Dynamics of brain activity can reflect early signs of neurodegeneration

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Publikace nespadá pod Ústav výpočetní techniky, ale pod Středoevropský technologický institut. Oficiální stránka publikace je na webu muni.cz.
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GAJDOŠ Martin NOVÁKOVÁ Marie LAMOŠ Martin ŘÍHA Pavel REKTOROVÁ Irena MIKL Michal

Rok publikování 2022
Druh Konferenční abstrakty
Fakulta / Pracoviště MU

Středoevropský technologický institut

Citace
Popis Early detection of neurodegenerative disease is for the patient beneficious. Thus, this task is challenging and more relevant parameters for reliable detection are needed. Our aim is to present parameters of brain dynamics measured with magnetic resonance imaging as relevant markers of early signs of synucleinopathy. We use functional magnetic resonance data and sliding window analysis. We show the process of data processing, data extraction and dynamic parameters identification. We identified four states describing the dynamics of large scale brain networks and found significant alterations in mean dwell time in one of these states. Group with risk of neurodegeneration spent in this state significantly less time than group of healthy controls (p = 0.038) and the density of this state is significantly higher than in healthy controls controls (p = 0.038). Mean dwell time and density of this identified state might serve as reasonable marker in diagnosis of early stage of synucleinopathy.
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