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Your search keyword '"Jan Chvojka"' showing total 3 results
Start Over Author "Jan Chvojka" Topic medicine
3 results on '"Jan Chvojka"'

1. Computational modeling allows unsupervised classification of epileptic brain states across species

Author

Isa Dallmer-Zerbe, Nikola Jajcay, Jan Chvojka, Radek Janca, Petr Jezdik, Pavel Krsek, Petr Marusic, Premysl Jiruska, and Jaroslav Hlinka

Subjects
Medicine, Science
Abstract

Abstract Current advances in epilepsy treatment aim to personalize and responsively adjust treatment parameters to overcome patient heterogeneity in treatment efficiency. For tailoring treatment to the individual and the current brain state, tools are required that help to identify the patient- and time-point-specific parameters of epilepsy. Computational modeling has long proven its utility in gaining mechanistic insight. Recently, the technique has been introduced as a diagnostic tool to predict individual treatment outcomes. In this article, the Wendling model, an established computational model of epilepsy dynamics, is used to automatically classify epileptic brain states in intracranial EEG from patients (n = 4) and local field potential recordings from in vitro rat data (high-potassium model of epilepsy, n = 3). Five-second signal segments are classified to four types of brain state in epilepsy (interictal, preonset, onset, ictal) by comparing a vector of signal features for each data segment to four prototypical feature vectors obtained by Wendling model simulations. The classification result is validated against expert visual assessment. Model-driven brain state classification achieved a classification performance significantly above chance level (mean sensitivity 0.99 on model data, 0.77 on rat data, 0.56 on human data in a four-way classification task). Model-driven prototypes showed similarity with data-driven prototypes, which we obtained from real data for rats and humans. Our results indicate similar electrophysiological patterns of epileptic states in the human brain and the animal model that are well-reproduced by the computational model, and captured by a key set of signal features, enabling fully automated and unsupervised brain state classification in epilepsy.

Published
2023
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2. The role of interictal discharges in ictogenesis - A dynamical perspective

Author

Premysl Jiruska, John G. R. Jefferys, Wei-Chih Chang, Ondrej Novak, Jan Kudláček, Filip Tomaska, Jakub Otáhal, and Jan Chvojka

Subjects
Neurons, education.field_of_study, Heterogeneous group, Epilepsy, Perspective (graphical), Population, Acquired epilepsy, Electroencephalography, medicine.disease, Network activity, 03 medical and health sciences, Behavioral Neuroscience, 0302 clinical medicine, Neurology, Seizures, medicine, Humans, Ictal, 030212 general & internal medicine, Neurology (clinical), education, Psychology, Neuroscience, 030217 neurology & neurosurgery
Abstract

Interictal epileptiform discharge (IED) is a traditional hallmark of epileptic tissue that is generated by the synchronous activity of a population of neurons. Interictal epileptiform discharges represent a heterogeneous group of pathological activities that differ in shape, duration, spatiotemporal distribution, underlying cellular and network mechanisms, and their relationship to seizure genesis. The exact role of IEDs in epilepsy is still not well understood, and there remains a persistent dichotomy about the impact on IEDs on seizures. Proseizure, antiseizure, and no impact on ictogenesis have all been described in previous studies. In this article, we review the existing knowledge on the role of interictal discharges in seizure genesis, and we discuss how dynamical approaches to ictogenesis can explain the existing dichotomy about the multifaceted role of IEDs in ictogenesis. This article is part of the Special Issue "NEWroscience 2018".

Published
2019

3. Loss of neuronal network resilience precedes seizures and determines the ictogenic nature of interictal synaptic perturbations

Author

Premysl Jiruska, Wei-Chih Chang, Milan Paluš, Dean R. Freestone, Michal Hadrava, Mark J. Cook, Radek Janca, Andrew D. Powell, Matias I. Maturana, Vojtech Kumpost, Jakub Otáhal, Jan Kudlacek, Philippa J. Karoly, Jaroslav Hlinka, John G. R. Jefferys, and Jan Chvojka

Subjects
0301 basic medicine, Physics, medicine.diagnostic_test, Nerve net, Mechanism (biology), General Neuroscience, Electroencephalography, medicine.disease, 03 medical and health sciences, Epilepsy, 030104 developmental biology, 0302 clinical medicine, medicine.anatomical_structure, medicine, Biological neural network, Ictal, Natural phenomenon, Resilience (network), Neuroscience, 030217 neurology & neurosurgery
Abstract

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.

Published
2018
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