Epilepsy is a substantial disease burden and ~30% of patients do not respond to drug therapy. For these patients the only option is epilepsy surgery. Localization of the seizure generating areas of the brain often requires implantation of intracranial electrodes. Visual analysis of long-term recordings from large number of electrodes is extremely laborious and introduces significant human bias. Improving the presurgical diagnosis and increasing the information yield of invasive recordings requires faster and more objective quantitative analysis. It is well established that seizures emerge within functionally altered brain networks. In the proposed project we will apply complex network methods to quantify the organization of epileptic networks and develop innovative and more precise presurgical diagnostic tools. Identification of key components of the epileptic network will improve localization of seizure-generating regions, and patient-oriented network modelling approach will allow us to predict surgical outcomes.

Přibližně 30% pacientů s epilepsií neodpovídá na farmakologickou léčbu a lze u nich zvážit chirugické řešení. Určení oblasti oblasti, jejíž resekce je nezbytná, aby došlo k vymizení záchvatů, vyžaduje u řady pacientů implantaci intrakraniálních elektrod. Zrakové hodnocení dlouhodobých intrakraniálních záznamů představuje velmi komplikovaný a zdlouhavý proces, který je zatížený subjektivní chybou. Zvýšení informační výtěžnosti záznamů vyžaduje nové metodické postupy, které umožní rychlou a objektivní analýzu. Nejnovější poznatky prokazují, že záchvaty jsou projevem abnormální funkce mozkových sítí. Na základě těchto znalostí využijeme analýz z oboru komplexní dynamiky sítí a teorie grafů k vývoji inovativních diagnostických algoritmů, které zvýší klinickou výtěžnost intrakraniálních záznamů a zkvalitní předoperační diagnostiku. Nalezení síťových ukazatelů oblasti vzniku záchvatů umožní přesněji lokalizovat klíčové oblasti resekce. Vytvoření algoritmu, který modeluje epileptické sítě na základě pacientských dat, umožní predikci funkčního vlivu resekce a výsledku chirurgické léčby.

• MeSH
• diagnostické techniky neurologické MeSH
• diagnóza počítačová MeSH
• elektroencefalografie MeSH
• epilepsie chirurgie   MeSH
• intrakraniální tlak MeSH
• neurochirurgické výkony MeSH
• předoperační péče MeSH

• Konspekt
• Patologie. Klinická medicína
• NLK Obory
• neurochirurgie
• NLK Publikační typ
• závěrečné zprávy o řešení grantu AZV MZ ČR

The mechanism of seizure emergence and the role of brief interictal epileptiform discharges (IEDs) in seizure generation are two of the most important unresolved issues in modern epilepsy research. We found that the transition to seizure is not a sudden phenomenon, but is instead a slow process that is characterized by the progressive loss of neuronal network resilience. From a dynamical perspective, the slow transition is governed by the principles of critical slowing, a robust natural phenomenon that is observable in systems characterized by transitions between dynamical regimes. In epilepsy, this process is modulated by synchronous synaptic input from IEDs. IEDs are external perturbations that produce phasic changes in the slow transition process and exert opposing effects on the dynamics of a seizure-generating network, causing either anti-seizure or pro-seizure effects. We found that the multifaceted nature of IEDs is defined by the dynamical state of the network at the moment of the discharge occurrence.

• MeSH
• elektroencefalografie MeSH
• hipokampální oblast CA1 patofyziologie   MeSH
• hipokampus patofyziologie   MeSH
• lidé MeSH
• nervová síť patofyziologie   MeSH
• potkani Sprague-Dawley MeSH
• potkani Wistar MeSH
• synapse fyziologie   MeSH
• záchvaty patofyziologie   MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Complex spatiotemporal patterns, called chimera states, consist of coexisting coherent and incoherent domains and can be observed in networks of coupled oscillators. The interplay of synchrony and asynchrony in complex brain networks is an important aspect in studies of both the brain function and disease. We analyse the collective dynamics of FitzHugh-Nagumo neurons in complex networks motivated by its potential application to epileptology and epilepsy surgery. We compare two topologies: an empirical structural neural connectivity derived from diffusion-weighted magnetic resonance imaging and a mathematically constructed network with modular fractal connectivity. We analyse the properties of chimeras and partially synchronized states and obtain regions of their stability in the parameter planes. Furthermore, we qualitatively simulate the dynamics of epileptic seizures and study the influence of the removal of nodes on the network synchronizability, which can be useful for applications to epileptic surgery.

• MeSH
• difuzní magnetická rezonance MeSH
• epilepsie diagnostické zobrazování   MeSH
• lidé MeSH
• mozek * fyziologie   MeSH
• nervová síť fyziologie   MeSH
• nervové vedení fyziologie   MeSH
• teoretické modely MeSH
• záchvaty diagnostické zobrazování   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• práce podpořená grantem MeSH
• srovnávací studie MeSH

In vitro brain tissue preparations allow the convenient and affordable study of brain networks and have allowed us to garner molecular, cellular, and electrophysiologic insights into brain function with a detail not achievable in vivo. Preparations from both rodent and human postsurgical tissue have been utilized to generate in vitro electrical activity similar to electrographic activity seen in patients with epilepsy. A great deal of knowledge about how brain networks generate various forms of epileptiform activity has been gained, but due to the multiple in vitro models and manipulations used, there is a need for a standardization across studies. Here, we describe epileptiform patterns generated using in vitro brain preparations, focusing on issues and best practices pertaining to recording, reporting, and interpretation of the electrophysiologic patterns observed. We also discuss criteria for defining in vitro seizure-like patterns (i.e., ictal) and interictal discharges. Unifying terminologies and definitions are proposed. We suggest a set of best practices for reporting in vitro studies to favor both efficient across-lab comparisons and translation to in vivo models and human studies.

• Publikační typ
• časopisecké články MeSH

Pathological high-frequency oscillations are a novel marker used to improve the delineation of epileptogenic tissue and, hence, the outcome of epilepsy surgery. Their practical clinical utilization is curtailed by the inability to discriminate them from physiological oscillations due to frequency overlap. Although it is well documented that pathological HFOs are suppressed by antiepileptic drugs (AEDs), the effect of AEDs on normal HFOs is not well known. In this experimental study, we have explored whether physiological HFOs (sharp-wave ripples) of hippocampal origin respond to AED treatment. The results show that application of a single dose of levetiracetam or lacosamide does not reduce the rate of sharp-wave ripples. In addition, it seems that these new generation drugs do not negatively affect the cellular and network mechanisms involved in sharp-wave ripple generation, which may provide a plausible explanation for the absence of significant negative effects on cognitive functions of these drugs, particularly on memory.

• Publikační typ
• časopisecké články MeSH

Maximum entropy estimation is of broad interest for inferring properties of systems across many disciplines. Using a recently introduced technique for estimating the maximum entropy of a set of random discrete variables when conditioning on bivariate mutual informations and univariate entropies, we show how this can be used to estimate the direct network connectivity between interacting units from observed activity. As a generic example, we consider phase oscillators and show that our approach is typically superior to simply using the mutual information. In addition, we propose a nonparametric formulation of connected informations, used to test the explanatory power of a network description in general. We give an illustrative example showing how this agrees with the existing parametric formulation, and demonstrate its applicability and advantages for resting-state human brain networks, for which we also discuss its direct effective connectivity. Finally, we generalize to continuous random variables and vastly expand the types of information-theoretic quantities one can condition on. This allows us to establish significant advantages of this approach over existing ones. Not only does our method perform favorably in the undersampled regime, where existing methods fail, but it also can be dramatically less computationally expensive as the cardinality of the variables increases.

• MeSH
• entropie MeSH
• informační systémy * MeSH
• lidé MeSH
• nervová síť MeSH
• teoretické modely MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• práce podpořená grantem MeSH

High-frequency oscillations (HFOs) are a type of brain activity that is recorded from brain regions capable of generating seizures. Because of the close association of HFOs with epileptogenic tissue and ictogenesis, understanding their cellular and network mechanisms could provide valuable information about the organization of epileptogenic networks and how seizures emerge from the abnormal activity of these networks. In this review, we summarize the most recent advances in the field of HFOs and provide a critical evaluation of new observations within the context of already established knowledge. Recent improvements in recording technology and the introduction of optogenetics into epilepsy research have intensified experimental work on HFOs. Using advanced computer models, new cellular substrates of epileptic HFOs were identified and the role of specific neuronal subtypes in HFO genesis was determined. Traditionally, the pathogenesis of HFOs was explored mainly in patients with temporal lobe epilepsy and in animal models mimicking this condition. HFOs have also been reported to occur in other epileptic disorders and models such as neocortical epilepsy, genetically determined epilepsies, and infantile spasms, which further support the significance of HFOs in the pathophysiology of epilepsy. It is increasingly recognized that HFOs are generated by multiple mechanisms at both the cellular and network levels. Future studies on HFOs combining novel high-resolution in vivo imaging techniques and precise control of neuronal behavior using optogenetics or chemogenetics will provide evidence about the causal role of HFOs in seizures and epileptogenesis. Detailed understanding of the pathophysiology of HFOs will propel better HFO classification and increase their information yield for clinical and diagnostic purposes.

• MeSH
• elektroencefalografie MeSH
• epilepsie patofyziologie   MeSH
• lidé MeSH
• mapování mozku * MeSH
• mozek patofyziologie   MeSH
• mozkové vlny fyziologie   MeSH
• počítačové zpracování signálu MeSH
• záchvaty patofyziologie   MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

In vitro preparations are a powerful tool to explore the mechanisms and processes underlying epileptogenesis and ictogenesis. In this review, we critically review the numerous in vitro methodologies utilized in epilepsy research. We provide support for the inclusion of detailed descriptions of techniques, including often ignored parameters with unpredictable yet significant effects on study reproducibility and outcomes. In addition, we explore how recent developments in brain slice preparation relate to their use as models of epileptic activity.

• MeSH
• epilepsie patologie   MeSH
• modely nemocí na zvířatech MeSH
• mozek patofyziologie   MeSH
• mozkové vlny fyziologie   MeSH
• orgánové kultury - kultivační techniky metody   normy   MeSH
• poradní výbory MeSH
• techniky in vitro * přístrojové vybavení   metody   normy   MeSH
• zvířata MeSH
• Check Tag
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• přehledy MeSH
• Research Support, N.I.H., Extramural MeSH
• Research Support, U.S. Gov't, Non-P.H.S. MeSH

Reconstructing the structural connectivity between interacting units from observed activity is a challenge across many different disciplines. The fundamental first step is to establish whether or to what extent the interactions between the units can be considered pairwise and, thus, can be modeled as an interaction network with simple links corresponding to pairwise interactions. In principle, this can be determined by comparing the maximum entropy given the bivariate probability distributions to the true joint entropy. In many practical cases, this is not an option since the bivariate distributions needed may not be reliably estimated or the optimization is too computationally expensive. Here we present an approach that allows one to use mutual informations as a proxy for the bivariate probability distributions. This has the advantage of being less computationally expensive and easier to estimate. We achieve this by introducing a novel entropy maximization scheme that is based on conditioning on entropies and mutual informations. This renders our approach typically superior to other methods based on linear approximations. The advantages of the proposed method are documented using oscillator networks and a resting-state human brain network as generic relevant examples.

• MeSH
• entropie MeSH
• informační systémy * MeSH
• korelace dat MeSH
• neuronové sítě MeSH
• teoretické modely MeSH
• Publikační typ
• práce podpořená grantem MeSH

Highlights Simultaneous epileptiform LFPs and single-cell activity can be recorded in the membrane chamber.Interneuron firing can be linked to epileptiform high frequency activity.Fast ripples, unique to chronic epilepsy, can be modeled in ex vivo tissue from TeNT-treated rats. Traditionally, visually-guided patch clamp in brain slices using submerged recording conditions has been required to characterize the activity of individual neurons. However, due to limited oxygen availability, submerged conditions truncate fast network oscillations including epileptiform activity. Thus, it is technically challenging to study the contribution of individual identified neurons to fast network activity. The membrane chamber is a submerged-style recording chamber, modified to enhance oxygen supply to the slice, which we use to demonstrate the ability to record single-cell activity during in vitro epilepsy. We elicited epileptiform activity using 9 mM potassium and simultaneously recorded from fluorescently labeled interneurons. Epileptiform discharges were more reliable than in standard submerged conditions. During these synchronous discharges interneuron firing frequency increased and action potential amplitude progressively decreased. The firing of 15 interneurons was significantly correlated with epileptiform high frequency activity (HFA; ~100-500 Hz) cycles. We also recorded epileptiform activity in tissue prepared from chronically epileptic rats, treated with intrahippocampal tetanus neurotoxin. Four of these slices generated fast ripple activity, unique to chronic epilepsy. We showed the membrane chamber is a promising new in vitro environment facilitating patch clamp recordings in acute epilepsy models. Further, we showed that chronic epilepsy can be better modeled using ex vivo brain slices. These findings demonstrate that the membrane chamber facilitates previously challenging investigations into the neuronal correlates of epileptiform activity in vitro.

• MeSH
• elektrokortikografie MeSH
• epilepsie * diagnostické zobrazování   MeSH
• interneurony MeSH
• krysa rodu rattus MeSH
• metoda terčíkového zámku * metody   MeSH
• modely nemocí na zvířatech MeSH
• mozková kůra diagnostické zobrazování   MeSH
• techniky in vitro metody   MeSH
• zvířata MeSH
• Check Tag
• krysa rodu rattus MeSH
• zvířata MeSH
• Publikační typ
• práce podpořená grantem MeSH