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.

Simultaneous subdural and scalp EEG correlates of frontal lobe epileptic sources.

OBJECTIVE: To assess the visibility and detectability in scalp electroencephalography (EEG) of cortical sources in frontal lobe epilepsy (FLE) as to their localization, and the extent and amplitude of activation. METHODS: We analyzed the simultaneous subdural and scalp interictal EEG recordings of 14 patients with refractory frontal lobe epilepsy (FLE) associated with focal cortical dysplasia. Subdural spike types were identified and averaged for source localization and detection of their scalp EEG correlates. Both raw and averaged scalp EEG segments were reviewed for spikes, blinded to subdural segments. We further analyzed the correlation of spike-to-background amplitude ratios in subdural and scalp EEG. RESULTS: We identified 36 spike types in subdural EEG, corresponding to 29 distinct sources. Four of 29 sources were visible by visual evaluation of scalp EEG and six additional sources were detectable after averaging: four in the medial frontal, two in the dorsolateral gyri, two in the depth of dorsolateral sulci, and two in the basal frontal region. Cortical sources generating scalp-detectable spikes presented a median of 6 cm(2) of activated cortical convexity surface and a subdural spike-to-background-amplitude ratio >8. These sources were associated with a higher number of activated subdural grid contacts and a higher subdural spike-to-background amplitude ratio than sources generating non-scalp-detectable spikes. SIGNIFICANCE: Not only dorsolateral but also basal and medial sources can be detectable in FLE. This is the first in vivo demonstration derived from simultaneous subdural and scalp EEG recordings of the complementary significance of extensive source activation and higher subdural spike-to-background amplitude ratio in the detection of cortical sources in FLE.

Reference-based source separation method for identification of brain regions involved in a reference state from intracerebral EEG.

In this paper, we present a fast method to extract the sources related to interictal epileptiform state. The method is based on general eigenvalue decomposition using two correlation matrices during: 1) periods including interictal epileptiform discharges (IED) as a reference activation model and 2) periods excluding IEDs or abnormal physiological signals as background activity. After extracting the most similar sources to the reference or IED state, IED regions are estimated by using multiobjective optimization. The method is evaluated using both realistic simulated data and actual intracerebral electroencephalography recordings of patients suffering from focal epilepsy. These patients are seizure-free after the resective surgery. Quantitative comparisons of the proposed IED regions with the visually inspected ictal onset zones by the epileptologist and another method of identification of IED regions reveal good performance.

Source reconstruction based on subdural EEG recordings adds to the presurgical evaluation in refractory frontal lobe epilepsy.

OBJECTIVE: In presurgical investigations of refractory frontal lobe epilepsy, subdural EEG recordings offer extensive cortical coverage, but may overlook deep sources. Electrical Source Localization (ESL) from subdural recordings could overcome this sampling limitation. This study aims to assess the clinical relevance of this new method in refractory frontal lobe epilepsy associated with focal cortical dysplasia. METHODS: In 14 consecutive patients, we retrospectively compared: (i) the ESL of interictal spikes to the conventional irritative and seizure onset zones; (ii) the surgical outcome of cases with congruent ESL and resection volume to cases with incongruent ESL and resection volume. Each spike type was averaged to serve as a template for ESL by the MUSIC and sLORETA algorithms. Results were superimposed on the corresponding pre and post-surgical MRI. RESULTS: Both ESL methods were congruent and consistent with conventional electroclinical analysis in all patients. In 7 cases, ESL identified a common deep source for spikes of different 2D localizations. The inclusion of ESL in the resection volume correlated with seizure freedom. CONCLUSIONS: ESL from subdural recordings provided clinically relevant results in patients with refractory frontal lobe epilepsy. SIGNIFICANCE: ESL complements the conventional analysis of subdural recordings. Its potential in improving tailored resections and surgical outcomes should be prospectively assessed.

Altered θ coupling between medial entorhinal cortex and dentate gyrus in temporal lobe epilepsy.

PURPOSE: Temporal lobe epilepsy is often accompanied by neuron loss and rewiring in the hippocampus. We hypothesized that the interaction of subnetworks of the entorhinal-hippocampal loop between epileptic events should show significant signatures of these pathologic changes. METHODS: We combined simultaneous recording of local field potentials in entorhinal cortex (EC) and dentate gyrus (DG) in freely behaving kainate-injected mice with histologic analyses and computational modeling. KEY FINDINGS: In healthy mice, theta band activity was synchronized between EC and DG. In contrast, in epileptic mice, theta activity in the EC was delayed with respect to the DG. A computational neural mass model suggests that hippocampal cell loss imbalances the coupling of subnetworks, introducing the shift. SIGNIFICANCE: We show that pathologic dynamics in epilepsy encompass ongoing activity in the entorhinal-hippocampal loop beyond acute epileptiform activity. This predominantly affects theta band activity, which links this shift in entorhinal-hippocampal interaction to behavioral aspects in epilepsy.

Computational modeling of epileptic activity: from cortical sources to EEG signals.

In epileptic patients candidate to surgery, the interpretation of EEG signals recorded either within (depth EEG) or at the surface (scalp EEG) of the head is a crucial issue to determine epileptogenic brain regions and to define subsequent surgical strategy. This task remains difficult as there is no simple relationship between the spatiotemporal features of neuronal generators (convoluted cortical dipole layers) and the electric field potentials recorded by the electrodes. Indeed, this relationship depends on the complex interaction of several factors regarding involved cortical sources: location, area, geometry, and synchronization of neuronal activity. A computational model is proposed to address this issue. It relies on a neurophysiologically relevant model of EEG signals, which combines an accurate description of both the intracerebral sources of activity and the transfer function between dipole layers and recorded field potentials. The model is used, on the one hand, to quantitatively study the influence of source-related parameters on the properties of simulated signals, and on the other hand, to jointly analyze depth EEG and scalp EEG signals. In this article, the authors review some of the results obtained from the model with respect to the literature on the interpretation of EEG signals in the context of epilepsy.

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

PURPOSE: 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.

Brain source localization using a fourth-order deflation scheme.

In this paper, a high-resolution method for solving potentially ill-posed inverse problems is proposed. This method named FO-D-MUSIC allows for localization of brain current sources with unconstrained orientations from surface electroencephalographic (EEG) or magnetoencephalographic (MEG) data using spherical or realistic head geometries. The FO-D-MUSIC method is based on the following: 1) the separability of the data transfer matrix as a function of location and orientation parameters, 2) the fourth-order (FO) virtual array theory, and 3) the deflation concept extended to FO statistics accounting for the presence of potentially but not completely statistically dependent sources. Computer results display the superiority of the FO-D-MUSIC approach in different situations (very closed sources, small number of electrodes, additive Gaussian noise with unknown spatial covariance, etc.) compared to classical algorithms.

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

Magnetoencephalography (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.

A physiologically plausible spatio-temporal model for EEG signals recorded with intracerebral electrodes in human partial epilepsy.

Stereoelectroencephalography (depth-EEG signals) is a presurgical investigation technique of drug-resistant partial epilepsy, in which multiple sensor intracerebral electrodes are used to directly record brain electrical activity. In order to interpret depth-EEG signals, we developed an extended source model which connects two levels of representation: (1) a distributed current dipole model which describes the spatial distribution of neuronal sources; (2) a model of coupled neuronal populations which describes their temporal dynamics. From this extended source model, depth-EEG signals were simulated from the forward solution at each electrode sensor located inside the brain. Results showed that realistic transient epileptiform activities (spikes) are obtained under specific conditions in the model in terms of degree of coupling between neuronal populations and spatial extent of the source. In particular, the cortical area involved in the generation of epileptic spikes was estimated to vary from 18 to 25 cm2, for brain conductivity values ranging from 30 to 35 x 10(-5) S/mm, for high coupling degree between neuronal populations and for a volume conductor model that accounts for the three main tissues of the head (brain, skull, and scalp). This study provides insight into the relationship between spatio-temporal properties of cortical neuronal sources and depth-EEG signals.

Fourth order approaches for localization of brain current sources.

Two 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.