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Exploring Dynamic Brain Functional Networks Using Continuous “State-Related” Functional MRI
We applied a “temporal decomposition” method, which decomposed a single brain functional network into several “modes”; each of them dominated a short temporal period, on a continuous, “state-” related, “finger-force feedback” functional magnetic resonance imaging experiment. With the hypothesis that...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4564637/ https://www.ncbi.nlm.nih.gov/pubmed/26413546 http://dx.doi.org/10.1155/2015/824710 |
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author | Li, Xun Zang, Yu-Feng Zhang, Han |
author_facet | Li, Xun Zang, Yu-Feng Zhang, Han |
author_sort | Li, Xun |
collection | PubMed |
description | We applied a “temporal decomposition” method, which decomposed a single brain functional network into several “modes”; each of them dominated a short temporal period, on a continuous, “state-” related, “finger-force feedback” functional magnetic resonance imaging experiment. With the hypothesis that attention and internal/external information processing interaction could be manipulated by different (real and sham) feedback conditions, we investigated functional network dynamics of the “default mode,” “executive control,” and sensorimotor networks. They were decomposed into several modes. During real feedback, the occurrence of “default mode-executive control competition-related” mode was higher than that during sham feedback (P = 0.0003); the “default mode-visual facilitation-related” mode more frequently appeared during sham than real feedback (P = 0.0004). However, the dynamics of the sensorimotor network did not change significantly between two conditions (P > 0.05). Our results indicated that the visual-guided motor feedback involves higher cognitive functional networks rather than primary motor network. The dynamics monitoring of inner and outside environment and multisensory integration could be the mechanisms. This study is an extension of our previous region-specific and static-styled study of our brain functional architecture. |
format | Online Article Text |
id | pubmed-4564637 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-45646372015-09-27 Exploring Dynamic Brain Functional Networks Using Continuous “State-Related” Functional MRI Li, Xun Zang, Yu-Feng Zhang, Han Biomed Res Int Research Article We applied a “temporal decomposition” method, which decomposed a single brain functional network into several “modes”; each of them dominated a short temporal period, on a continuous, “state-” related, “finger-force feedback” functional magnetic resonance imaging experiment. With the hypothesis that attention and internal/external information processing interaction could be manipulated by different (real and sham) feedback conditions, we investigated functional network dynamics of the “default mode,” “executive control,” and sensorimotor networks. They were decomposed into several modes. During real feedback, the occurrence of “default mode-executive control competition-related” mode was higher than that during sham feedback (P = 0.0003); the “default mode-visual facilitation-related” mode more frequently appeared during sham than real feedback (P = 0.0004). However, the dynamics of the sensorimotor network did not change significantly between two conditions (P > 0.05). Our results indicated that the visual-guided motor feedback involves higher cognitive functional networks rather than primary motor network. The dynamics monitoring of inner and outside environment and multisensory integration could be the mechanisms. This study is an extension of our previous region-specific and static-styled study of our brain functional architecture. Hindawi Publishing Corporation 2015 2015-08-27 /pmc/articles/PMC4564637/ /pubmed/26413546 http://dx.doi.org/10.1155/2015/824710 Text en Copyright © 2015 Xun Li et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Li, Xun Zang, Yu-Feng Zhang, Han Exploring Dynamic Brain Functional Networks Using Continuous “State-Related” Functional MRI |
title | Exploring Dynamic Brain Functional Networks Using Continuous “State-Related” Functional MRI |
title_full | Exploring Dynamic Brain Functional Networks Using Continuous “State-Related” Functional MRI |
title_fullStr | Exploring Dynamic Brain Functional Networks Using Continuous “State-Related” Functional MRI |
title_full_unstemmed | Exploring Dynamic Brain Functional Networks Using Continuous “State-Related” Functional MRI |
title_short | Exploring Dynamic Brain Functional Networks Using Continuous “State-Related” Functional MRI |
title_sort | exploring dynamic brain functional networks using continuous “state-related” functional mri |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4564637/ https://www.ncbi.nlm.nih.gov/pubmed/26413546 http://dx.doi.org/10.1155/2015/824710 |
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