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The spatial structure of resting state connectivity stability on the scale of minutes
Resting state functional MRI (rsfMRI) connectivity patterns are not temporally stable, but fluctuate in time at scales shorter than most common rest scan durations (5–10 min). Consequently, connectivity patterns for two different portions of the same scan can differ drastically. To better characteri...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4052097/ https://www.ncbi.nlm.nih.gov/pubmed/24999315 http://dx.doi.org/10.3389/fnins.2014.00138 |
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author | Gonzalez-Castillo, Javier Handwerker, Daniel A. Robinson, Meghan E. Hoy, Colin Weir Buchanan, Laura C. Saad, Ziad S. Bandettini, Peter A. |
author_facet | Gonzalez-Castillo, Javier Handwerker, Daniel A. Robinson, Meghan E. Hoy, Colin Weir Buchanan, Laura C. Saad, Ziad S. Bandettini, Peter A. |
author_sort | Gonzalez-Castillo, Javier |
collection | PubMed |
description | Resting state functional MRI (rsfMRI) connectivity patterns are not temporally stable, but fluctuate in time at scales shorter than most common rest scan durations (5–10 min). Consequently, connectivity patterns for two different portions of the same scan can differ drastically. To better characterize this temporal variability and understand how it is spatially distributed across the brain, we scanned subjects continuously for 60 min, at a temporal resolution of 1 s, while they rested inside the scanner. We then computed connectivity matrices between functionally-defined regions of interest for non-overlapping 1 min windows, and classified connections according to their strength, polarity, and variability. We found that the most stable connections correspond primarily to inter-hemispheric connections between left/right homologous ROIs. However, only 32% of all within-network connections were classified as most stable. This shows that resting state networks have some long-term stability, but confirms the flexible configuration of these networks, particularly those related to higher order cognitive functions. The most variable connections correspond primarily to inter-hemispheric, across-network connections between non-homologous regions in occipital and frontal cortex. Finally we found a series of connections with negative average correlation, but further analyses revealed that such average negative correlations may be related to the removal of CSF signals during pre-processing. Using the same dataset, we also evaluated how similarity of within-subject whole-brain connectivity matrices changes as a function of window duration (used here as a proxy for scan duration). Our results suggest scanning for a minimum of 10 min to optimize within-subject reproducibility of connectivity patterns across the entire brain, rather than a few predefined networks. |
format | Online Article Text |
id | pubmed-4052097 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-40520972014-07-04 The spatial structure of resting state connectivity stability on the scale of minutes Gonzalez-Castillo, Javier Handwerker, Daniel A. Robinson, Meghan E. Hoy, Colin Weir Buchanan, Laura C. Saad, Ziad S. Bandettini, Peter A. Front Neurosci Neuroscience Resting state functional MRI (rsfMRI) connectivity patterns are not temporally stable, but fluctuate in time at scales shorter than most common rest scan durations (5–10 min). Consequently, connectivity patterns for two different portions of the same scan can differ drastically. To better characterize this temporal variability and understand how it is spatially distributed across the brain, we scanned subjects continuously for 60 min, at a temporal resolution of 1 s, while they rested inside the scanner. We then computed connectivity matrices between functionally-defined regions of interest for non-overlapping 1 min windows, and classified connections according to their strength, polarity, and variability. We found that the most stable connections correspond primarily to inter-hemispheric connections between left/right homologous ROIs. However, only 32% of all within-network connections were classified as most stable. This shows that resting state networks have some long-term stability, but confirms the flexible configuration of these networks, particularly those related to higher order cognitive functions. The most variable connections correspond primarily to inter-hemispheric, across-network connections between non-homologous regions in occipital and frontal cortex. Finally we found a series of connections with negative average correlation, but further analyses revealed that such average negative correlations may be related to the removal of CSF signals during pre-processing. Using the same dataset, we also evaluated how similarity of within-subject whole-brain connectivity matrices changes as a function of window duration (used here as a proxy for scan duration). Our results suggest scanning for a minimum of 10 min to optimize within-subject reproducibility of connectivity patterns across the entire brain, rather than a few predefined networks. Frontiers Media S.A. 2014-06-11 /pmc/articles/PMC4052097/ /pubmed/24999315 http://dx.doi.org/10.3389/fnins.2014.00138 Text en Copyright © 2014 Gonzalez-Castillo, Handwerker, Robinson, Hoy, Buchanan, Saad and Bandettini. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Gonzalez-Castillo, Javier Handwerker, Daniel A. Robinson, Meghan E. Hoy, Colin Weir Buchanan, Laura C. Saad, Ziad S. Bandettini, Peter A. The spatial structure of resting state connectivity stability on the scale of minutes |
title | The spatial structure of resting state connectivity stability on the scale of minutes |
title_full | The spatial structure of resting state connectivity stability on the scale of minutes |
title_fullStr | The spatial structure of resting state connectivity stability on the scale of minutes |
title_full_unstemmed | The spatial structure of resting state connectivity stability on the scale of minutes |
title_short | The spatial structure of resting state connectivity stability on the scale of minutes |
title_sort | spatial structure of resting state connectivity stability on the scale of minutes |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4052097/ https://www.ncbi.nlm.nih.gov/pubmed/24999315 http://dx.doi.org/10.3389/fnins.2014.00138 |
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