Permittivity Coupling across Brain Regions Determines Seizure Recruitment in Partial Epilepsy

Proix, Timothée; Bartolomei, Fabricē; Chauvel, Patrick; Bernard, Christophe; Jirsa, Viktor K.

doi:10.1523/jneurosci.1570-14.2014

Cited by 109 publications

(122 citation statements)

References 60 publications

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“…This result paves the way towards a systematic study of spatio-temporal mixed-mode oscillations (MMOs) in spatially-extended systems, with the view of explaining the origin of MMOs observed in spatio-temporal signals modelling spike-frequency adaptation and synaptic depression [41]. The spatio-temporal structures discussed here are also directly relevant to neural mass and connectomic models, in which a discrete connectomic matrix replaces the heterogeneous kernel W [42]: canard structures in these models would offer a rigorous explanation of the brutal transitions observed, for instance, in models of partial epilepsy [43]. There is a general consensus that spike (and more generally burst) timings, durations and rates are involved in information coding in the brain [44].…”

Section: Discussionmentioning

confidence: 89%

Spatiotemporal canards in neural field equations

Avitabile¹,

Desroches²,

Knobloch³

2017

Phys. Rev. E

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Canards are special solutions to ordinary differential equations that follow invariant repelling slow manifolds for long time intervals. In realistic biophysical single cell models, canards are responsible for several complex neural rhythms observed experimentally, but their existence and role in spatially-extended systems is largely unexplored. We describe a novel type of coherent structure in which a spatial pattern displays temporal canard behavior. Using interfacial dynamics and geometric singular perturbation theory, we classify spatio-temporal canards and give conditions for the existence of folded-saddle and folded-node canards. We find that spatio-temporal canards are robust to changes in the synaptic connectivity and firing rate. The theory correctly predicts the existence of spatio-temporal canards with octahedral symmetry in a neural field model posed on the unit sphere.

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Section: Discussionmentioning

confidence: 89%

Spatiotemporal canards in neural field equations

Avitabile¹,

Desroches²,

Knobloch³

2017

Phys. Rev. E

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“…However, the propagation of seizures is a complex process that does not correspond to the classical propagation of the nerve flux. Indeed, long delays may occur from one region to the other, probably linked to gradual changes in the biologic properties of the involved regions . The anatomic sites involved during seizures depends on the structural connectivity; both cortical and subcortical structures are involved .…”

Section: Historical Considerations and Seeg Recordings Of Seizure Onsetmentioning

confidence: 99%

Defining epileptogenic networks: Contribution of SEEG and signal analysis

et al. 2017

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SUMMARYEpileptogenic networks are defined by the brain regions involved in the production and propagation of epileptic activities. In this review we describe the historical, methodologic, and conceptual bases of this model in the analysis of electrophysiologic intracerebral recordings. In the context of epilepsy surgery, the determination of cerebral regions producing seizures (i.e., the "epileptogenic zone") is a crucial objective. In contrast with a traditional focal vision of focal drug-resistant epilepsies, the concept of epileptogenic networks has been progressively introduced as a model better able to describe the complexity of seizure dynamics and realistically describe the distribution of epileptogenic anomalies in the brain. The concept of epileptogenic networks is historically linked to the development of the stereoelectroencephalography (SEEG) method and subsequent introduction of means of quantifying the recorded signals. Seizures, and preictal and interictal discharges produce clear patterns on SEEG. These patterns can be analyzed utilizing signal analysis methods that quantify high-frequency oscillations or changes in functional connectivity. Dramatic changes in SEEG brain connectivity can be described during seizure genesis and propagation within cortical and subcortical regions, associated with the production of different patterns of seizure semiology. The interictal state is characterized by networks generating abnormal activities (interictal spikes) and also by modified functional properties. The introduction of novel approaches to large-scale modeling of these networks offers new methods in the goal of better predicting the effects of epilepsy surgery. The epileptogenic network concept is a key factor in identifying the anatomic distribution of the epileptogenic process, which is particularly important in the context of epilepsy surgery.

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“…This is plausible, because a region that receives many incoming links without driving other regions may not be hyperexcitable. Future modelling work could help understanding better such phenomenon (Proix et al , 2014).…”

Section: Concordance Between Measures and Epileptogenicity Indexmentioning

confidence: 99%

Graph Measures of Node Strength for Characterizing Preictal Synchrony in Partial Epilepsy

et al. 2016

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The reference electrophysiological pattern at seizure onset is the "rapid discharge," as visible on intracerebral electroencephalography (EEG). This discharge typically corresponds to a decrease of synchrony across brain areas. In contrast, the preictal period can exhibit patterns of increased synchrony, which can be quantified by network measures. Our objective was to compare preictal synchrony with a quantification of the rapid discharge as provided by the epileptogenicity index (EI). We investigated 24 seizures from 12 patients recorded by stereotaxic EEG (SEEG). Seizures were classified visually as containing preictal synchrony or not. We computed pairwise nonlinear correlation (h(2)) across channels in the 8 sec preceding the rapid discharge. The sum of ingoing and outgoing links (IN and OUT node strength), as well as the sum of all links (total strength, TOT) were computed for each region. We tested several filtering schemes, and quantified the capacity of each strength measure to serve as a detector of regions with high EI values using a receiver operating characteristic (ROC) analysis. We found that the best correspondence between node strength and EI was obtained for the OUT and TOT measures, for signals filtered in the 15-40 Hz band-that is, for the band corresponding to the spiky part of epileptic discharges. In agreement with these results, we also found that the ROC results were improved when considering only seizures with visible synchronous patterns in the preictal period. Our results suggest that measuring strength of preictal connectivity graphs can bring useful clinical information on the epileptogenic zone.

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Permittivity Coupling across Brain Regions Determines Seizure Recruitment in Partial Epilepsy

Cited by 109 publications

References 60 publications

Spatiotemporal canards in neural field equations

Spatiotemporal canards in neural field equations

Defining epileptogenic networks: Contribution of SEEG and signal analysis

Graph Measures of Node Strength for Characterizing Preictal Synchrony in Partial Epilepsy

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