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Resting state functional connectivity provides mechanistic predictions of future changes in sedentary behavior
Sedentary behaviors are increasing at the cost of millions of dollars spent in health care and productivity losses due to physical inactivity-related deaths worldwide. Understanding the mechanistic predictors of sedentary behaviors will improve future intervention development and precision medicine...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8766514/ https://www.ncbi.nlm.nih.gov/pubmed/35042916 http://dx.doi.org/10.1038/s41598-021-04738-y |
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author | Morris, Timothy P. Kucyi, Aaron Anteraper, Sheeba Arnold Geddes, Maiya Rachel Nieto-Castañon, Alfonso Burzynska, Agnieszka Gothe, Neha P. Fanning, Jason Salerno, Elizabeth A. Whitfield-Gabrieli, Susan Hillman, Charles H. McAuley, Edward Kramer, Arthur F. |
author_facet | Morris, Timothy P. Kucyi, Aaron Anteraper, Sheeba Arnold Geddes, Maiya Rachel Nieto-Castañon, Alfonso Burzynska, Agnieszka Gothe, Neha P. Fanning, Jason Salerno, Elizabeth A. Whitfield-Gabrieli, Susan Hillman, Charles H. McAuley, Edward Kramer, Arthur F. |
author_sort | Morris, Timothy P. |
collection | PubMed |
description | Sedentary behaviors are increasing at the cost of millions of dollars spent in health care and productivity losses due to physical inactivity-related deaths worldwide. Understanding the mechanistic predictors of sedentary behaviors will improve future intervention development and precision medicine approaches. It has been posited that humans have an innate attraction towards effort minimization and that inhibitory control is required to overcome this prepotent disposition. Consequently, we hypothesized that individual differences in the functional connectivity of brain regions implicated in inhibitory control and physical effort decision making at the beginning of an exercise intervention in older adults would predict the change in time spent sedentary over the course of that intervention. In 143 healthy, low-active older adults participating in a 6-month aerobic exercise intervention (with three conditions: walking, dance, stretching), we aimed to use baseline neuroimaging (resting state functional connectivity of two a priori defined seed regions), and baseline accelerometer measures of time spent sedentary to predict future pre-post changes in objectively measured time spent sedentary in daily life over the 6-month intervention. Our results demonstrated that functional connectivity between (1) the anterior cingulate cortex and the supplementary motor area and (2) the right anterior insula and the left temporoparietal/temporooccipital junction, predicted changes in time spent sedentary in the walking group. Functional connectivity of these brain regions did not predict changes in time spent sedentary in the dance nor stretch and tone conditions, but baseline time spent sedentary was predictive in these conditions. Our results add important knowledge toward understanding mechanistic associations underlying complex out-of-session sedentary behaviors within a walking intervention setting in older adults. |
format | Online Article Text |
id | pubmed-8766514 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-87665142022-01-20 Resting state functional connectivity provides mechanistic predictions of future changes in sedentary behavior Morris, Timothy P. Kucyi, Aaron Anteraper, Sheeba Arnold Geddes, Maiya Rachel Nieto-Castañon, Alfonso Burzynska, Agnieszka Gothe, Neha P. Fanning, Jason Salerno, Elizabeth A. Whitfield-Gabrieli, Susan Hillman, Charles H. McAuley, Edward Kramer, Arthur F. Sci Rep Article Sedentary behaviors are increasing at the cost of millions of dollars spent in health care and productivity losses due to physical inactivity-related deaths worldwide. Understanding the mechanistic predictors of sedentary behaviors will improve future intervention development and precision medicine approaches. It has been posited that humans have an innate attraction towards effort minimization and that inhibitory control is required to overcome this prepotent disposition. Consequently, we hypothesized that individual differences in the functional connectivity of brain regions implicated in inhibitory control and physical effort decision making at the beginning of an exercise intervention in older adults would predict the change in time spent sedentary over the course of that intervention. In 143 healthy, low-active older adults participating in a 6-month aerobic exercise intervention (with three conditions: walking, dance, stretching), we aimed to use baseline neuroimaging (resting state functional connectivity of two a priori defined seed regions), and baseline accelerometer measures of time spent sedentary to predict future pre-post changes in objectively measured time spent sedentary in daily life over the 6-month intervention. Our results demonstrated that functional connectivity between (1) the anterior cingulate cortex and the supplementary motor area and (2) the right anterior insula and the left temporoparietal/temporooccipital junction, predicted changes in time spent sedentary in the walking group. Functional connectivity of these brain regions did not predict changes in time spent sedentary in the dance nor stretch and tone conditions, but baseline time spent sedentary was predictive in these conditions. Our results add important knowledge toward understanding mechanistic associations underlying complex out-of-session sedentary behaviors within a walking intervention setting in older adults. Nature Publishing Group UK 2022-01-18 /pmc/articles/PMC8766514/ /pubmed/35042916 http://dx.doi.org/10.1038/s41598-021-04738-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Morris, Timothy P. Kucyi, Aaron Anteraper, Sheeba Arnold Geddes, Maiya Rachel Nieto-Castañon, Alfonso Burzynska, Agnieszka Gothe, Neha P. Fanning, Jason Salerno, Elizabeth A. Whitfield-Gabrieli, Susan Hillman, Charles H. McAuley, Edward Kramer, Arthur F. Resting state functional connectivity provides mechanistic predictions of future changes in sedentary behavior |
title | Resting state functional connectivity provides mechanistic predictions of future changes in sedentary behavior |
title_full | Resting state functional connectivity provides mechanistic predictions of future changes in sedentary behavior |
title_fullStr | Resting state functional connectivity provides mechanistic predictions of future changes in sedentary behavior |
title_full_unstemmed | Resting state functional connectivity provides mechanistic predictions of future changes in sedentary behavior |
title_short | Resting state functional connectivity provides mechanistic predictions of future changes in sedentary behavior |
title_sort | resting state functional connectivity provides mechanistic predictions of future changes in sedentary behavior |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8766514/ https://www.ncbi.nlm.nih.gov/pubmed/35042916 http://dx.doi.org/10.1038/s41598-021-04738-y |
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