Chimera states in brain networks: Empirical neural vs. modular fractal connectivity

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00023752%3A_____%2F18%3A43919972" target="_blank" >RIV/00023752:_____/18:43919972 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/67985823:_____/18:00489894 RIV/67985807:_____/18:00489894

Výsledek na webu

<a href="https://aip.scitation.org/doi/10.1063/1.5009812" target="_blank" >https://aip.scitation.org/doi/10.1063/1.5009812</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1063/1.5009812" target="_blank" >10.1063/1.5009812</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Chimera states in brain networks: Empirical neural vs. modular fractal connectivity

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Chimera states in brain networks: Empirical neural vs. modular fractal connectivity

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30103 - Neurosciences (including psychophysiology)

Projekt

<a href="/cs/project/LO1611" target="_blank" >LO1611: Udržitelnost pro Národní ústav duševního zdraví</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Chaos

ISSN

1054-1500

e-ISSN

—

Svazek periodika

28

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

10

Strana od-do

"Article Number: 045112"

Kód UT WoS článku

000431142000042

EID výsledku v databázi Scopus

2-s2.0-85045270801