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Spatial variability of low frequency brain signal differentiates brain states
Temporal variability of the neural signal has been demonstrated to be closely related to healthy brain function. Meanwhile, the evolving brain functions are supported by dynamic relationships among brain regions. We hypothesized that the spatial variability of brain signal might provide important in...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660497/ https://www.ncbi.nlm.nih.gov/pubmed/33180843 http://dx.doi.org/10.1371/journal.pone.0242330 |
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author | Wang, Yifeng Ao, Yujia Yang, Qi Liu, Yang Ouyang, Yujie Jing, Xiujuan Pang, Yajing Cui, Qian Chen, Huafu |
author_facet | Wang, Yifeng Ao, Yujia Yang, Qi Liu, Yang Ouyang, Yujie Jing, Xiujuan Pang, Yajing Cui, Qian Chen, Huafu |
author_sort | Wang, Yifeng |
collection | PubMed |
description | Temporal variability of the neural signal has been demonstrated to be closely related to healthy brain function. Meanwhile, the evolving brain functions are supported by dynamic relationships among brain regions. We hypothesized that the spatial variability of brain signal might provide important information about brain function. Here we used the spatial sample entropy (SSE) to investigate the spatial variability of neuroimaging signal during a steady-state presented face detection task. Lower SSE was found during task state than during resting state, associating with more repetitive functional interactions between brain regions. The standard deviation (SD) of SSE during the task was negatively related to the SD of reaction time, suggesting that the spatial pattern of neural activity is reorganized according to particular cognitive function and supporting the previous theory that greater variability is associated with better task performance. These results were replicated with reordered data, implying the reliability of SSE in measuring the spatial organization of neural activity. Overall, the present study extends the research scope of brain signal variability from the temporal dimension to the spatial dimension, improving our understanding of the spatiotemporal characteristics of brain activities and the theory of brain signal variability. |
format | Online Article Text |
id | pubmed-7660497 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-76604972020-11-18 Spatial variability of low frequency brain signal differentiates brain states Wang, Yifeng Ao, Yujia Yang, Qi Liu, Yang Ouyang, Yujie Jing, Xiujuan Pang, Yajing Cui, Qian Chen, Huafu PLoS One Research Article Temporal variability of the neural signal has been demonstrated to be closely related to healthy brain function. Meanwhile, the evolving brain functions are supported by dynamic relationships among brain regions. We hypothesized that the spatial variability of brain signal might provide important information about brain function. Here we used the spatial sample entropy (SSE) to investigate the spatial variability of neuroimaging signal during a steady-state presented face detection task. Lower SSE was found during task state than during resting state, associating with more repetitive functional interactions between brain regions. The standard deviation (SD) of SSE during the task was negatively related to the SD of reaction time, suggesting that the spatial pattern of neural activity is reorganized according to particular cognitive function and supporting the previous theory that greater variability is associated with better task performance. These results were replicated with reordered data, implying the reliability of SSE in measuring the spatial organization of neural activity. Overall, the present study extends the research scope of brain signal variability from the temporal dimension to the spatial dimension, improving our understanding of the spatiotemporal characteristics of brain activities and the theory of brain signal variability. Public Library of Science 2020-11-12 /pmc/articles/PMC7660497/ /pubmed/33180843 http://dx.doi.org/10.1371/journal.pone.0242330 Text en © 2020 Wang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Wang, Yifeng Ao, Yujia Yang, Qi Liu, Yang Ouyang, Yujie Jing, Xiujuan Pang, Yajing Cui, Qian Chen, Huafu Spatial variability of low frequency brain signal differentiates brain states |
title | Spatial variability of low frequency brain signal differentiates brain states |
title_full | Spatial variability of low frequency brain signal differentiates brain states |
title_fullStr | Spatial variability of low frequency brain signal differentiates brain states |
title_full_unstemmed | Spatial variability of low frequency brain signal differentiates brain states |
title_short | Spatial variability of low frequency brain signal differentiates brain states |
title_sort | spatial variability of low frequency brain signal differentiates brain states |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660497/ https://www.ncbi.nlm.nih.gov/pubmed/33180843 http://dx.doi.org/10.1371/journal.pone.0242330 |
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