Dynamics of brain activity can reflect early signs of
neurodegeneration

a 2022

Dynamics of brain activity can reflect early signs of neurodegeneration

GAJDOŠ, Martin, Marie NOVÁKOVÁ, Martin LAMOŠ, Pavel ŘÍHA, Irena REKTOROVÁ et. al.

Základní údaje

Originální název

Dynamics of brain activity can reflect early signs of neurodegeneration

Autoři

GAJDOŠ, Martin (203 Česká republika, garant, domácí), Marie NOVÁKOVÁ (203 Česká republika, domácí), Martin LAMOŠ (203 Česká republika, domácí), Pavel ŘÍHA (203 Česká republika, domácí), Irena REKTOROVÁ (203 Česká republika, domácí) a Michal MIKL (203 Česká republika, domácí)

Vydání

2022 International Conference on Electrical, Computer and Energy Technologies (ICECET), 2022

Další údaje

Jazyk

angličtina

Typ výsledku

Konferenční abstrakt

Obor

30103 Neurosciences

Stát vydavatele

Česká republika

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Kód RIV

RIV/00216224:14740/22:00134729

Organizační jednotka

Středoevropský technologický institut

Klíčová slova anglicky

magnetic resonance imaging; sliding window analysis; neurodegeneration

Štítky

CF MAFIL, rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 21. 5. 2024 12:21, Mgr. Eva Dubská

Anotace

V originále

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.

Návaznosti

NU21J-04-00077, projekt VaV

Název: Využití dynamických parametrů funkční konektivity mozku jako diagnostického biomarkeru neurodegenerativních nemocí

Investor: Ministerstvo zdravotnictví ČR, Využití dynamických parametrů funkční konektivity mozku jako diagnostického biomarkeru neurodegenerativních nemocí, Podprogram 2 - juniorský - výzkumníci do 35 let

90129, velká výzkumná infrastruktura

Název: Czech-BioImaging II

Citovat

GAJDOŠ, Martin, Marie NOVÁKOVÁ, Martin LAMOŠ, Pavel ŘÍHA, Irena REKTOROVÁ a Michal MIKL. Dynamics of brain activity can reflect early signs of neurodegeneration. In 2022 International Conference on Electrical, Computer and Energy Technologies (ICECET). 2022.

@proceedings{2401038,
   author = {Gajdoš, Martin and Nováková, Marie and Lamoš, Martin and Říha, Pavel and Rektorová, Irena and Mikl, Michal},
   booktitle = {2022 International Conference on Electrical, Computer and Energy Technologies (ICECET)},
   keywords = {magnetic resonance imaging; sliding window analysis; neurodegeneration},
   language = {eng},
   title = {Dynamics of brain activity can reflect early signs of neurodegeneration},
   url = {https://ieeexplore.ieee.org/document/9872993},
   year = {2022}
}

TY  - CONF
ID  - 2401038
AU  - Gajdoš, Martin - Nováková, Marie - Lamoš, Martin - Říha, Pavel - Rektorová, Irena - Mikl, Michal
PY  - 2022
TI  - Dynamics of brain activity can reflect early signs of neurodegeneration
KW  - magnetic resonance imaging
KW  - sliding window analysis
KW  - neurodegeneration
UR  - https://ieeexplore.ieee.org/document/9872993
N2  - 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.
ER  -

GAJDOŠ, Martin, Marie NOVÁKOVÁ, Martin LAMOŠ, Pavel ŘÍHA, Irena REKTOROVÁ a Michal MIKL. Dynamics of brain activity can reflect early signs of neurodegeneration. In \textit{2022 International Conference on Electrical, Computer and Energy Technologies (ICECET)}. 2022.

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