GAJDOŠ, Martin, Marie NOVÁKOVÁ, Martin LAMOŠ, Pavel ŘÍHA, Irena REKTOROVÁ and Michal MIKL. Dynamics of brain activity can reflect early signs of neurodegeneration. In 2022 International Conference on Electrical, Computer and Energy Technologies (ICECET). 2022.
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Basic information
Original name Dynamics of brain activity can reflect early signs of neurodegeneration
Authors GAJDOŠ, Martin (203 Czech Republic, guarantor, belonging to the institution), Marie NOVÁKOVÁ (203 Czech Republic, belonging to the institution), Martin LAMOŠ (203 Czech Republic, belonging to the institution), Pavel ŘÍHA (203 Czech Republic, belonging to the institution), Irena REKTOROVÁ (203 Czech Republic, belonging to the institution) and Michal MIKL (203 Czech Republic, belonging to the institution).
Edition 2022 International Conference on Electrical, Computer and Energy Technologies (ICECET), 2022.
Other information
Original language English
Type of outcome Conference abstract
Field of Study 30103 Neurosciences
Country of publisher Czech Republic
Confidentiality degree is not subject to a state or trade secret
WWW URL
RIV identification code RIV/00216224:14740/22:00134729
Organization unit Central European Institute of Technology
Keywords in English magnetic resonance imaging; sliding window analysis; neurodegeneration
Tags CF MAFIL, rivok
Tags International impact, Reviewed
Changed by Changed by: Mgr. Eva Dubská, učo 77638. Changed: 21/5/2024 12:21.
Abstract
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.
Links
NU21J-04-00077, research and development projectName: Využití dynamických parametrů funkční konektivity mozku jako diagnostického biomarkeru neurodegenerativních nemocí
Investor: Ministry of Health of the CR, Biomarkers of neurodegenerative diseases based on dynamic functional connectivity, Subprogram 2 - junior
90129, large research infrastructuresName: Czech-BioImaging II
PrintDisplayed: 22/7/2024 23:33