verbal memory performance with left mesial-temporal spike associated ripples (rs = −0.458; p = 0.007) and overall ripples (rs = −0.475; p = 0.006). All three ripple types in right-sided mesial-temporal channels did not correlate with pre-surgical nonverbal memory. No correlation for the difference between post- and pre-surgical memory and pre-surgical spindle-ripple rates was seen in patients with left-sided temporal or mesial-temporal surgery.DiscussionThis study fails to establish a clear link between memory performance and spindle ripples. This highly suggests that spindle-ripples are only a small portion of physiological ripples contributing to memory performance. More importantly, this study indicates that spindle-ripples do not necessarily compromise the predictive value of ripples in patients with temporal epilepsy. The majority of ripples were clearly linked to areas with poor memory function.

HP22: Daily evolution of brain connectivity during the pre-ictal period in intracranial recordings of epileptic patients

Our understanding of epilepsy mechanisms has shifted its focus towards a dynamic, whole-brain network perspective. Several factors, such as circadian and multi-day cycles, are assumed to influence the likelihood of seizure occurrence. Moreover, this seizure susceptibility is critically dependent on anti-epileptic drug dosage. In this study, we aim to uncover changes in inter-regional communication that are associated with a systematic increase in seizure susceptibility. Uncovering this relationship is important to understand the mechanisms of seizure generation. Method: We investigated long-term, intracranial EEG recordings of 9 drug-refractory epileptic patients. In the context of their presurgical evaluation, anti-epileptic drugs were continuously decreased until seizures occurred (typically between fourth and sixth day). We quantified brain network changes using Directed Transfer Function in the interval between admission and first seizure. Furthermore, each measurement was characterized by various factors, such as time, drug dose, and interictal epileptic spike rate. Finally, to track connectivity changes in time, we projected them into low-dimensional space using Principal Component Analysis. Result: Connectivity changes were consistently linked to time (Pearson’s r range 0.22-0.82), drug dosage (0.24-0.79), interictal spikes and high-frequency oscillations (0.25-0.94), and circadian rhythm (0.21-0.74). These correlations were significant in 8/9 subjects (p<0.05, FDR corrected). When analyzing connectivity dynamics, we observed time points linked with seizure buildup. Their timing was patient-specific and varied between one and three days before seizure. Conclusion: Seizure susceptibility influences inter-regional communication. Interictal spikes and high-frequency oscillations are the most prominent factor. Connectivity investigations can unveil patient-specific critical time points during seizure buildup.

Validating EEG, MEG and Combined MEG and EEG Beamforming for an Estimation of the Epileptogenic Zone in Focal Cortical Dysplasia.

MEG and EEG source analysis is frequently used for the presurgical evaluation of pharmacoresistant epilepsy patients. The source localization of the epileptogenic zone depends, among other aspects, on the selected inverse and forward approaches and their respective parameter choices. In this validation study, we compare the standard dipole scanning method with two beamformer approaches for the inverse problem, and we investigate the influence of the covariance estimation method and the strength of regularization on the localization performance for EEG, MEG, and combined EEG and MEG. For forward modelling, we investigate the difference between calibrated six-compartment and standard three-compartment head modelling. In a retrospective study, two patients with focal epilepsy due to focal cortical dysplasia type IIb and seizure freedom following lesionectomy or radiofrequency-guided thermocoagulation (RFTC) used the distance of the localization of interictal epileptic spikes to the resection cavity resp. RFTC lesion as reference for good localization. We found that beamformer localization can be sensitive to the choice of the regularization parameter, which has to be individually optimized. Estimation of the covariance matrix with averaged spike data yielded more robust results across the modalities. MEG was the dominant modality and provided a good localization in one case, while it was EEG for the other. When combining the modalities, the good results of the dominant modality were mostly not spoiled by the weaker modality. For appropriate regularization parameter choices, the beamformer localized better than the standard dipole scan. Compared to the importance of an appropriate regularization, the sensitivity of the localization to the head modelling was smaller, due to similar skull conductivity modelling and the fixed source space without orientation constraint.

Classification of High Frequency Oscillations in intracranial EEG signals based on coupled time-frequency and image-related features

High Frequency Oscillations (HFOs) occurring in the range of [30–500 Hz] in epileptic intracranial ElectroEncephaloGraphic (iEEG) signals have recently proven to be good biomarkers for localizing the epileptogenic zone. Identifying these particular cerebral events and their discrimination from other transient events like interictal epileptic spikes is traditionally performed by experts through a visual inspection. However, this is laborious, very time-consuming and subjective. In this paper, a new classification approach of HFOs is proposed. This approach mainly relies on the combination of raw time frequency (TF) features, computed from a TF representation of HFOs using S-transform, with relevant image-based ones derived from a binarization of the corresponding TF grayscale image. The obtained feature vector is then used to learn a multi-class Radial Basis Function (RBF) based Support Vector Machine (SVM) classifier. The efficiency of the proposed approach, compared to conventional classification schemes based only on time, frequency or energy-based features, is confirmed, using both simulated and real iEEG signals. The proposed classification system has achieved, using simulated data and a signal to noise ratio (SNR) of 15 dB, a sensitivity, specificity, accuracy, area under the curve and F1-score around 0.990, 0.996, 0.995, 0.993 and 0.990 respectively. Besides, for real data, our proposed approach has attained the scores of 0.765, 0.941, 0.906, 0.929 and 0.768 for sensitivity, specificity, accuracy, area under the curve and F1-score respectively. These results confirm the relevance of coupling TF and image-related features, in the way proposed in this paper, for higher HFOs classification quality compared to already existing approaches.

P.127 Ultra-high field 7-Tesla magnetic resonance imaging and electroencephalography findings in epilepsy

Background: Assessment of patients for temporal lobe epilepsy (TLE) surgery requires multimodality input, including EEG to ensure optimal surgical planning. Often EEG demonstrates abnormal foci not detected on clinical MRI. 7T MRI provides improved resolution and we investigated its utility to detect potential abnormalities associated with EEG. Methods: Images were acquired on 7T MRI scanner (N=13) in oatients with TLE. Evaluation of 7T imaging for focal abnormalities was performed. Correlation of 7T MRI findings with EEG of focal slowing or interictal epileptic spikes (IEDs) and seizures was performed. Results: Assessment of 7T MRI demonstrated concordance with TLE in 8/13 cases. Three cases exhibited abnormal 7T MRI abnormalities not detected by 1.5 T MRI. Eleven out of 13 cases had EEG findings without anatomic correlates on MRI, with IEDs localizing to contralateral temporal, frontal, and parieto-occipital lobes. 7T images did not reveal focal anatomical abnormalities to account for the EEG findings in these patients. Conclusions: To our knowledge, this is the first study to investigate the role of 7T MRI in relation to EEG abnormalities. 7T RI findings show concordance with clinical data. 7T MRI did not reveal anatomical findings to account for EEG abnormalities, suggesting that such changes may be functional rather than anatomical.

Auditory stimulation during sleep suppresses spike activity in benign epilepsy with centrotemporal spikes

SummaryBenign epilepsy with centrotemporal spikes (BECTS) is a common form of childhood epilepsy linked to diverse cognitive abnormalities. The electroencephalogram of patients shows focal interictal epileptic spikes, particularly during non-rapid eye movement (NonREM) sleep. Spike formation involves thalamocortical networks, which also contribute to the generation of sleep slow oscillations (SOs) and spindles. Motivated by evidence that SO-spindle activity can be controlled through closed-loop auditory stimulation, here, we show in seven patients that auditory stimulation also reduces spike rates in BECTS. Stimulation during NonREM sleep decreases spike rates, with most robust reductions when tones are presented 1.5 to 3.5 s after spikes. Stimulation further reduces the amplitude of spikes closely following tones. Sleep spindles are negatively correlated with spike rates, suggesting that tone-evoked spindle activity mediates the spike suppression. We hypothesize spindle-related refractoriness in thalamocortical circuits as a potential mechanism. Our results open an avenue for the non-pharmacological treatment of BECTS.

Ultra-High Field 7-Tesla Magnetic Resonance Imaging and Electroencephalography Findings in Epilepsy

Assessment of patients for temporal lobe epilepsy (TLE) surgery requires multimodality input, including EEG recordings to ensure optimal surgical planning. Often EEG demonstrates abnormal foci not detected on 1.5T MRI. Ultra-high field MRI at 7T provides improved resolution of the brain. We investigated the utility of 7T MRI to detect potential anatomical abnormalities associated with EEG changes. Ultra-high field data were acquired on a 7T MRI scanner for 13 patients with history of drug resistant TLE who had had EEG telemetry recordings. Qualitative evaluation of 7T imaging for presence of focal abnormalities detected on EEG was performed. Correlation of 7T MRI findings with EEG recordings of focal slowing or interictal epileptic spikes (IEDs), and seizures was performed. Assessment of 7T MRI demonstrated concordance with TLE as determined by the multidisciplinary team in 61.5% of cases (n = 8). Among these, 3 patients exhibited supportive abnormal 7T MRI abnormalities not detected by 1.5T MRI. In patients who underwent surgery, 72.7% had concordant histopathology findings with 7T MRI findings (n = 8). However, qualitative assessment of 7T images revealed focal anatomical abnormalities to account for EEG findings in only 15.4% of patients (n = 2). Other regions that were found to have localized IEDs in addition to the lesional temporal lobe, included the contralateral temporal lobe (n = 5), frontal lobe (n = 3), and parieto-occipital lobe (n = 2). Ultra-high field 7T MRI findings show concordance with clinical data. However, 7T MRI did not reveal anatomical findings to account for abnormalities detected by EEG.

What Triggers the Interictal Epileptic Spike? A Multimodal Multiscale Analysis of the Dynamic of Synaptic and Non-synaptic Neuronal and Vascular Compartments Using Electrical and Optical Measurements.

Interictal spikes (IISs) may result from a disturbance of the intimate functional balance between various neuronal (synaptic and non-synaptic), vascular, and metabolic compartments. To better characterize the complex interactions within these compartments at different scales we developed a simultaneous multimodal-multiscale approach and measure their activity around the time of the IIS. We performed such measurements in an epileptic rat model (n = 43). We thus evaluated (1) synaptic dynamics by combining electrocorticography and multiunit activity recording in the time and time-frequency domain, (2) non-synaptic dynamics by recording modifications in light scattering induced by changes in the membrane configuration related to cell activity using the fast optical signal, and (3) vascular dynamics using functional near-infrared spectroscopy and, independently but simultaneously to the electrocorticography, the changes in cerebral blood flow using diffuse correlation spectroscopy. The first observed alterations in the measured signals occurred in the hemodynamic compartments a few seconds before the peak of the IIS. These hemodynamic changes were followed by changes in coherence and then synchronization between the deep and superficial neural networks in the 1 s preceding the IIS peaks. Finally, changes in light scattering before the epileptic spikes suggest a change in membrane configuration before the IIS. Our multimodal, multiscale approach highlights the complexity of (1) interactions between the various neuronal, vascular, and extracellular compartments, (2) neural interactions between various layers, (3) the synaptic mechanisms (coherence and synchronization), and (4) non-synaptic mechanisms that take place in the neuronal network around the time of the IISs in a very specific cerebral hemodynamic environment.

Source imaging of deep-brain activity using the regional spatiotemporal Kalman filter

Background and objective: The human brain displays rich and complex patterns of interaction within and among brain networks that involve both cortical and subcortical brain regions. Due to the limited spatial resolution of surface electroencephalography (EEG), EEG source imaging is used to reconstruct brain sources and investigate their spatial and temporal dynamics. The majority of EEG source imaging methods fail to detect activity from subcortical brain structures. The reconstruction of subcortical sources is a challenging task because the signal from these sources is weakened and mixed with artifacts and other signals from cortical sources. In this proof-of-principle study we present a novel EEG source imaging method, the regional spatiotemporal Kalman filter (RSTKF), that can detect deep brain activity.Methods: The regional spatiotemporal Kalman filter (RSTKF) is a generalization of the spatiotemporal Kalman filter (STKF), which allows for the characterization of different regional dynamics in the brain. It is based on state-space modeling with spatially heterogeneous dynamical noise variances, since models with spatial and temporal homogeneity fail to describe the dynamical complexity of brain activity. First, RSTKF is tested using simulated EEG data from sources in the frontal lobe, putamen, and thalamus. After that, it is applied to non-averaged interictal epileptic spikes from a presurgical epilepsy patient with focal epileptic activity in the amygdalo-hippocampal complex. The results of RSTKF are compared to those of low-resolution brain electromagnetic tomography (LORETA) and of standard STKF.Results: Only RSTKF is successful in consistently and accurately localizing the sources in deep brain regions. Additionally, RSTKF shows improved spatial resolution compared to LORETA and STKF.Conclusions: RSTKF is a generalization of STKF that allows for accurate, focal, and consistent localization of sources, especially in the deeper brain areas. In contrast to standard source imaging methods, RSTKF may find application in the localization of the epileptogenic zone in deeper brain structures, such as mesial frontal and temporal lobe epilepsies, especially in EEG recordings for which no reliable averaged spike shape can be obtained due to lack of the necessary number of spikes required to reach a certain signal-to-noise ratio level after averaging.

Interictal Fast Ripples Are Associated With the Seizure-Generating Lesion in Patients With Dual Pathology.

Rationale: Patients with dual pathology have two potentially epileptogenic lesions: One in the hippocampus and one in the neocortex. If epilepsy surgery is considered, stereotactic electroencephalography (SEEG) may reveal which of the lesions is seizure-generating, but frequently, some uncertainty remains. We aimed to investigate whether interictal high-frequency oscillations (HFOs), which are a promising biomarker of epileptogenicity, are associated with the primary focus.Methods: We retrospectively analyzed 16 patients with dual pathology. They were grouped according to their seizure-generating lesion, as suggested by ictal SEEG. An automated detector was applied to identify interictal epileptic spikes, ripples (80–250 Hz), ripples co-occurring with spikes (IES-ripples) and fast ripples (250–500 Hz). We computed a ratio R to obtain an indicator of whether rates were higher in the hippocampal lesion (R close to 1), higher in the neocortical lesion (R close to −1), or more or less similar (R close to 0).Results: Spike and HFO rates were higher in the hippocampal than in the neocortical lesion (p < 0.001), particularly in seizure onset zone channels. Seizures originated exclusively in the hippocampus in 5 patients (group 1), in both lesions in 7 patients (group 2), and exclusively in the neocortex in 4 patients (group 3). We found a significant correlation between the patients' primary focus and the ratio Rfast ripples, i.e., the proportion of interictal fast ripples detected in this lesion (p < 0.05). No such correlation was observed for interictal epileptic spikes (p = 0.69), ripples (p = 0.60), and IES-ripples (p = 0.54). In retrospect, interictal fast ripples would have correctly “predicted” the primary focus in 69% of our patients (p < 0.01).Conclusions: We report a correlation between interictal fast ripple rate and the primary focus, which was not found for epileptic spikes. Fast ripple analysis could provide helpful information for generating a hypothesis on seizure-generating networks, especially in cases with few or no recorded seizures.

Automatic detection of high-frequency-oscillations and their sub-groups co-occurring with interictal-epileptic-spikes

Objective. High-frequency-oscillations (HFO) and interictal-epileptic-spikes (IES) are spatial biomarkers of the epileptogenic-zone. Those HFO spatially and temporally co-occurring with IES (IES-HFO) are potentially superior biomarkers, their use is however challenged by the difficulty in detecting the low amplitude HFO riding the high-amplitude and steep-waveform of IES. We aim to develop an automatic HFO detector with an improved performance with respect to current methods and that also correctly distinguishes IES-HFO from IES occurring in isolation (isol-IES). We also aim to validate the biomarker-value of the automatic detections by utilizing them to localize a surrogate of the epileptogenic-zone. Approach. We developed automatic-detectors of HFO-Ripples (80–250 Hz), HFO-FastRipples (250–500 Hz) and IES based on kernelized support-vector-machines (SVM). The training of the HFO-detectors was based on visually marked HFO and the parameter optimization during this training-process promoted the correct discernment between IES-HFO and isol-IES. Both HFO-detectors were benchmarked against other published detectors using databases with both visually marked and simulated gold-standards. The IES-detector was trained with a publicly available simulated database and tested against both simulated and visually marked gold-standards. To validate the detections’ biomarker-value, the detectors were run on intracranial-EEGs from 8 patients and each with durations of 2–3 days, the detections’ cumulated per-channel occurrence-rate was then used to predict the seizure-onset-zone as a surrogate of the epileptogenic-zone. Main results. The HFO-detectors obtained at least 21 more F1-score points than previously published algorithms at the lowest signal-to-noise-ratio. The success achieved when discerning between IES-HFO and isol-IES was comparable to that of other published algorithms. The automatically detected IES-HFO and IES-Ripples showed the best biomarker-value to localize the epileptogenic-zone. Significance. The developed detectors are publicly available and provide a reliable tool to further study HFO, IES-HFO and their value as biomarkers. The putative higher biomarker value from IES-HFO was validated on automatically-detected, long-term data.

Functional and Structural Network Disorganizations in Typical Epilepsy With Centro-Temporal Spikes and Impact on Cognitive Neurodevelopment.

Epilepsy with Centrotemporal Spikes (ECTS) is the most common form of self-limited focal epilepsy. The pathophysiological mechanisms by which ECTS induces neuropsychological impairment in 15–30% of affected children remain unclear. The objective of this study is to review the current state of knowledge concerning the brain structural and functional changes that may be involved in cognitive dysfunctions in ECTS. Structural brain imaging suggests the presence of subtle neurodevelopmental changes over the epileptogenic zone and over distant regions in ECTS. This structural remodeling likely occurs prior to the diagnosis and evolves over time, especially in patients with cognitive impairment, suggesting that the epileptogenic processes might interfere with the dynamics of the brain development and/or the normal maturation processes. Functional brain imaging demonstrates profound disorganization accentuated by interictal epileptic spikes (IES) in the epileptogenic zone and in remote networks in ECTS. Over the epileptogenic zone, the literature demonstrates changes in term of neuronal activity and synchronization, which are effective several hundred milliseconds before the IES. In the same time window, functional changes are also observed in bilateral distant networks, notably in the frontal and temporal lobes. Effective connectivity demonstrates that the epileptogenic zone constitutes the key area at the origin of IES propagation toward distant cortical regions, including frontal areas. Altogether, structural and functional network disorganizations, in terms of: (i) power spectral values, (ii) functional and effective connectivity, are likely to participate in the cognitive impairment commonly reported in children with ECTS. These results suggest a central and causal role of network disorganizations related to IES in the neuropsychological impairment described in ECTS children.

Optimization of the Cortical Traveling Wave Analysis framework for feasibility in Stereo-Electroencephalography.

The study of brain waves propagation is of interest to understand the neural involvement in both physiological and pathological events, such as interictal epileptic spikes (IES). The possibility to track the trajectory of IESs could be useful to better characterize the role of the involved structures in the epileptic network, adding valuable information to the epileptic focus localization. Methods for the cortical traveling wave analysis (CTWA) have been proposed to trace the preferred propagation path of sleep slow waves, using scalp high-density EEG and reconstructing the trajectories both in the sensors and in the sources space. In this work, we propose a feasibility study of the application of these concepts to Stereo-EEG (SEEG) data for the analysis of IES. Through simulations, we selected the best performing Electrical Source Imaging inverse solution for our purpose and illustrate the CTWA procedure. We further show an exemplary application on real data and discuss advantages and pitfalls of the application of CTWA in SEEG.

Evaluation of a dual signal subspace projection algorithm in magnetoencephalographic recordings from patients with intractable epilepsy and vagus nerve stimulators

Magnetoencephalography (MEG) data is subject to many sources of environmental noise, and interference rejection is a necessary step in the processing of MEG data. Large amplitude interference caused by sources near the brain have been common in clinical settings and are difficult to reject. Artifact from vagal nerve stimulators (VNS) is a prototypical example. In this study, we describe a novel MEG interference rejection algorithm called dual signal subspace projection (DSSP), and evaluate its performance in clinical MEG data from people with epilepsy and implanted VNS. The performance of DSSP was evaluated in a retrospective cohort study of patients with epilepsy and VNS who had MEG scans for source localization of interictal epileptiform discharges. DSSP was applied to the MEG data and compared with benchmark for performance. We evaluated the clinical impact of interference rejection based on human expert detection and estimation of the location and time-course of interictal spikes, using an empirical Bayesian source reconstruction algorithm (Champagne). Clinical recordings, after DSSP processing, became more readable and a greater number of interictal epileptic spikes could be clearly identified. Source localization results of interictal spikes also significantly improved from those achieved before DSSP processing, including meaningful estimates of activity time courses. Therefore, DSSP is a valuable novel interference rejection algorithm that can be successfully deployed for the removal of strong artifacts and interferences in MEG.

New insight of the physiopathology of Interictal Epileptic Spikes (IES) using Time-Frequency Analysis

Objectives To better define the physiopathology of Interictal Epileptic Spikes (IES) and specially: (i) the mechanisms that propel neurons to hypersynchronizations, and (ii) the local and distant dynamic changes of neuronal population activities, we performed a time frequency analysis (TFA) of the surrounding activation of the IES. Methods HD EEG (64 and 128 electrodes) of 19 children (10 males; mean age 9.6 years), with refractory partial epilepsy of different aetiology, were analysed. Two types of IES were analyzed: spikes and poly-spike waves. TFA was performed on HD EEG epochs around the peak of IES (± 1000 ms). TFAs were calculated for frequencies between 4 and 50 Hz. Source localization was then performed from averaging spikes on EEG, from hypersynchronization, and from changes in TFA before hypersynchronization. Results Two time-frequency patterns were individualized: one specific for spike, the other specific for poly-spike-wave. TFA also revealed desynchronization around (before and after) hypersynchronization of IES (± 400 ms) in the epileptogenic zone, as already described in BECTS and in epileptic rats. At the lobar level the source localization was more accurate when performed during desynchronization (100%) than when performed during hypersynchronization (90%), and also than when performed on the peak of IES (74%) in the time domain. Discussion TFA with HD EEG in a children population of refractory partial epilepsy indicate complex changes in the dynamics of neuronal networks, not only during, but also before and after IES that is not specific to the type of epilepsy but to the type of IES. This provides new insight in the mechanism that propels neurons to synchronize. Source localization of IES should be performed during desynchronization, suggesting that the pathological activation already spread before the neuronal hypersynchronization of the IES.

Optimization of epileptic source localization in children: Influences of different modeling parameters

Objectives EEG-HR source localization is a non-invasive method to better delineate the source of the epileptic activity and thus the schema for electrodes implantation. Such source localization method relies on solving an inverse problem. In this study we evaluate the impact of bone conductivity, different head models and filtering, different methods of localization, the number of electrodes and the selection of different parts of the interictal epileptic spike. Methods Two groups of patients were studied. The first group (n = 13) consists of patients with lesions on the MRI. They were recorded with 64 electrodes. The second group consists of non lesional patient but one (n = 7) they were recorded with 128 electrodes. In the first group, the impact of bone conductivity, different head models, different filtering, and different methods of localization and the selection of different parts of the interictal spike was evaluate through the Euclidian distance of the resulting dipoles. In the second group, the impact of the number of electrodes (n = 128/64/32) on the location of the dipole was evaluated. Results The selection of the different parts of the interictal epileptic spikes and the different inverse methods (dipolar/scanning) did not return any significant difference on the source localization. Different filtering and bone conductivities did not significantly impact the localization. The different head model (realistic/realist) had significant impact on the localization of the source. Using 128 electrodes improved significantly the accuracy of the source localization. Conclusion Controlling the different parameters involved in the source localization significantly improve the accuracy of the inverse methods used to delineate the localization of the source of the IES and thus might be helpful to precise the schema of electrodes implantation.

S13. Local and distant dysregulation of synchronization around interictal spikes in BECTS

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. 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 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). 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.

S15. Shedding lights on interictal epliepyic spikes: An animal and patient study

Many questions concerning the mechanisms that drive neurons to hypersynchronize remain unsolved, but synaptic as well as non-synaptic events are likely to be involved. Here Optical Imaging (OI) of the epileptic brain by concomitant electroencephalography (FOS-ECoG/HD-EEG), allow investigating the changes in the cellular environment associated with Interictal Epileptic Spikes (IES). The FOS changes (milliseconds) are related to non-synaptic events neuronal activation while ECoG-HDEEG investigates the synaptic events related to the IES. In 3 patients with frontal epileptic spikes, High-Density EEG (HD-EEG) was acquired with 64 electrodes. In 15 epileptic penicillin rats’ experiments, ECoG signals were acquired with two monopolar electrodes disposed over the somatosensory cortex. FOS were recorded with a frequency-domain spectrophotometer at a sampling rate of 62.5 Hz with 16/2 detectors and 4/2 sources in patients and rats respectively. In order to provide an independent control condition to evaluate the method and the specificity of FOS in IES, the FOS signal in response to electrical stimulation of the median nerve was evaluated in both species. In both species median nerve stimulation (mERP) induces similar changes in FOS signal consisted in an increase followed by a decrease in the FOS concomitant to the mERP. In both species, alternating increase–decrease-increase in FOS occurred 200 ms before to 180 ms after the IES peak. This started before any changes in EEG signal. Time–frequency domain ECoG-HD EEG analysis revealed alternating decrease-increase–decrease in the EEG spectral power concomitantly with changes in FOS during IES. The FOS response was weaker with a lower signal-to-noise ratio when recorded on the scalp than when recorded from the cortex.This suggests a tight relationship between (de) synchronization and neuronal volume changes during IES. FOS-ECoG/HDEEG analysis revel complex changes surrounding the IES and illustrating the complexity of the underlying mechanisms of IES generation. These changes in the neuronal environment around IES in frontal lobe epilepsy in children and in rats raise new questions about the synaptic and non-synaptic mechanisms that propel the neurons to IES hypersynchronization. Because it unable to evaluate non-invasively the synaptic and non-synaptic compartments, this multiscale multimodal high temporal resolution approach offer the opportunity to thoroughly investigate the pathophysiology of the IES. FOS response was specific to exogenous stimuli or endogenous neuronal activation (IES). The observed responses in epileptic patients were similar to those on epileptic rats using similar acquisition protocol and data analysis processes. This suggests that the mechanisms involved are fairly specific to the epileptic spikes, independently of the species and of the type of epilepsy.