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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.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 hThe 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.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.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.

Sleep can modulate epileptic activities, but our knowledge of sleep perturbation by epilepsy remains sparse. Interestingly, epilepsy and sleep both present with defining electrophysiological features in the form of specific graphoelements on EEG. This raises the possibility to identify, within ongoing EEG activity, how epilepsy impacts and disrupts sleep. Here, we asked whether the presence of a lateralized epileptic focus interferes with the expression of the dominant electrophysiological hallmarks of sleep: slow oscillations, slow waves and spindles. To this aim, we conducted a cross-sectional study and analysed sleep recordings with surface EEG from 69 patients with focal epilepsy (age range at EEG: 17-61 years, 29 females, 34 left focal epilepsy). Comparing patients with left and right focal epilepsy, we assessed inter-hemispheric asymmetry of sleep slow oscillations power (delta range, 0.5-4 Hz), sleep slow wave density, amplitude, duration and slope; and spindle density, amplitude, duration as well as locking to slow oscillations. We found significantly different asymmetries in slow oscillation power (p

Nodular heterotopias (NHs) are malformations of cortical development associated with drug-resistant focal epilepsy with frequent poor surgical outcome. The epileptogenic network is complex and can involve the nodule, the overlying cortex, or both. Single-pulse electrical stimulation (SPES) during stereo-electroencephalography (SEEG) allows the investigation of functional connectivity between the stimulated and responsive cortices by eliciting cortico-cortical evoked potentials (CCEPs). We used SPES to analyze the NH connectome and its relation to the epileptogenic network organization.We retrospectively studied 12 patients with NH who underwent 1 Hz or 0.2 Hz SPES of NH during SEEG. Outbound connectivity (regions where CCEPs were elicited by NH stimulation) and inbound connectivity (regions where stimulation elicited CCEPs in the NH) were searched. SEEG channels were then classified as "heterotopic" (located within the NH), "connected" (located in normotopic cortex and showing connectivity with the NH), and "unconnected." We used the epileptogenicity index (EI) to quantify implication of channels in the seizure-onset zone and to classify seizures as heterotopic, normotopic, and normo-heterotopic.One hundred thirty-five outbound and 72 inbound connections were found. Three patients showed connectivity between hippocampus and NH, and seven patients showed strong internodular connectivity. A total of 39 seizures were analyzed: 23 normo-heterotopic, 12 normotopic, and 4 heterotopic. Logistic regression found that "connected" channels were significantly (p = 8.4e-05) more likely to be epileptogenic than "unconnected" channels (odds ratio 4.71, 95% confidence interval (CI) [2.17, 10.21]) and heterotopic channels were also significantly (p = .024) more epileptogenic than "unconnected" channels (odds ratio 3.29, 95% CI [1.17, 9.23]).SPES reveals widespread connectivity between NH and normotopic regions. Those connected regions show higher epileptogenicity. SPES might be useful to assess NH epileptogenic network.

Brain oscillations play a pivotal role in synchronizing responses of local and global ensembles of neurons. Patients with schizophrenia exhibit impairments in oscillatory response, which are thought to stem from abnormal maturation during critical developmental stages. Studying individuals at genetic risk for psychosis, such as 22q11.2 deletion carriers, from childhood to adulthood may provide insights into developmental abnormalities.The authors acquired 106 consecutive TDeletion carriers had decreased theta and late-latency 40-Hz ASSRs and phase synchronization compared with control subjects. Deletion carriers with psychotic symptoms displayed a further reduction of gamma-band response, decreased ITPC, and decreased top-down modulation of gamma-band response in the auditory cortex. Reduced gamma-band response was correlated with the atrophy of auditory cortex in individuals with psychotic symptoms. In addition, a linear increase of theta and gamma power from childhood to adulthood was found in control subjects but not in deletion carriers.The results suggest that while all deletion carriers exhibit decreased gamma-band response, more severe local and long-range communication abnormalities are associated with the emergence of psychotic symptoms and gray matter loss. Additionally, the lack of age-related changes in deletion carriers indexes a potential developmental impairment in circuits underlying the maturation of neural oscillations during adolescence. The progressive disruption of gamma-band response in 22q11.2 deletion syndrome supports a developmental perspective toward understanding and treating psychotic disorders.

Objective Non-rapid eye movement (NREM) sleep is supposed to play a key role in long-term memory consolidation transferring information from hippocampus to neocortex. However, sleep also activates epileptic activities in medial temporal regions. This study investigated whether interictal hippocampal spikes during sleep would impair long-term memory consolidation. Method We prospectively measured visual and verbal memory performance in 20 patients with epilepsy investigated with stereoelectroencephalography (SEEG) at immediate, 30-minute, and 1-week delays, and studied the correlations between interictal hippocampal spike frequency during waking and the first cycle of NREM sleep and memory performance, taking into account the number of seizures occurring during the consolidation period and other possible confounding factors, such as age and epilepsy duration. Results Retention of verbal memory over 1 week was negatively correlated with hippocampal spike frequency during sleep, whereas no significant correlation was found with hippocampal interictal spikes during waking. No significant result was found for visual memory. Regression tree analysis showed that the number of seizures was the first factor that impaired the verbal memory retention between 30 minutes and 1 week. When the number of seizures was below 5, spike frequency during sleep higher than 13 minutes was associated with impaired memory retention over 1 week. Interpretation Our results show that activation of interictal spikes in the hippocampus during sleep and seizures specifically impair long-term memory consolidation. We hypothesize that hippocampal interictal spikes during sleep interrupt hippocampal-neocortical transfer of information. ANN NEUROL 2020;87:976-987.

International audience; ObjectiveStereo-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.MethodsInterictal 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.ResultsAfter 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).SignificanceQuantified 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.

International audience; Multicentre studies are of utmost importance to conrm hypotheses. The lack of established standards and the ensuing complexity of their datamanagement often hamper their implementation. The Brain Imaging Data Structure (BIDS) is an initiative for organizing and describing neuroimagingand electrophysiological data. Building on BIDS, we have developed two software programs: BIDS Manager and BIDS Uploader. The former has beendesigned 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.

International audience; 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.

ObjectiveTo determine the involvement of subcortical regions in human epilepsy by analyzing direct recordings from these regions during epileptic seizures using stereo-EEG (SEEG).MethodsWe 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.ResultsWe 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).ConclusionsThalamic 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.

International audience; 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.

Objective: High-frequency oscillations (HFOs) in intracerebral EEG (stereoencephalography, 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 the HFOs and the spikes can predict epileptogenic regions with a large spatial sampling at the patient level. Methods: We analyzed non-REM sleep SEEG recordings sampled at 2048 Hz of thirty patients. Ripples (R, 80-250 Hz), fast ripples (FR, 250-500 Hz) 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 sign 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 2930 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, did not delineate all epileptogenic tissues. Interpretation: At the patient level, the performance of the 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.

Background Magnetoencephalography allows defining non-invasively the spatio-temporal activation of brain networks thanks to source localization algorithms. A major difficulty of MNE and beamforming methods, two classically used techniques, is the definition of proper thresholds that allow deciding the extent of activated cortex. New method We investigated two strategies for computing a threshold, taking into account the difficult multiple comparison issue. The strategies were based either on parametric statistics (Bonferroni, FDR correction) or on empirical estimates (local FDR and a custom measure based on the survival function). Results We found thanks to the simulations that parametric methods based on the sole estimation of H 0 (Bonferroni, FDR) performed poorly, in particular in high SNR situations. This is due to the spatial leakage originating from the source localization methods, which give a ‘blurred’ reconstruction of the patch extension: the higher the SNR, the more this effect is visible. Comparison with existing methods Adaptive methods such as local FDR or our proposed ‘concavity threshold’ performed better than Bonferroni or classical FDR. We present an application to real data originating from auditory stimulation in MEG. Conclusion In order to estimate source extent, adaptive strategies should be preferred to parametric statistics when dealing with ‘leaking’ source reconstruction algorithms.

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.

International audience; Purpose of review Precise localization of the epileptogenic zone is imperative for the success of resective surgery of drug-resistant epileptic patients. To decrease the number of surgical failures, clinical research has been focusing on finding new biomarkers. For the past decades, high-frequency oscillations (HFOs, 80-500Hz) have ousted interictal spikes-the classical interictal marker-from the research spotlight. Many studies have claimed that HFOs were more linked to epileptogenicity than spikes. This present review aims at refining this statement in light of recent studies. Recent findings Analysis based on single-patient characteristics has not been able to determine which of HFOs or spikes were better marker of epileptogenic tissues. Physiological HFOs are one of the main obstacles to translate HFOs to clinical practice as separating them from pathological HFOs remains a challenge. Fast ripples (a subgroup of HFOs, 250-500Hz) which are mostly pathological are not found in all epileptogenic tissues. Summary Quantified measures of HFOs and spikes give complementary results, but many barriers still persist in applying them in clinical routine. The current way of testing HFO and spike detectors and their performance in delineating the epileptogenic zone is debatable and still lacks practicality. Solutions to handle physiological HFOs have been proposed but are still at a preliminary stage.

Objectives The objective of the study was to describe electroclinical patterns in habitual seizures with motor semiology at onset, triggered by diagnostic stimulation, in patients undergoing presurgical evaluation using stereoelectroencephalography (SEEG). Methods Seizure semiology, stimulation parameters, electroclinical data, and anatomical localization were evaluated in stimulated and spontaneous seizures. Results From 120 habitual seizures triggered by 50-Hz train bipolar stimulation during SEEG, 20 presented initial motor semiology (elementary motor signs, complex motor behavior, or both). Two patterns occurred: long latency onset (7/20), where semiology occurred after the stimulation train, following visible cortical epileptic discharge similarly to spontaneous seizures; and short latency onset (13/20), in which typical semiological expression occurred during the stimulation train, preceding typical cortical discharge. Conclusions This novel observation shows that in some conditions, seizures with habitual motor semiology could be triggered early during stimulation, before typical cortical epileptic discharge became visible. The earliness of clinical onset with regard to visible cortical discharge, notably in comparison with clinically similar spontaneous seizures, suggests differences in electrophysiological mechanisms that require further investigation. These may involve preferential involvement of descending corticosubcortical connections within the same epileptogenic network for a given patient.

The hippocampus and amygdala are key brain structures of the medial temporal lobe, involved in cognitive and emotional processes as well as pathological states such as epilepsy. Despite their importance, it is still unclear whether their neural activity can be recorded non-invasively. Here, using simultaneous intracerebral and magnetoencephalography (MEG) recordings in patients with focal drug-resistant epilepsy, we demonstrate a direct contribution of amygdala and hippocampal activity to surface MEG recordings. In particular, a method of blind source separation, independent component analysis, enabled activity arising from large neocortical networks to be disentangled from that of deeper structures, whose amplitude at the surface was small but significant. This finding is highly relevant for our understanding of hippocampal and amygdala brain activity as it implies that their activity could potentially be measured non-invasively.

Objectif Le role du sommeil dans la consolidation mnesique est reconnu et impliquerait un transfert de l’information de l’hippocampe au neocortex au cours du sommeil lent, grâce au couplage entre les ripples hippocampiques, les fuseaux thalamo-corticaux et les ondes lentes corticales. Le but de ce travail est d’etudier l’interaction de ces oscillations chez l’homme. Methodes Nous avons inclus huit patients atteints d’epilepsie focale pharmacodependante enregistres en stereo-electro-encephalographie avec : –une exploration ipsilaterale de l’hippocampe, le thalamus (pulvinar) et le gyrus frontal moyen ; –une frequence des pointes inferieure a 15/min. Nous avons calcule le grand-moyennage de l’analyse temps-frequence centre sur les ripples et sur les fuseaux, effectue une analyse de coherence inter-essai et calcule les co-occurrences entre ripples, entre fuseaux et les co-occurrences entre fuseaux et ripples au sein de chacune des regions. Resultats On retrouve des activites dans la bande de frequence des ripples centres sur le creux des fuseaux dans la region frontale, l’hippocampe et le thalamus. Des ondes lentes surviennent en phase avec les fuseaux dans les trois regions. Les fuseaux et les ripples co-occurrent de facon plus significative entre la region frontale et l’hippocampe. Les ripples et les fuseaux co-occurrent de facon plus significative dans l’hippocampe. Les ripples hippocampiques co-occurrent significativement avec les fuseaux frontaux. Conclusion Notre travail retrouve une interaction entre fuseaux et ripples au sein de l’hippocampe, du thalamus et de la region frontale.

Interictal stereotactic-EEG functional connectivity in refractory focal epilepsies Lagarde S, Roehri N, Lambert I, et al. Brain. 2018;141(10):2966-2980.Drug-refractory focal epilepsies are network diseases associated with functional connectivity alterations both during ictal and interictal periods. A large majority of studies on the interictal/resting state have focused on functional magnetic resonance imaging (MRI)-based functional connectivity. Few studies have used electrophysiology, despite its high-temporal capacities. In particular, stereotactic-electroencephalogram (EEG) is highly suitable to study functional connectivity because it permits direct intracranial electrophysiological recordings with relative large-scale sampling. Most previous studies in stereotactic-EEG have been directed toward temporal lobe epilepsy, which does not represent the whole spectrum of drug-refractory epilepsies. The present study aims at filling this gap, investigating interictal functional connectivity alterations behind cortical epileptic organization and its association with postsurgical prognosis. To this purpose, we studied a large cohort of 59 patients with malformation of cortical development explored by stereotactic-EEG with a wide spatial sampling (76 distinct brain areas were recorded, median of 13.2 per patient). We computed functional connectivity using nonlinear correlation. We focused on 3 zones defined by stereotactic-EEG ictal activity: the epileptogenic zone (EZ), the propagation zone (PZ), and the noninvolved zone. First, we compared within-zone and between-zones functional connectivity. Second, we analyzed the directionality of functional connectivity between these zones. Third, we measured the associations between functional connectivity measures and clinical variables, especially postsurgical prognosis. Our study confirms that functional connectivity differs according to the zone under investigation. We found: (1) a gradual decrease in the within-zone functional connectivity with higher values for EZ and PZ, and lower for noninvolved zones; (2) preferential coupling between structures of the EZ; (3) preferential coupling between EZ and PZ; and (4) poorer postsurgical outcome in patients with higher functional connectivity of non-involved zone (within-noninvolved zone, between noninvolved zone, and PZ functional connectivity). Our work suggests that, even during the interictal state, functional connectivity is reinforced within epileptic cortices (EZ and PZ) with a gradual organization. Moreover, larger functional connectivity alterations, suggesting more diffuse disease, are associated with poorer postsurgical prognosis. This is consistent with computational studies suggesting that connectivity is crucial in order to model the spatiotemporal dynamics of seizures. Dynamic brain network states in human generalized spike-wave discharges Tangwiriyasakul C, Perani S, Centeno M, et al. Brain. 2018;141(10):2981-2994.Generalized spike-wave discharges in idiopathic generalized epilepsy are conventionally assumed to have abrupt onset and offset. However, in rodent models, discharges emerge during a dynamic evolution of brain network states, extending several seconds before and after the discharge. In human idiopathic generalized epilepsy, simultaneous EEG and functional MRI shows cortical regions may be active before discharges, and network connectivity around discharges may not be normal. Here, in human idiopathic generalized epilepsy, we investigated whether generalized spike-wave discharges emerge during a dynamic evolution of brain network states. Using EEG-functional MRI, we studied 43 patients and 34 healthy control subjects. We obtained 95 discharges from 20 patients. We compared data from patients with discharges with data from patients without discharges and healthy controls. Changes in MRI (blood oxygenation level dependent) signal amplitude in discharge epochs were observed only at and after EEG onset, involving a sequence of parietal and frontal cortical regions then thalamus (P < .01, across all regions and measurement time points). Examining MRI signal phase synchrony as a measure of functional connectivity between each pair of 90 brain regions, we found significant connections (P < .01, across all connections and measurement time points) involving frontal, parietal and occipital cortex during discharges, and for 20 seconds after EEG offset. This network prominent during discharges showed significantly low synchrony (below 99% confidence interval for synchrony in this network in nondischarge epochs in patients) from 16 seconds to 10 seconds before discharges, then ramped up steeply to a significantly high level of synchrony 2 seconds before discharge onset. Significant connections were seen in a sensorimotor network in the minute before discharge onset. This network also showed elevated synchrony in patients without discharges compared to healthy controls (P = .004). During 6 seconds prior to discharges, additional significant connections to this sensorimotor network were observed, involving prefrontal, and precuneus regions. In healthy subjects, significant connections involved a posterior cortical network. In patients with discharges, this posterior network showed significantly low synchrony during the minute prior to discharge onset. In patients without discharges, this network showed the same level of synchrony as in healthy controls. Our findings suggest persistently high sensorimotor network synchrony, coupled with transiently (at least 1 minute) low posterior network synchrony, may be a state predisposing to generalized spike-wave discharge onset. Our findings also show that EEG onset and associated MRI signal amplitude change is embedded in a considerably longer period of evolving brain network states before and after discharge events.

International audience

Background In pharmacoresistant epilepsy, exploration with depth electrodes can be needed to precisely define the epileptogenic zone. Accurate location of these electrodes is thus essential for the interpretation of Stereotaxic EEG (SEEG) signals. As SEEG analysis increasingly relies on signal processing, it is crucial to make a link between these results and patient’s anatomy. Our aims were thus to develop a suite of software tools, called “EpiTools”, able to i) precisely and automatically localize the position of each SEEG contact and ii) display the results of signal analysis in each patient’s anatomy. New method The first tool, GARDEL (GUI for Automatic Registration and Depth Electrode Localization), is able to automatically localize SEEG contacts and to label each contact according to a pre-specified nomenclature (for instance that of FreeSurfer or MarsAtlas). The second tool, 3Dviewer, enables to visualize in the 3D anatomy of the patient the origin of signal processing results such as rate of biomarkers, connectivity graphs or Epileptogenicity Index. Results GARDEL was validated in 30 patients by clinicians and proved to be highly reliable to determine within the patient’s individual anatomy the actual location of contacts. Comparison with existing methods GARDEL is a fully automatic electrode localization tool needing limited user interaction (only for electrode naming or contact correction). The 3Dviewer is able to read signal processing results and to display them in link with patient’s anatomy. Conclusion EpiTools can help speeding up the interpretation of SEEG data and improving its precision.

Epilepsy is a major health problem as it affects 50 million people worldwide. One third of the patients are resistant to medication. Surgical removal of the brain areas generating the seizure – the epileptogenic zone – is considered as the standard option for these patients to be seizure free. The non-negligible rate of surgical failure has led to seek other electrophysiological criteria. One putative marker is the high-frequency oscillations (HFOs). An HFO is a brief oscillation between 80-500 Hz lasting at least 4 periods recorded in intracerebral EEG. Due to their short-lasting nature, visually marking of these small oscillations is tedious and time-consuming. Automatically detecting these oscillations seems an imperative stage to study HFOs on cohorts of patients. There is however no general agreement on existing detectors. In this thesis, we developed a new way of representing HFOs thanks to a novel normalisation of the wavelet transform and to use this representation as a base for detecting HFOs automatically. We secondly designed a strategy to properly characterise and validate automated detectors. Finally, we characterised, in a cohort of patients, the reliability of HFOs and epileptic spikes - the standard marker - as predictors of the epileptogenic zone using the validated detector. The conclusion of this thesis is that HFOs are not better than epileptic spikes in predicting the epileptogenic zone but combining the two leads to a more robust biomarker.; Touchant plus de 50 millions de personnes dans le monde, l’épilepsie est un problème majeur de santé publique. Un tiers des patients souffrent d’épilepsie pharmaco-résistante. Une chirurgie visant à enlever la région cérébrale à l’origine des crises – la zone épileptogène – est considérée comme l’option de référence pour rendre libre de crises ces patients. Le taux d’échec chirurgical non négligeable a poussé la recherche d’autres marqueurs. Un marqueur potentiel est les oscillations à haute fréquence (HFOs). Une HFO est une brève oscillation entre 80-500 Hz qui dure au moins 4 périodes enregistrée en EEG intracérébrale. Par leur caractère très bref, le marquage visuel de ces petites oscillations est fastidieux et chronophage.. Il semble impératif de trouver un moyen de détecter automatiquement ces oscillations pour étudier les HFOs sur des cohortes de patients. Aucun détecteur automatique existant ne fait cependant l’unanimité. Durant cette thèse, nous avons développé un nouveau moyen de visualiser les HFOs grâce à une normalisation originale de la transformée en ondelettes pour ensuite mieux les détecter automatiquement. Puis, nous avons mise en place une stratégie pour caractériser et valider des détecteurs. Enfin, nous avons appliqué le nouveau détecteur à une cohorte de patients pour déterminer la fiabilité des HFOs et des pointes épileptiques - le marqueur standard - dans la prédiction de la zone épileptogène. La conclusion de cette thèse est que les HFOs ne sont pas meilleurs que les pointes épileptiques pour prédire la zone épileptogène mais que combiner ces deux marqueurs permettait d’obtenir un marqueur plus robuste.

International audience; Objective Non-rapid eye movement (NREM) sleep is known to be a brain state associated with an activation of interictal epileptic activity. The goal of this work was to quantify topographic changes occurring during NREM sleep in comparison with wakefulness. Method We studied intracerebral recordings of 20 patients who underwent stereo-electroencephalography (SEEG) during presurgical evaluation for pharmacoresistant focal epilepsy. We measured the number of interictal spikes (IS) and quantified the co-occurrence of IS between brain regions during 1hour of NREM sleep and 1hour of wakefulness. Co-occurrence is a method to estimate IS networks based on a temporal concordance between IS of different brain regions. Each studied region was labeled as seizure-onset zone (SOZ), propagation zone (PZ), or not involved region (NIR). Results During NREM sleep, the number of interictal spikes significantly increased in all regions (mean of 68%). This increase was higher in medial temporal regions than in other regions, whether involved in the SOZ. Spike co-occurrence increased significantly in all regions during NREM sleep in comparison with wakefulness but was greater in neocortical regions. Spike co-occurrence in medial temporal regions was not higher than in other regions, suggesting that the increase of the number of spikes in this region was in great part a local effect. Significance This study demonstrated that medial temporal regions show a greater propensity to spike production or propagation during NREM sleep compared to other brain regions, even when the medial temporal lobe is not involved in the SOZ.

Objectif L’objectif de ce travail est d’etudier l’impact des pointes epileptiques hippocampiques grâce a des enregistrements intracrâniens (stereoencephalographie, SEEG) sur les capacites de consolidation mnesique a long terme (plusieurs jours), en etudiant egalement l’effet sur les fuseaux du sommeil hippocampiques. Methodes Un total de 20 patients explores en SEEG dans le cadre du bilan prechirurgical d’une epilepsie focale pharmaco-resistante, avec une implantation hippocampique uni ou bilaterale, ont ete inclus. Ils ont passe des tests de memoire 48 h apres l’implantation des electrodes puis un rappel une semaine plus tard. Les analyses ont ete effectuees sur la nuit suivant la premiere session de tests mnesiques : detection des pointes epileptiques hippocampiques et detection des fuseaux de sommeil hippocampiques. Resultats On retrouve une correlation negative entre la frequence des pointes au cours du sommeil lent et les performances mnesiques a une semaine. Il existe une correlation negative entre la frequence des pointes epileptiques au cours du sommeil lent et la frequence des fuseaux hippocampiques. Neanmoins, aucune correlation n’est retrouvee entre la frequence des fuseaux de sommeil hippocampiques et les performances mnesiques a une semaine. Conclusion Ces resultats suggerent que les pointes epileptiques hippocampiques survenant au cours du sommeil lent interferent avec les processus responsables de la consolidation de la memoire a long terme. Les fuseaux hippocampiques ne semblent pas directement associes aux processus de consolidation mnesique a long terme.

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.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).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 (p0.001) 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.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.

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.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.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.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.

International audience; 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 8 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 time-frequency plane and in time domain. Conclusion: The normalization strategies based on a baseline and on our proposed method (the " H0 z-score ") are more precise than the others. Significance: The H0 z-score provides an optimal framework for representing and detecting HFOs, independent of a baseline and a priori frequency bands.

Many wearable lower-limb robots for walking assistance have been developed in recent years. However, it remains unclear how they can be commanded in an intuitive and efficient way by their user. In particular, providing robotic assistance to neurologically impaired individuals in turning remains a significant challenge. The control should be safe to the users and their environment, yet yield sufficient performance and enable natural human-machine interaction. Here, we propose using the head and trunk anticipatory behaviour in order to detect the intention to turn in a natural, non-intrusive way, and use it for triggering turning movement in a robot for walking assistance. We therefore study head and trunk orientation during locomotion of healthy adults, and investigate upper body anticipatory behaviour during turning. The collected walking and turning kinematics data are clustered using the k-means algorithm and cross-validation tests and k-nearest neighbours method are used to evaluate the performance of turning detection during locomotion. Tests with seven subjects exhibited accurate turning detection. Head anticipated turning by more than 400-500 ms in average across all subjects. Overall, the proposed method detected turning 300 ms after its initiation and 1230 ms before the turning movement was completed. Using head anticipatory behaviour enabled to detect turning faster by about 100 ms, compared to turning detection using only pelvis orientation measurements. Finally, it was demonstrated that the proposed turning detection can improve the quality of human-robot interaction by improving the control accuracy and transparency.