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Spatial Smoothing Effect on Group-Level Functional Connectivity during Resting and Task-Based fMRI
Spatial smoothing is a preprocessing step applied to neuroimaging data to enhance data quality by reducing noise and artifacts. However, selecting an appropriate smoothing kernel size can be challenging as it can lead to undesired alterations in final images and functional connectivity networks. How...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10346894/ https://www.ncbi.nlm.nih.gov/pubmed/37447716 http://dx.doi.org/10.3390/s23135866 |
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author | Candemir, Cemre |
author_facet | Candemir, Cemre |
author_sort | Candemir, Cemre |
collection | PubMed |
description | Spatial smoothing is a preprocessing step applied to neuroimaging data to enhance data quality by reducing noise and artifacts. However, selecting an appropriate smoothing kernel size can be challenging as it can lead to undesired alterations in final images and functional connectivity networks. However, there is no sufficient information about the effects of the Gaussian kernel size on group-level results for different cases yet. This study investigates the influence of kernel size on functional connectivity networks and network parameters in whole-brain rs-fMRI and tb-fMRI analyses of healthy adults. The analysis includes {0, 2, 4, 6, 8, 10} mm kernels, commonly used in practical analyses, covering all major brain networks. Graph theoretical measures such as betweenness centrality, global/local efficiency, clustering coefficient, and average path length are examined for each kernel. Additionally, principal component analysis (PCA) and independent component analysis (ICA) parameters, namely kurtosis and skewness, are evaluated for the functional images. The findings demonstrate that kernel size directly affects node connections, resulting in modifications to functional network structures and PCA/ICA parameters. However, network metrics exhibit greater resilience to these changes. |
format | Online Article Text |
id | pubmed-10346894 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-103468942023-07-15 Spatial Smoothing Effect on Group-Level Functional Connectivity during Resting and Task-Based fMRI Candemir, Cemre Sensors (Basel) Article Spatial smoothing is a preprocessing step applied to neuroimaging data to enhance data quality by reducing noise and artifacts. However, selecting an appropriate smoothing kernel size can be challenging as it can lead to undesired alterations in final images and functional connectivity networks. However, there is no sufficient information about the effects of the Gaussian kernel size on group-level results for different cases yet. This study investigates the influence of kernel size on functional connectivity networks and network parameters in whole-brain rs-fMRI and tb-fMRI analyses of healthy adults. The analysis includes {0, 2, 4, 6, 8, 10} mm kernels, commonly used in practical analyses, covering all major brain networks. Graph theoretical measures such as betweenness centrality, global/local efficiency, clustering coefficient, and average path length are examined for each kernel. Additionally, principal component analysis (PCA) and independent component analysis (ICA) parameters, namely kurtosis and skewness, are evaluated for the functional images. The findings demonstrate that kernel size directly affects node connections, resulting in modifications to functional network structures and PCA/ICA parameters. However, network metrics exhibit greater resilience to these changes. MDPI 2023-06-24 /pmc/articles/PMC10346894/ /pubmed/37447716 http://dx.doi.org/10.3390/s23135866 Text en © 2023 by the author. 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 Candemir, Cemre Spatial Smoothing Effect on Group-Level Functional Connectivity during Resting and Task-Based fMRI |
title | Spatial Smoothing Effect on Group-Level Functional Connectivity during Resting and Task-Based fMRI |
title_full | Spatial Smoothing Effect on Group-Level Functional Connectivity during Resting and Task-Based fMRI |
title_fullStr | Spatial Smoothing Effect on Group-Level Functional Connectivity during Resting and Task-Based fMRI |
title_full_unstemmed | Spatial Smoothing Effect on Group-Level Functional Connectivity during Resting and Task-Based fMRI |
title_short | Spatial Smoothing Effect on Group-Level Functional Connectivity during Resting and Task-Based fMRI |
title_sort | spatial smoothing effect on group-level functional connectivity during resting and task-based fmri |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10346894/ https://www.ncbi.nlm.nih.gov/pubmed/37447716 http://dx.doi.org/10.3390/s23135866 |
work_keys_str_mv | AT candemircemre spatialsmoothingeffectongrouplevelfunctionalconnectivityduringrestingandtaskbasedfmri |