Etude des paramètres d'un modèle de génération de signaux EEG intracérébraux : synchronisation, conductivité cérébrale et surface corticale

- La stéréo-électroencéphalographie (SEEG) permet d'enregistrer l'activité électrique cérébrale en profondeur (électrodes intracérébrales, signaux EEG de profondeur). Ce travail est centré sur l'étude des relations qui existent entre les dynamiques qui s'expriment dans les signaux SEEG et l'organisation spatio-temporelle des sources neuronales à l'origine de ces signaux. Ce problème est abordé au travers d'un modèle réaliste de génération des signaux SEEG à partir d'un champ de dipôles correspondant à une source néocorticale étendue formée par un ensemble de populations de neurones interconnectées. Les résultats montrent que le modèle est capable de générer des signaux comparables à des signaux SEEG réels enregistrés lors de processus épileptiques (pointes épileptiques). Les signaux simulés permettent alors d'interpréter les signaux réels par rapport aux problèmes liés à la source (surface, synchronisation des populations de neurones) et au milieu (conductivité)

Modèle de génération simultanée des signaux EEG de surface et de profondeur

Ce travail porte sur l'interprétation des signaux électroencéphalographiques (EEG) et stéréo-électroencéphalographiques (SEEG) acquis chez des patients épileptiques candidats à la chirurgie. Cette question est abordée au travers d'une modélisation réaliste des signaux EEG et SEEG, qui repose sur une représentation physiologiquement pertinente des sources de l'activité cérébrale associant un modèle biophysique de sources dipolaires et un modèle biomathématique de populations neuronales. Les signaux induits sur les capteurs de surface et de profondeur sont ensuite obtenus par la résolution du problème direct dans le volume conducteur de la tête. Le modèle complet permet d'étudier les relations existant entre la configuration spatio-temporelle des sources d'activité et les propriétés des signaux observés en surface et en profondeur

A realistic spatiotemporal source model for EEG activity: Application to the reconstruction of epileptic depth-EEG signals.

International audienceThe context of this work is the interpretation of depth-EEG signals recorded in epileptic patients. This study focuses on the relationship between spatial and temporal properties of neuronal sources and depth-EEG signals observed along intracerebral electrodes (source/sensor relationship). We developed an extended source model which connects two levels of representation: a model of coupled neuronal populations and a distributed current dipole model. This model was used to simulate epileptic spiking depth-EEG signals from the forward solution at each intracerebral sensor location. Results showed that realistic spikes were obtained in the model under two specific conditions: a sufficiently large spatial extension of the neocortical source and a high degree of coupling between activated neuronal populations composing this extended source

A novel approach for multiscale source analysis and modeling of epileptic spikes

Multiscale recordings of brain electrical activity are often performed for presurgical evaluation in patients with focal epilepsy to facilitate the identification and precise delineation of the epileptogenic zone. However, data regarding the concordance of source models derived from recordings on different scales and their reciprocal validation against clinical outcomes remains scarce. This study aims to define a common source model that accurately depicts both scalp EEG and subdural EEG (ECoG) interictal spikes. To this purpose, the sLORETA method was applied to averaged spikes and source reconstruction results were implemented to outline the location and extent of an epileptic cortical patch. This estimated patch served as the basis for the spatiotemporal source model in a generative model of EEG. Spike activity was simulated on both scalp EEG and ECoG signal scales, with simulated traces resembling measured traces regarding their spatial distribution and amplitude compared to background. Simulated spikes served for the evaluation of source reconstruction with a known generator topography. The described setup allows for the validation and, ultimately, for the refinement of source reconstruction methods. It provides novel insights towards a thorough understanding of physiological and pathological brain processes and their representation in neuroelectric measurements

Fourth order approaches for localization of brain current sources.

International audienceTwo high resolution methods solving inverse problems potentially ill-posed, named 4-MUSIC and 4-RapMUSIC, are proposed. They allow for localization of brain current sources with unconstrained orientations from surface electro-or magneto-encephalographic data using spherical or realistic head geometries. The 4-MUSIC and 4-RapMUSIC methods are based on i) the separability of the data transfer matrix as a function of location and orientation parameters and ii) the fourth order (FO) virtual array theory. In addition, 4-RapMUSIC uses the deflation concept extended to FO statistics accounting for the presence of potentially but not totally coherent sources. Computer results display the superiority of the 4-RapMUSIC approach in different situations (two closed sources, additive Gaussian noise with unknown spatial covariance, ...) especially over classical algorithms

Realistic synthetic background neuronal activity for the analysis of MEG probe configurations.

International audienceMagnetoencephalography (MEG) sensors are capable of recording the tiny magnetic activity from the brain. They can be constituted of either magnetometers or gradiometers that respectively record the magnetic field or its gradient. In this paper, we present a framework for constructing realistic MEG signals. This framework can be used to test different probe configurations and source localization algorithms. The methodology of generation of synthetic signals is presented, and synthetic signals are compared to real signals. Paroxysmal activity generated with this model and originating from a deep cerebral source is determined with two different localization algorithms. Preliminary results show that gradiometers even with a short baseline perform close to magnetometer and that the use of hybrid systems should be further investigated

From mesial temporal lobe to temporoperisylvian seizures: a quantified study of temporal lobe seizure networks.

International audiencePURPOSE: The determination of epileptogenic structures in partial epilepsy is crucial in the context of epilepsy surgery. In this study we have quantified the "epileptogenicity" of mesial temporal lobe structures (M), lateral neocortical regions (L), and extratemporal perisylvian structures (ET) in patients with temporal lobe epilepsy (TLE), in order to classify the brain networks involved in seizure generation. METHODS: Thirty-four patients having TLE investigated by intracerebral recordings using stereotactic electroencephalography (EEG) (SEEG) were selected. Epileptogenicity of M, L, and ET structures was quantified according to the "epileptogenicity index" (EI), a new way to quantify rapid discharges at seizure onset, ranging from 0 (no epileptogenicity) to 1 (maximal epileptogenicity). RESULTS: Automatic clustering using EI values from M, L, and ET separated patients into four classes: mesial group (max EI in M), lateral group (max EI in L), mesiolateral group (high EI in both M and L) and temporoperisylvian group (TPS) (high values in ET). The median number of highly epileptogenic structures (defined by EI >0.3) was four, a result confirming that most TLE is organized as "epileptogenic networks." We found that the duration of epilepsy was correlated with the number of epileptogenic structures and that surgical prognosis was also related to the extent of the epileptogenicity in the brain. CONCLUSIONS: Several distinct epileptogenic networks are involved in seizure generation in TLE. Findings advocate for a progressive recruitment of epileptogenic structures in human brain with time