Changes in local and network brain activity after stereotactic thermocoagulation in patients with drug-resistant epilepsy.

OBJECTIVE: Stereoelectroencephalography-guided radiofrequency thermocoagulation (SEEG-guided RF-TC) aims to reduce seizure frequency by modifying epileptogenic networks through local thermocoagulative lesions. Although RF-TC is hypothesized to functionally modify brain networks, reports of changes in functional connectivity (FC) following the procedure are missing. We evaluated, by means of SEEG recordings, whether variation in brain activity after RF-TC is related to clinical outcome. METHODS: Interictal SEEG recordings from 33 patients with drug-resistant epilepsy (DRE) were analyzed. Therapeutic response was defined as a >50% reduction in seizure frequency for at least 1 month following RF-TC. Local (power spectral density [PSD]) and FC changes were evaluated in 3-min segments recorded shortly before (baseline), shortly after, and 15 min after RF-TC. The PSD and FC strength values after thermocoagulation were compared with baseline as well as between the responder and nonresponder groups. RESULTS: In responders, we found a significant reduction in PSD after RF-TC in channels that were thermocoagulated for all frequency bands (p = .007 for broad, delta and theta, p <.001 for alpha and beta bands). However, we did not observe such PSD decrease in nonresponders. At the network level, nonresponders displayed a significant FC increase in all frequency bands except theta (broad, delta, beta band: p <.001; alpha band: p <.01), although responders showed a significant FC decrease in delta (p <.001) and alpha bands (p <.05). Nonresponders showed stronger FC changes with respect to responders exclusively in TC channels (broad, alpha, theta, beta: p >.05; delta: p = .001). SIGNIFICANCE: Thermocoagulation induces both local and network-related (FC) changes in electrical brain activity of patients with DRE lasting for at least 15 min. This study demonstrates that the observed short-term modifications in brain network and local activity significantly differ between responders and nonresponders and opens new perspectives for studying the longer-lasting FC changes after RF-TC.

Spontaneous fast-ultradian dynamics of polymorphic interictal events in drug-resistant focal epilepsy.

OBJECTIVE: We studied the rate dynamics of interictal events occurring over fast-ultradian time scales, as commonly examined in clinics to guide surgical planning in epilepsy. METHODS: Stereo-electroencephalography (SEEG) traces of 35 patients with good surgical outcome (Engel I) were analyzed. For this we developed a general data mining method aimed at clustering the plethora of transient waveform shapes including interictal epileptiform discharges (IEDs) and assessed the temporal fluctuations in the capability of mapping the epileptogenic zone (EZ) of each type of event. RESULTS: We found that the fast-ultradian dynamics of the IED rate may effectively impair the precision of EZ identification, and appear to occur spontaneously, that is, not triggered by or exclusively associated with a particular cognitive task, wakefulness, sleep, seizure occurrence, post-ictal state, or antiepileptic drug withdrawal. Propagation of IEDs from the EZ to the propagation zone (PZ) could explain the observed fast-ultradian fluctuations in a reduced fraction of the analyzed patients, suggesting that other factors like the excitability of the epileptogenic tissue could play a more relevant role. A novel link was found between the fast-ultradian dynamics of the overall rate of polymorphic events and the rate of specific IEDs subtypes. We exploited this feature to estimate in each patient the 5 min interictal epoch for near-optimal EZ and resected-zone (RZ) localization. This approach produces at the population level a better EZ/RZ classification when compared to both (1) the whole time series available in each patient (p = .084 for EZ, p < .001 for RZ, Wilcoxon signed-rank test) and (2) 5 min epochs sampled randomly from the interictal recordings of each patient (p < .05 for EZ, p < .001 for RZ, 105 random samplings). SIGNIFICANCE: Our results highlight the relevance of the fast-ultradian IED dynamics in mapping the EZ, and show how this dynamics can be estimated prospectively to inform surgical planning in epilepsy.

Changes in epileptogenicity biomarkers after stereotactic thermocoagulation.

OBJECTIVE: Stereo-electroencephalography (SEEG)-guided radiofrequency thermocoagulation (RF-TC) aims at modifying epileptogenic networks to reduce seizure frequency. High-frequency oscillations (HFOs), spikes, and cross-rate are quantifiable epileptogenic biomarkers. In this study, we sought to evaluate, using SEEG signals recorded before and after thermocoagulation, whether a variation in these markers is related to the therapeutic effect of this procedure and to the outcome of surgery. METHODS: Interictal segments of SEEG signals were analyzed in 38 patients during presurgical evaluation. We used an automatized method to quantify the rate of spikes, rate of HFOs, and cross-rate (a measure combining spikes and HFOs) before and after thermocoagulation. We analyzed the differences both at an individual level with a surrogate approach and at a group level with analysis of variance. We then evaluated the correlation between these variations and the clinical response to RF-TC and to subsequent resective surgery. RESULTS: After thermocoagulation, 19 patients showed a clinical improvement. At the individual level, clinically improved patients more frequently had a reduction in spikes and cross-rate in the epileptogenic zone than patients without clinical improvement (p = .002, p = .02). At a group level, there was a greater decrease of HFOs in epileptogenic and thermocoagulated zones in patients with clinical improvement (p < .05) compared to those with no clinical benefit. Eventually, a significant decrease of all the markers after RF-TC was found in patients with a favorable outcome of resective surgery (spikes, p = .026; HFOs, p = .03; cross-rate, p = .03). SIGNIFICANCE: Quantified changes in the rate of spikes, rate of HFOs, and cross-rate can be observed after thermocoagulation, and the reduction of these markers correlates with a favorable clinical outcome after RF-TC and with successful resective surgery. This may suggest that interictal biomarker modifications after RF-TC can be clinically used to predict the effectiveness of the thermocoagulation procedure and the outcome of resective surgery.

High-frequency oscillations are not better biomarkers of epileptogenic tissues than spikes.

OBJECTIVE: High-frequency oscillations (HFOs) in intracerebral EEG (stereoelectroencephalography; SEEG) are considered as better biomarkers of epileptogenic tissues than spikes. How this can be applied at the patient level remains poorly understood. We investigated how well HFOs and spikes can predict epileptogenic regions with a large spatial sampling at the patient level. METHODS: We analyzed non-REM sleep SEEG recordings sampled at 2,048Hz of 30 patients. Ripples (Rs; 80-250Hz), fast ripples (FRs; 250-500Hz), and spikes were automatically detected. Rates of these markers and several combinations-spikes co-occurring with HFOs or FRs and cross-rate (Spk⊗HFO)-were compared to a quantified measure of the seizure onset zone (SOZ) by performing a receiver operating characteristic analysis for each patient individually. We used a Wilcoxon signed-rank test corrected for false-discovery rate to assess whether a marker was better than the others for predicting the SOZ. RESULTS: A total of 2,930 channels was analyzed (median of 100 channels per patient). The HFOs or any of its variants were not statistically better than spikes. Only one feature, the cross-rate, was better than all the other markers. Moreover, fast ripples, even though very specific, were not delineating all epileptogenic tissues. INTERPRETATION: At the patient level, the performance of HFOs is weakened by the presence of strong physiological HFO generators. Fast ripples are not sensitive enough to be the unique biomarker of epileptogenicity. Nevertheless, combining HFOs and spikes using our proposed measure-the cross-rate-is a better strategy than using only one marker. Ann Neurol 2018;83:84-97.

Epileptogenic networks in nodular heterotopia: A stereoelectroencephalography study.

OBJECTIVE: Defining the roles of heterotopic and normotopic cortex in the epileptogenic networks in patients with nodular heterotopia is challenging. To elucidate this issue, we compared heterotopic and normotopic cortex using quantitative signal analysis on stereoelectroencephalography (SEEG) recordings. METHODS: Clinically relevant biomarkers of epileptogenicity during ictal (epileptogenicity index; EI) and interictal recordings (high-frequency oscillation and spike) were evaluated in 19 patients undergoing SEEG. These biomarkers were then compared between heterotopic cortex and neocortical regions. Seizures were classified as normotopic, heterotopic, or normoheterotopic according to respective values of quantitative analysis (EI ≥0.3). RESULTS: A total of 1,246 contacts were analyzed: 259 in heterotopic tissue (heterotopic cortex), 873 in neocortex in the same lobe of the lesion (local neocortex), and 114 in neocortex distant from the lesion (distant neocortex). No significant difference in EI values, high-frequency oscillations, and spike rate was found comparing local neocortex and heterotopic cortex at a patient level, but local neocortex appears more epileptogenic (p < 0.001) than heterotopic cortex analyzing EI values at a seizure level. According to EI values, seizures were mostly normotopic (48.5%) or normoheterotopic (45.5%); only 6% were purely heterotopic. A good long-term treatment response was obtained in only two patients after thermocoagulation and surgical disconnection. SIGNIFICANCE: This is the first quantitative SEEG study providing insight into the mechanisms generating seizures in nodular heterotopia. We demonstrate that both the heterotopic lesion and particularly the normotopic cortex are involved in the epileptogenic network. This could open new perspectives on multitarget treatments, other than resective surgery, aimed at modifying the epileptic network.

Ictal Magnetic Source Imaging in Presurgical Assessment.

Ictal MEG recordings constitute rare data. The objective of this study was to evaluate ictal magnetic source localization (MSI), using two algorithms: linearly constrained minimum variance (LCMV), a beamforming technique and equivalent current dipole (ECD). Ictal MSI was studied in six patients. Three of them were undergoing post-operative re-evaluation. For all patients, results were validated by the stereoelectroencephalographic (SEEG) definition of the epileptogenic zone (EZ). EZ was quantified using the epileptogenicity index (EI) method, which accounts for both the propensity of a brain area to generate rapid discharges and the time for this area to become involved in the seizure. EI values range from 0 (no epileptogenicity) to 1 (maximal epileptogenicity). Levels of concordance between ictal MSI and EZ were determined as follows: A: ictal MSI localized the site whose value EI = 1, B: MSI localized a part of the EZ (not corresponding to the maximal value of EI = 1), C: a region could be identified on ictal MSI but not on SEEG, D: a region could be identified on SEEG but not on MSI, E: different regions were localized on MSI and SEEG. Ictal MEG pattern consisted of rhythmic activities between 10 and 20 Hz for all patients. For LCMV (first maxima), levels of concordance were A (two cases), B (two cases) and E (two cases). For ECD fitted on each time point separately (location characterized by the best goodness-of-fit value), levels of concordance were A (one case), B (one case), D (three cases) and E (one case). For ECD calculated for the whole time window, levels of concordance were A (two cases) and D (four cases). Source localization methods performed on rhythmic patterns can localize the EZ as validated by SEEG. In terms of concordance, LCMV was superior to ECD. In some cases, LCMV allows extraction of several maxima that could reflect ictal dynamics. In a medial temporal lobe epilepsy case, ictal MSI indicated an area of delayed propagation and was non-contributory to the presurgical assessment.

Magnetic source imaging in posterior cortex epilepsies.

Posterior cortex epilepsies (PCE) are characterized by less satisfying postoperative results than temporal lobe epilepsies and are thus challenging for non-invasive presurgical investigations. The objective of this study was to evaluate the performance of magnetic source imaging (MSI) in PCE, validating the results by the SEEG (stereoelectroencephalography) definition of irritative and epileptogenic zones (IZ and EZ). Fourteen PCE surgery candidates were investigated using MSI and SEEG. LCMV (Linearly Constrained Minimum Variance) and MUSIC algorithms were used. IZ was quantified using a semi-automatic detection of interictal spikes. EZ was quantified using the epileptogenicity index (EI) method that accounts for both the propensity of a brain area to generate rapid discharges and the time for this area to get involved in the seizure. EI values range from 0 (no epileptogenicity) to 1 (maximal epileptogenicity). Levels of concordance between MSI and IZ, MSI and EZ were determined as follows: A = localized on MSI and SEEG for the site of value 1 (IZ and EZ quantification), B = localized on MSI and SEEG for a part of the IZ or a structure involved in the EZ (without the maximal value 1), C = localized on MSI and not SEEG, D = localized on SEEG and not MSI, E = localized on MSI and SEEG, discordant for site. Five PCE cases were characterized by focal IZ, nine by distributed IZ between several distant brain areas. MSI allowed to determinate IZ in 4/5 focal IZ cases. In case of distributed IZ, levels of concordance were A (2 cases), B (4 cases) and D (3 cases). In most distributed cases, MSI allowed to localize only a part of the IZ. Medial temporal involvement in the IZ was frequent (9/12 cases) and not evidenced by MSI. The brain area that demonstrated the maximal value of EI was shown by MSI in four out of five (80 %) focal IZ cases, in two out of nine (22 %) distributed cases. MSI results depend on IZ characteristics. A distributed IZ organization presents difficulties for MSI and highlights the need for further methodological approaches.

Interictal networks in magnetoencephalography.

Epileptic networks involve complex relationships across several brain areas. Such networks have been shown on intracerebral EEG (stereotaxic EEG, SEEG), an invasive technique. Magnetoencephalography (MEG) is a noninvasive tool, which was recently proven to be efficient for localizing the generators of epileptiform discharges. However, despite the importance of characterizing non-invasively network aspects in partial epilepsies, only few studies have attempted to retrieve fine spatiotemporal dynamics of interictal discharges with MEG. Our goal was to assess the relevance of magnetoencephalography for detecting and characterizing the brain networks involved in interictal epileptic discharges. We propose here a semi-automatic method based on independent component analysis (ICA) and on co-occurrence of events across components. The method was evaluated in a series of seven patients by comparing its results with networks identified in SEEG. On both MEG and SEEG, we found that interictal discharges can involve remote regions which are acting in synchrony. More regions were identified in SEEG (38 in total) than in MEG (20). All MEG regions were confirmed by SEEG when an electrode was present in the vicinity. In all patients, at least one region could be identified as leading according to our criteria. A majority (71%) of MEG leaders were confirmed by SEEG. We have therefore shown that MEG measurements can extract a significant proportion of the networks visible in SEEG. This suggests that MEG can be a useful tool for defining noninvasively interictal epileptic networks, in terms of regions and patterns of connectivity, in search for a "primary irritative zone".

Helium Optically Pumped Magnetometers Can Detect Epileptic Abnormalities as Well as SQUIDs as Shown by Intracerebral Recordings.

Magnetoencephalography based on superconducting quantum interference devices (SQUIDs) has been shown to improve the diagnosis and surgical treatment decision for presurgical evaluation of drug-resistant epilepsy. Still, its use remains limited because of several constraints such as cost, fixed helmet size, and the obligation of immobility. A new generation of sensors, optically pumped magnetometers (OPMs), could overcome these limitations. In this study, we validate the ability of helium-based OPM (4He-OPM) sensors to record epileptic brain activity thanks to simultaneous recordings with intracerebral EEG [stereotactic EEG (SEEG)]. We recorded simultaneous SQUIDs-SEEG and 4He-OPM-SEEG signals in one patient during two sessions. We show that epileptic activities on intracerebral EEG can be recorded by OPMs with a better signal-to noise ratio than classical SQUIDs. The OPM sensors open new venues for the widespread application of magnetoencephalography in the management of epilepsy and other neurologic diseases and fundamental neuroscience.

Cortico-cortical and thalamo-cortical connectivity during non-REM and REM sleep: Insights from intracranial recordings in humans.

OBJECTIVE: To study changes of thalamo-cortical and cortico-cortical connectivity during wakefulness, non-Rapid Eye Movement (non-REM) sleep, including N2 and N3 stages, and REM sleep, using stereoelectroencephalography (SEEG) recording in humans. METHODS: We studied SEEG recordings of ten patients during wakefulness, non-REM sleep and REM sleep, in seven brain regions of interest including the thalamus. We calculated directed and undirected functional connectivity using a measure of non-linear correlation coefficient h2. RESULTS: The thalamus was more connected to other brain regions during N2 stage and REM sleep than during N3 stage during which cortex was more connected than the thalamus. We found two significant directed links: the first from the prefrontal region to the lateral parietal region in the delta band during N3 sleep and the second from the thalamus to the insula during REM sleep. CONCLUSIONS: These results showed that cortico-cortical connectivity is more prominent in N3 stage than in N2 and REM sleep. During REM sleep we found significant thalamo-insular connectivity, with a driving role of the thalamus. SIGNIFICANCE: We found a pattern of cortical connectivity during N3 sleep concordant with antero-posterior traveling slow waves. The thalamus seemed particularly involved as a hub of connectivity during REM sleep.

Hippocampal intracerebral evoked potentials as a marker of its functionality in drug-resistant epilepsy.

OBJECTIVES: To assess hippocampal function during stereoelectroencephalography (SEEG) investigations through the study of the medial temporal lobe event-related potential (ERP) MTL-P300. METHODS: We recorded the MTL-P300 during a visual oddball task, using hippocampal electrodes implanted for SEEG in 71 patients, in a preoperative epilepsy investigation. The presence of an MTL-P300 and its amplitude were correlated with hippocampal involvement during seizures and memory function. RESULTS: Analysis using ROC curves revealed that an MTL-P300 amplitude below -46 µV, has a specificity of 93.3% in detecting the epileptogenic zone, and absence of the MTL-P300 in the left hippocampus of patients with typical language organization was associated with marked alteration of verbal memory scores. There was a significant correlation between performance in non-verbal memory tests and the amplitude of the MTL-P300 in the right hippocampus of patients with left hemispheric seizures (immediate visual recall: r = 0.67, p = 0.005; delayed visual recall: r = 0.56, p = 0.025). Using a linear regression, we confirmed that the absence of the MTL-P300 in the left hippocampus, the involvement of the left hippocampus during seizures, and the duration of epilepsy were predictors of verbal memory deficits. CONCLUSION: Analysis of the MTL-P300 during SEEG recording provides relevant information for the analysis of hippocampal functionality and can help to localize the epileptogenic zone.

Relationship between flow and metabolism in BOLD signals: insights from biophysical models.

In many physiological or pathological situations, the interpretation of BOLD signals remains elusive as the intimate link between neuronal activity and subsequent flow/metabolic changes is not fully understood. During the past decades, a number of biophysical models of the neurovascular coupling have been proposed. It is now well-admitted that these models may bridge between observations (fMRI data) and underlying biophysical and (patho-)physiological mechanisms (related to flow and metabolism) by providing mechanistic explanations. In this study, three well-established models (Buxton's, Friston's and Sotero's) are investigated. An exhaustive parameter sensitivity analysis (PSA) was conducted to study the marginal and joint influences of model parameters on the three main features of the BOLD response (namely the principal peak, the post-stimulus undershoot and the initial dip). In each model, parameters that have the greatest (and least) influence on the BOLD features as well as on the direction of variation of these features were identified. Among the three studied models, parameters were shown to affect the output features in different manners. Indeed, the main parameters revealed by the PSA were found to strongly depend on the way the flow(CBF)-metabolism(CMRO(2)) relationship is implemented (serial vs. parallel). This study confirmed that the model structure which accounts for the representation of the CBF-CMRO(2) relationship (oxygen supply by the flow vs. oxygen demand from neurons) plays a key role. More generally, this work provides substantial information about the tuning of parameters in the three considered models and about the subsequent interpretation of BOLD signals based on these models.

Is beta band desynchronization related to skin conductance biofeedback effectiveness in drug resistant focal epilepsy?

Skin Conductance Biofeedback (SCB) is a non-invasive behavioral treatment for epilepsy based on modulation of Galvanic Skin Response (GSR). We evaluated changes in functional connectivity occurring after SCB. Six patients with drug-resistant temporal lobe epilepsy underwent monthly SCB sessions. For each patient, 10 min of resting-state magnetoencephalographic (MEG) recording were acquired before and after the first and the last SCB session. For each recording we computed the mean weighted phase lag index (WPLI) across all pair of MEG sensors. After SCB, two patients had consistent reduction of seizure frequency (>50 %). Connectivity analysis revealed a decrease of WPLI-beta band in the two responders and an increase of WPLI-alpha connectivity in all patients regardless of the clinical effect. Results suggest that reduction of WPLI-beta-low connectivity is related to the clinical response after SCB.

Transfer, Collection and Organisation of Electrophysiological and Imaging Data for Multicentre Studies.

Multicentre studies are of utmost importance to confirm hypotheses. The lack of established standards and the ensuing complexity of their data management often hamper their implementation. The Brain Imaging Data Structure (BIDS) is an initiative for organizing and describing neuroimaging and electrophysiological data. Building on BIDS, we have developed two software programs: BIDS Manager and BIDS Uploader. The former has been designed to collect, organise and manage the data and the latter has been conceived to handle their transfer and anonymisation from the partner centres. These two programs aim at facilitating the implementation of multicentre study by providing a standardised framework.

Extracting seizure onset from surface EEG with independent component analysis: Insights from simultaneous scalp and intracerebral EEG.

The success of stereoelectroencephalographic (SEEG) investigations depends crucially on the hypotheses on the putative location of the seizure onset zone. This information is derived from non-invasive data either based on visual analysis or advanced source localization algorithms. While source localization applied to interictal spikes recorded on scalp is the classical method, it does not provide unequivocal information regarding the seizure onset zone. Raw ictal activity contains a mixture of signals originating from several regions of the brain as well as EMG artifacts, hampering direct input to the source localization algorithms. We therefore introduce a methodology that disentangles the various sources contributing to the scalp ictal activity using independent component analysis and uses equivalent current dipole localization as putative locus of ictal sources. We validated the results of our analysis pipeline by performing long-term simultaneous scalp - intracerebral (SEEG) recordings in 14 patients and analyzing the wavelet coherence between the independent component encoding the ictal discharge and the SEEG signals in 8 patients passing the inclusion criteria. Our results show that invasively recorded ictal onset patterns, including low-voltage fast activity, can be captured by the independent component analysis of scalp EEG. The visibility of the ictal activity strongly depends on the depth of the sources. The equivalent current dipole localization can point to the seizure onset zone (SOZ) with an accuracy that can be as high as 10 mm for superficially located sources, that gradually decreases for deeper seizure generators, averaging at 47 mm in the 8 analyzed patients. Independent component analysis is therefore shown to have a promising SOZ localizing value, indicating whether the seizure onset zone is neocortical, and its approximate location, or located in mesial structures. That may contribute to a better crafting of the hypotheses used as basis of the stereo-EEG implantations.

The Ictal Signature of Thalamus and Basal Ganglia in Focal Epilepsy: A SEEG Study.

OBJECTIVE: To determine the involvement of subcortical regions in human epilepsy by analyzing direct recordings from these regions during epileptic seizures using stereo-EEG (SEEG). METHODS: We studied the SEEG recordings of a large series of patients (74 patients, 157 seizures) with an electrode sampling the thalamus and in some cases also the basal ganglia (caudate nucleus, 22 patients; and putamen, 4 patients). We applied visual analysis and signal quantification methods (Epileptogenicity Index [EI]) to their ictal recordings and compared electrophysiologic with clinical data. RESULTS: We found that in 86% of patients, thalamus was involved during seizures (visual analysis) and 20% showed high values of epileptogenicity (EI >0.3). Basal ganglia may also disclose high values of epileptogenicity (9% in caudate nucleus) but to a lesser degree than thalamus (p < 0.01). We observed different seizure onset patterns including low voltage high frequency activities. We found high values of thalamic epileptogenicity in different epilepsy localizations, including opercular and motor epilepsies. We found no difference between epilepsy etiologies (cryptogenic vs malformation of cortical development, p = 0.77). Thalamic epileptogenicity was correlated with the extension of epileptogenic networks (p = 0.02, ρ 0.32). We found a significant effect (p < 0.05) of thalamic epileptogenicity regarding the postsurgical outcome (higher thalamic EI corresponding to higher probability of surgical failure). CONCLUSIONS: Thalamic involvement during seizures is common in different seizure types. The degree of thalamic epileptogenicity is a possible marker of the epileptogenic network extension and of postsurgical prognosis.

The "Connectivity Epileptogenicity Index " (cEI), a method for mapping the different seizure onset patterns in StereoElectroEncephalography recorded seizures.

OBJECTIVE: Localization of epileptogenic brain regions is a crucial aim of pre-surgical evaluation of patients with drug-resistant epilepsy. Several methods have been proposed to identify the seizure onset zone, particularly based on the detection of fast activity. Most of these methods are inefficient to detect slower patterns of onset that account for 20-30% of commonly observed Stereo-Electro-Encephalography (SEEG) patterns. We seek to evaluate the performance of a new quantified measure called the Connectivity Epileptogenicity Index (cEI) in various types of seizure onset patterns. METHODS: We studied SEEG recorded seizures from 51 patients, suffering from focal drug-resistant epilepsy. The cEI combines a directed connectivity measure ("out-degrees") and the original epileptogenicity index (EI). Quantified results (Out-degrees, cEI and EI) were compared to visually defined seizure onset zone (vSOZ). We computed recall (sensitivity) and precision (proportion of correct detections within all detections) with vSOZ as a reference. The quality of the detector was quantified by the area under the precision-recall curve. RESULTS: Best results (in terms of match with vSOZ) were obtained for cEI. For seizures with fast onset patterns, cEI and EI gave comparable results. For seizures with slow onset patterns, cEI gave a better estimation of the vSOZ than EI. CONCLUSIONS: We observed that cEI discloses better performance than EI when seizures starts with slower patterns and equal to EI in seizures with fast onset patterns. SIGNIFICANCE: The cEI is a promising new tool for epileptologists, that helps characterizing the seizure onset zone in sEEG, in a robust way despite variations in seizure onset patterns.

High-frequency oscillations and spikes running down after SEEG-guided thermocoagulations in the epileptogenic network of periventricular nodular heterotopia.

OBJECTIVE: Epilepsy associated with periventricular nodular heterotopia (PNH) is characterized by complex relationships between the heterotopic and the normotopic cortex during the interictal state and at seizure onset. High-frequency oscillations (HFO) have been proposed as a marker of epileptogenicity that might reflect disease activity. The effects of thermocoagulations on epileptogenicity in this context remain unknown. We aimed to investigate the interictal HFO- and spike profiles of different cortical structures before and after two consecutive SEEG-guided thermocoagulations, in correlation with seizure outcome, in a patient with PNH-related drug-resistant epilepsy. METHODS: The epileptogenic zone (EZ) was defined by SEEG analysis based on the Epileptogenicity Index. Interictal spikes, ripples (80-250 Hz) and fast ripples (FR, 250-330 Hz) were analyzed within the heterotopia, the temporal neocortex and the hippocampus. RESULTS: The SEEG recordings revealed a distributed EZ involving the heterotopia and the posterior temporal neocortex. Both structures were targeted by thermocoagulations. Background spikes, ripples and FR-rates were significantly higher in PNH compared to the normotopic cortex. A drastic reduction of spikes (by over 80%) and absence of FR were demonstrated both in the PNH and in the neocortex during the second SEEG exploration 6 months after the first thermocoagulation, whereas no significant difference was observed in the posterior hippocampus. Ripples were significantly reduced by the first and suppressed by the second thermocoagulation within the three structures. Seizures relapsed after two months but decreased in frequency after the first thermocoagulation. Sustained seizure-freedom was achieved only after the second procedure. CONCLUSIONS: Our data demonstrate the running down of interictal HFO and spikes within the epileptogenic network following thermocoagulations of heterotopic and normotopic sites involved at seizure onset. This dynamics was in good correlation with significantly improved seizure control. SIGNIFICANCE: Combination of ictal and different interictal markers of epileptogenicity, including HFO and spike analysis, is important to get the full picture of the epileptogenic zone and could help to evaluate the disease activity.

What are the assets and weaknesses of HFO detectors? A benchmark framework based on realistic simulations.

High-frequency oscillations (HFO) have been suggested as biomarkers of epileptic tissues. While visual marking of these short and small oscillations is tedious and time-consuming, automatic HFO detectors have not yet met a large consensus. Even though detectors have been shown to perform well when validated against visual marking, the large number of false detections due to their lack of robustness hinder their clinical application. In this study, we developed a validation framework based on realistic and controlled simulations to quantify precisely the assets and weaknesses of current detectors. We constructed a dictionary of synthesized elements-HFOs and epileptic spikes-from different patients and brain areas by extracting these elements from the original data using discrete wavelet transform coefficients. These elements were then added to their corresponding simulated background activity (preserving patient- and region- specific spectra). We tested five existing detectors against this benchmark. Compared to other studies confronting detectors, we did not only ranked them according their performance but we investigated the reasons leading to these results. Our simulations, thanks to their realism and their variability, enabled us to highlight unreported issues of current detectors: (1) the lack of robust estimation of the background activity, (2) the underestimated impact of the 1/f spectrum, and (3) the inadequate criteria defining an HFO. We believe that our benchmark framework could be a valuable tool to translate HFOs into a clinical environment.

Time-Frequency Strategies for Increasing High-Frequency Oscillation Detectability in Intracerebral EEG.

BACKGROUND: High-frequency oscillations (HFOs) are considered to be highly representative of brain tissues capable of producing epileptic seizures. The visual review of HFOs on intracerebral electroencephalography is time consuming and tedious, and it can be improved by time-frequency (TF) analysis. The main issue is that the signal is dominated by lower frequencies that mask the HFOs. Our aim was to flatten (i.e., whiten) the frequency spectrum to enhance the fast oscillations while preserving an optimal signal to noise ratio (SNR). METHOD: We investigated eight methods of data whitening based on either prewhitening or TF normalization in order to improve the detectability of HFOs. We detected all local maxima of the TF image above a range of thresholds in the HFO band. RESULTS: We obtained the precision and recall curves at different SNR and for different HFO types and illustrate the added value of whitening both in the TF plane and in time domain. CONCLUSION: The normalization strategies based on a baseline and on our proposed method (the "H 0 z-score") are more precise than the others. SIGNIFICANCE: The H 0 z-score provides an optimal framework for representing and detecting HFOs, independent of a baseline and a priori frequency bands.