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Test–Retest Reliability of Synchrony and Metastability in Resting State fMRI
In recent years, interest has been growing in dynamic characteristic of brain signals from resting-state functional magnetic resonance imaging (rs-fMRI). Synchrony and metastability, as neurodynamic indexes, are considered as one of methods for analyzing dynamic characteristics. Although much resear...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8773904/ https://www.ncbi.nlm.nih.gov/pubmed/35053813 http://dx.doi.org/10.3390/brainsci12010066 |
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author | Yang, Lan Wei, Jing Li, Ying Wang, Bin Guo, Hao Yang, Yanli Xiang, Jie |
author_facet | Yang, Lan Wei, Jing Li, Ying Wang, Bin Guo, Hao Yang, Yanli Xiang, Jie |
author_sort | Yang, Lan |
collection | PubMed |
description | In recent years, interest has been growing in dynamic characteristic of brain signals from resting-state functional magnetic resonance imaging (rs-fMRI). Synchrony and metastability, as neurodynamic indexes, are considered as one of methods for analyzing dynamic characteristics. Although much research has studied the analysis of neurodynamic indices, few have investigated its reliability. In this paper, the datasets from the Human Connectome Project have been used to explore the test–retest reliabilities of synchrony and metastability from multiple angles through intra-class correlation (ICC). The results showed that both of these indexes had fair test–retest reliability, but they are strongly affected by the field strength, the spatial resolution, and scanning interval, less affected by the temporal resolution. Denoising processing can help improve their ICC values. In addition, the reliability of neurodynamic indexes was affected by the node definition strategy, but these effects were not apparent. In particular, by comparing the test–retest reliability of different resting-state networks, we found that synchrony of different networks was basically stable, but the metastability varied considerably. Among these, DMN and LIM had a relatively higher test–retest reliability of metastability than other networks. This paper provides a methodological reference for exploring the brain dynamic neural activity by using synchrony and metastability in fMRI signals. |
format | Online Article Text |
id | pubmed-8773904 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87739042022-01-21 Test–Retest Reliability of Synchrony and Metastability in Resting State fMRI Yang, Lan Wei, Jing Li, Ying Wang, Bin Guo, Hao Yang, Yanli Xiang, Jie Brain Sci Article In recent years, interest has been growing in dynamic characteristic of brain signals from resting-state functional magnetic resonance imaging (rs-fMRI). Synchrony and metastability, as neurodynamic indexes, are considered as one of methods for analyzing dynamic characteristics. Although much research has studied the analysis of neurodynamic indices, few have investigated its reliability. In this paper, the datasets from the Human Connectome Project have been used to explore the test–retest reliabilities of synchrony and metastability from multiple angles through intra-class correlation (ICC). The results showed that both of these indexes had fair test–retest reliability, but they are strongly affected by the field strength, the spatial resolution, and scanning interval, less affected by the temporal resolution. Denoising processing can help improve their ICC values. In addition, the reliability of neurodynamic indexes was affected by the node definition strategy, but these effects were not apparent. In particular, by comparing the test–retest reliability of different resting-state networks, we found that synchrony of different networks was basically stable, but the metastability varied considerably. Among these, DMN and LIM had a relatively higher test–retest reliability of metastability than other networks. This paper provides a methodological reference for exploring the brain dynamic neural activity by using synchrony and metastability in fMRI signals. MDPI 2021-12-31 /pmc/articles/PMC8773904/ /pubmed/35053813 http://dx.doi.org/10.3390/brainsci12010066 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Yang, Lan Wei, Jing Li, Ying Wang, Bin Guo, Hao Yang, Yanli Xiang, Jie Test–Retest Reliability of Synchrony and Metastability in Resting State fMRI |
title | Test–Retest Reliability of Synchrony and Metastability in Resting State fMRI |
title_full | Test–Retest Reliability of Synchrony and Metastability in Resting State fMRI |
title_fullStr | Test–Retest Reliability of Synchrony and Metastability in Resting State fMRI |
title_full_unstemmed | Test–Retest Reliability of Synchrony and Metastability in Resting State fMRI |
title_short | Test–Retest Reliability of Synchrony and Metastability in Resting State fMRI |
title_sort | test–retest reliability of synchrony and metastability in resting state fmri |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8773904/ https://www.ncbi.nlm.nih.gov/pubmed/35053813 http://dx.doi.org/10.3390/brainsci12010066 |
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