With or without spikes: localization of focal epileptic activity by simultaneous electroencephalography and functional magnetic resonance imaging

In patients with medically refractory focal epilepsy who are candidates for epilepsy surgery, concordant non-invasive neuroimaging data are useful to guide invasive electroencephalographic recordings or surgical resection. Simultaneous electroencephalography and functional magnetic resonance imaging recordings can reveal regions of haemodynamic fluctuations related to epileptic activity and help localize its generators. However, many of these studies (40-70%) remain inconclusive, principally due to the absence of interictal epileptiform discharges during simultaneous recordings, or lack of haemodynamic changes correlated to interictal epileptiform discharges. We investigated whether the presence of epilepsy-specific voltage maps on scalp electroencephalography correlated with haemodynamic changes and could help localize the epileptic focus. In 23 patients with focal epilepsy, we built epilepsy-specific electroencephalographic voltage maps using averaged interictal epileptiform discharges recorded during long-term clinical monitoring outside the scanner and computed the correlation of this map with the electroencephalographic recordings in the scanner for each time frame. The time course of this correlation coefficient was used as a regressor for functional magnetic resonance imaging analysis to map haemodynamic changes related to these epilepsy-specific maps (topography-related haemodynamic changes). The method was first validated in five patients with significant haemodynamic changes correlated to interictal epileptiform discharges on conventional analysis. We then applied the method to 18 patients who had inconclusive simultaneous electroencephalography and functional magnetic resonance imaging studies due to the absence of interictal epileptiform discharges or absence of significant correlated haemodynamic changes. The concordance of the results with subsequent intracranial electroencephalography and/or resection area in patients who were seizure free after surgery was assessed. In the validation group, haemodynamic changes correlated to voltage maps were similar to those obtained with conventional analysis in 5/5 patients. In 14/18 patients (78%) with previously inconclusive studies, scalp maps related to epileptic activity had haemodynamic correlates even when no interictal epileptiform discharges were detected during simultaneous recordings. Haemodynamic changes correlated to voltage maps were spatially concordant with intracranial electroencephalography or with the resection area. We found better concordance in patients with lateral temporal and extratemporal neocortical epilepsy compared to medial/polar temporal lobe epilepsy, probably due to the fact that electroencephalographic voltage maps specific to lateral temporal and extratemporal epileptic activity are more dissimilar to maps of physiological activity. Our approach significantly increases the yield of simultaneous electroencephalography and functional magnetic resonance imaging to localize the epileptic focus non-invasively, allowing better targeting for surgical resection or implantation of intracranial electrode array

Cartographie fonctionnelle du cerveau épileptique lors des évaluations préchirurgicales

Mapping of epileptic networks is crucial during functional investigations in drug-resistant patients (30%). Recent advances in neuroimaging opened the possibility to record simultaneously fMRI and EEG. It appears as a technique perfectly suited to epilepsy evaluation because it allows identifying both functional and epileptic.The main goal of this PhD work was to develop EEG/fMRI procedures at the Grenoble Hospital for pre- and post-surgical brain mapping in epileptics. Potential clinical benefits are the improvement of surgical outcome by identifying epileptic networks, and the reduction of side-effects of surgery by preserving brain functions.Because EEG signals acquired in a magnetic environment are noisy, we first evaluated how the performance of different artefact removal algorithms depends on various experimental settings. Second, we assessed hemodynamic variability in EEG/fMRI recordings and proposed a robust method estimating the most suitable patient-specific hemodynamic response to improve the sensitivity of such exams.Our results show that (i) most of removal artefact methods are efficient but that over-filtering could deteriorate EEG; (ii) estimation of hemodynamic properties is critical for EEG/fMRI exams in epilepsy. This suggests that epilepsy is often accompanied by an alteration of brain hemodynamics.We have successfully implemented EEG/fMRI at the Grenoble Hospital. This technique appeared to be helpful for presurgical evaluations. However, because of heterogeneous neurovascular coupling, the interpretation of activation maps remains difficult. Therefore, characterizing epilepsy cannot be done solely using EEG/fMRI and needs complementary investigations.La cartographie des réseaux épileptiques est cruciale lors des explorations fonctionnelles chez les patients pharmacorésistants (30%). Parmi les techniques récentes, l'acquisition simultanée en IRMf et EEG apparaît adaptée à l'exploration des épilepsies. L'IRMf/EEG est une méthode non invasive permettant de localiser les régions épileptiques et fonctionnelles.L'objectif de cette thèse était la mise en place, au CHU de Grenoble, de protocoles d'acquisition et de traitement de l'IRMf/EEG afin de localiser les réseaux épileptiques lors des évaluations pré- et post-chirurgicales. Les bénéfices sont de maximiser les chances de guérison en identifiant le réseau épileptique et de limiter les effets secondaires en préservant les aires fonctionnelles.L'acquisition de l'EEG en milieu magnétique produit des artefacts. Nous avons d'abord évalué la performance de plusieurs algorithmes de correction d'artefacts selon différentes configurations expérimentales. Nous avons ensuite évalué l'influence du couplage hémodynamique et proposé une méthode robuste estimant la réponse hémodynamique optimale pour chaque patient afin d'améliorer la sensibilité des examens.Nos résultats montrent que (i) la plupart des algorithmes sont efficaces mais qu'un filtrage trop strict peut détériorer l'EEG ; (ii) l'estimation de la réponse hémodynamique est cruciale en IRMf/EEG. Ceci suggère que l'épilepsie peut induire une modification des propriétés hémodynamiques.L'IRMf/EEG est une méthode prometteuse pour les investigations préchirurgicales. En raison de l'hétérogénéité du couplage neurovasculaire, l'interprétation des cartes d'activation reste délicate et nécessite l'emploi d'approches complémentaires

Cartographie fonctionnelle du cerveau épileptique lors des évaluations préchirurgicales

La cartographie des réseaux épileptiques est cruciale lors des explorations fonctionnelles chez les patients pharmacorésistants (30%). Parmi les techniques récentes, l'acquisition simultanée en IRMf et EEG apparaît adaptée à l'exploration des épilepsies. L'IRMf/EEG est une méthode non invasive permettant de localiser les régions épileptiques et fonctionnelles. L'objectif de cette thèse était la mise en place, au CHU de Grenoble, de protocoles d'acquisition et de traitement de l'IRMf/EEG afin de localiser les réseaux épileptiques lors des évaluations pré- et post-chirurgicales. Les bénéfices sont de maximiser les chances de guérison en identifiant le réseau épileptique et de limiter les effets secondaires en préservant les aires fonctionnelles. L'acquisition de l'EEG en milieu magnétique produit des artefacts. Nous avons d'abord évalué la performance de plusieurs algorithmes de correction d'artefacts selon différentes configurations expérimentales. Nous avons ensuite évalué l'influence du couplage hémodynamique et proposé une méthode robuste estimant la réponse hémodynamique optimale pour chaque patient afin d'améliorer la sensibilité des examens. Nos résultats montrent que (i) la plupart des algorithmes sont efficaces mais qu'un filtrage trop strict peut détériorer l'EEG ; (ii) l'estimation de la réponse hémodynamique est cruciale en IRMf/EEG. Ceci suggère que l'épilepsie peut induire une modification des propriétés hémodynamiques. L'IRMf/EEG est une méthode prometteuse pour les investigations préchirurgicales. En raison de l'hétérogénéité du couplage neurovasculaire, l'interprétation des cartes d'activation reste délicate et nécessite l'emploi d'approches complémentaires.Mapping of epileptic networks is crucial during functional investigations in drug-resistant patients (30%). Recent advances in neuroimaging opened the possibility to record simultaneously fMRI and EEG. It appears as a technique perfectly suited to epilepsy evaluation because it allows identifying both functional and epileptic. The main goal of this PhD work was to develop EEG/fMRI procedures at the Grenoble Hospital for pre- and post-surgical brain mapping in epileptics. Potential clinical benefits are the improvement of surgical outcome by identifying epileptic networks, and the reduction of side-effects of surgery by preserving brain functions. Because EEG signals acquired in a magnetic environment are noisy, we first evaluated how the performance of different artefact removal algorithms depends on various experimental settings. Second, we assessed hemodynamic variability in EEG/fMRI recordings and proposed a robust method estimating the most suitable patient-specific hemodynamic response to improve the sensitivity of such exams. Our results show that (i) most of removal artefact methods are efficient but that over-filtering could deteriorate EEG; (ii) estimation of hemodynamic properties is critical for EEG/fMRI exams in epilepsy. This suggests that epilepsy is often accompanied by an alteration of brain hemodynamics. We have successfully implemented EEG/fMRI at the Grenoble Hospital. This technique appeared to be helpful for presurgical evaluations. However, because of heterogeneous neurovascular coupling, the interpretation of activation maps remains difficult. Therefore, characterizing epilepsy cannot be done solely using EEG/fMRI and needs complementary investigations.GRENOBLE1-BU Sciences (384212103) / SudocSudocFranceF

Neural concomitants of remote memory in a comedian with exceptional verbal memory

Most studies exploring how remote memory is represented in the brain are based on strong episodic self-related components. Because of methodological reasons, much less is known about how the information concerning the semantic part of autobiographical memory is retrieved, and whether the brain correlates differ according to the autobiographical moment of the memory formation. In the present study, we explored the neural concomitants of the retrieval of texts learnt at different periods of life, in a comedian with exceptional verbal memory skills. This 49-year-old comedian was instructed to recite aloud a total of 30 texts he learnt during three different epochs: before the age of 15 years (E1), between the age of 15 and 25 years (E2), and after the age of 25 years (E3). The most salient activation was observed for memory from the farthest period, with a preponderance of the medial rostral prefrontal cortex (PFC) and of the precuneus. There was no hippocampal activation during text retrieval by comparison to a control condition, whatever the learning period. This study supports the assumption that the recall of remote semantic memories can occur without hippocampal activation. We discussed the activation of the rostral PFC during retrieval of the oldest (and best consolidated) memories as the possible involvement of control meta-memory processes rather than memory processes per se

Pulse Artifact Detection in Simultaneous EEG-fMRI Recording Based on EEG Map Topography

One of the major artifact corrupting electroencephalogram (EEG) acquired during functional magnetic resonance imaging (fMRI) is the pulse artifact (PA). It is mainly due to the motion of the head and attached electrodes and wires in the magnetic field occurring after each heartbeat. In this study we propose a novel method to improve PA detection by considering the strong gradient and inversed polarity between left and right EEG electrodes. We acquired high-density EEG-fMRI (256 electrodes) with simultaneous electrocardiogram (ECG) at 3T. PA was estimated as the voltage difference between right and left signals from the electrodes showing the strongest artifact (facial and temporal). Peaks were detected on this estimated signal and compared to the peaks in the ECG recording. We analyzed data from eleven healthy subjects, two epileptic patients and four healthy subjects with an insulating layer between electrodes and scalp. The accuracy of the two methods was assessed with three criteria: (i) standard deviation, (ii) kurtosis and (iii) confinement into the physiological range of the inter-peak intervals. We also checked whether the new method has an influence on the identification of epileptic spikes. Results show that estimated PA improved artifact detection in 15/17 cases, when compared to the ECG method. Moreover, epileptic spike identification was not altered by the correction. The proposed method improves the detection of pulse-related artifacts, particularly crucial when the ECG is of poor quality or cannot be recorded. It will contribute to enhance the quality of the EEG increasing the reliability of EEG-informed fMRI analysis

Pulse Artifact Detection in Simultaneous EEG–fMRI Recording Based on EEG Map Topography

One of the major artifact corrupting electroencephalogram (EEG) acquired during functional magnetic resonance imaging (fMRI) is the pulse artifact (PA). It is mainly due to the motion of the head and attached electrodes and wires in the magnetic field occurring after each heartbeat. In this study we propose a novel method to improve PA detection by considering the strong gradient and inversed polarity between left and right EEG electrodes. We acquired high-density EEG-fMRI (256 electrodes) with simultaneous electrocardiogram (ECG) at 3 T. PA was estimated as the voltage difference between right and left signals from the electrodes showing the strongest artifact (facial and temporal). Peaks were detected on this estimated signal and compared to the peaks in the ECG recording. We analyzed data from eleven healthy subjects, two epileptic patients and four healthy subjects with an insulating layer between electrodes and scalp. The accuracy of the two methods was assessed with three criteria: (i) standard deviation, (ii) kurtosis and (iii) confinement into the physiological range of the inter-peak intervals. We also checked whether the new method has an influence on the identification of epileptic spikes. Results show that estimated PA improved artifact detection in 15/17 cases, when compared to the ECG method. Moreover, epileptic spike identification was not altered by the correction. The proposed method improves the detection of pulse-related artifacts, particularly crucial when the ECG is of poor quality or cannot be recorded. It will contribute to enhance the quality of the EEG increasing the reliability of EEG-informed fMRI analysis

A comparative study of different artefact removal algorithms for EEG signals acquired during functional MRI.

International audienceIn electroencephalographic (EEG) measurements performed during functional Magnetic Resonance Imaging (fMRI), imaging and cardiac artefacts strongly contaminate the EEG signal. Several algorithms have been proposed to suppress these artefacts and most of them have shown important improvements with respect to uncorrected signals. However, the relative performances of these algorithms have not been properly assessed. In particular, it is not known to what extent such algorithms deteriorate the EEG signal of interest. In this study, we propose to cross-validate different methods proposed for artefact correction, using a forward model to generate EEG and MR-related artefacts. The methods are assessed under various experimental conditions (described in terms of EEG sampling rate, artefacts amplitude, frequency band of interest, etc.). Using experimental data, we also tested the performance of the correction methods for alpha rhythm imaging and for epileptic spike reconstruction. Results show that most of the methods allow the observation of the modulation of alpha rhythms and the identification of spikes, despite subtle differences between algorithms. They also show that over-filtering the data may degrade the EEG. Our results indicate that the optimal artefact removal technique should be chosen according to whether one is interested in fast (>10 Hz) vs. slow (<10 Hz) oscillations or in evoked vs. ongoing activity

EEG source imaging of brain states using spatiotemporal regression

Relating measures of electroencephalography (EEG) back to the underlying sources is a long-standing inverse problem. Here we propose a new method to estimate the EEG sources of identified electrophysiological states that represent spontaneous activity, or are evoked by a stimulus, or caused by disease or disorder. Our method has the unique advantage of seamlessly integrating a statistical significance of the source estimate while efficiently eliminating artifacts (e.g., due to eye blinks, eye movements, bad electrodes). After determining the electrophysiological states in terms of stable topographies using established methods (e.g.: ICA, PCA, k-means, epoch average), we propose to estimate these states' time courses through spatial regression of a General Linear Model (GLM). These time courses are then used to find EEG sources that have a similar time-course (using temporal regression of a second GLM). We validate our method using both simulated and experimental data. Simulated data allows us to assess the difference between source maps obtained by the proposed method and those obtained by applying conventional source imaging of the state topographies. Moreover, we use data from 7 epileptic patients (9 distinct epileptic foci localized by intracranial EEG) and 2 healthy subjects performing an eyes-open/eyes-closed task to elicit activity in the alpha frequency range. Our results indicate that the proposed EEG source imaging method accurately localizes the sources for each of the electrical brain states. Furthermore, our method is particularly suited for estimating the sources of EEG resting states or otherwise weak spontaneous activity states, a problem not adequately solved before