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.

Basic information

Original name

Dynamics of brain activity can reflect early signs of neurodegeneration

Authors

GAJDOŠ, Martin ; Marie NOVÁKOVÁ; Martin LAMOŠ ; Pavel ŘÍHA; Irena REKTOROVÁ and Michal MIKL

Edition

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

Other information

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

References:

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

Abstract

In the original language

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 project

Name: 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 infrastructures

Name: Czech-BioImaging II

Cite

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.

@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 and 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.

Přehled o publikaci