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Erschienen in:
Analysis of the Acoustic Power Emitted by a Physiotherapeutic Ultrasound Equipment Used at the Brazilian Air Force Academy Kapitel lesen Erstes Kapitel lesen

2022 | OriginalPaper | Buchkapitel

Resting-State Brain in Cognitive Decline: Analysis of Brain Network Architecture Using Graph Theory

verfasst von : C. M. Maulaz, D. B. A. Mantovani, A. M. Marques da Silva

Erschienen in: XXVII Brazilian Congress on Biomedical Engineering

Verlag: Springer International Publishing

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Abstract

Resting-State functional magnetic resonance imaging (rs-fMRI) provides the assessment of some brain functions without tasks. Through rs-fMRI, it is possible to discover that the brain is organized in spatially distributed and interconnected brain regions. Studies suggest that aging and certain neurological or neuropsychiatric diseases affect brain connectivity, such as Alzheimer’s disease (AD) and mild cognitive impairment (MCI). The general objective of this work is to investigate the evolution of the brain connectivity of individuals with healthy aging who convert to MCI and individuals with MCI who convert to AD, using rs-fMRI and analysis based on graph theory (GT). The processing was implemented in SPM12-MATLAB, and the analysis was performed in the CONN Toolbox. The GT metrics chosen to describe the main topological characteristics of the networks were: characteristic path length, global efficiency, local efficiency, clustering coefficient, and degree. Two main findings emerged from this study. When using GT metrics and analyzing healthy subjects converting to MCI, it was possible to observe a decrease in all GT metrics. Second, changes in GT metrics indicated a rupture in the functional connectivity when the cognitive decline occurs from healthy aging to MCI and from MCI to AD.

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Metadaten
Titel
Resting-State Brain in Cognitive Decline: Analysis of Brain Network Architecture Using Graph Theory
verfasst von
C. M. Maulaz
D. B. A. Mantovani
A. M. Marques da Silva
Copyright-Jahr
2022
Buch
XXVII Brazilian Congress on Biomedical Engineering

Print ISBN: 978-3-030-70600-5

Electronic ISBN: 978-3-030-70601-2

Copyright-Jahr: 2022

DOI
https://doi.org/10.1007/978-3-030-70601-2_279

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