Cargando…

Time-varying spectral power of resting-state fMRI networks reveal cross-frequency dependence in dynamic connectivity

Brain oscillations and synchronicity among brain regions (brain connectivity) have been studied in resting-state (RS) and task-induced settings. RS-connectivity which captures brain functional integration during an unconstrained state is shown to vary with the frequency of oscillations. Indeed, high...

Descripción completa

Detalles Bibliográficos
Autores principales: Yaesoubi, Maziar, Miller, Robyn L., Calhoun, Vince D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5305250/
https://www.ncbi.nlm.nih.gov/pubmed/28192457
http://dx.doi.org/10.1371/journal.pone.0171647
_version_ 1782507018953687040
author Yaesoubi, Maziar
Miller, Robyn L.
Calhoun, Vince D.
author_facet Yaesoubi, Maziar
Miller, Robyn L.
Calhoun, Vince D.
author_sort Yaesoubi, Maziar
collection PubMed
description Brain oscillations and synchronicity among brain regions (brain connectivity) have been studied in resting-state (RS) and task-induced settings. RS-connectivity which captures brain functional integration during an unconstrained state is shown to vary with the frequency of oscillations. Indeed, high temporal resolution modalities have demonstrated both between and cross-frequency connectivity spanning across frequency bands such as theta and gamma. Despite high spatial resolution, functional magnetic resonance imaging (fMRI) suffers from low temporal resolution due to modulation with slow-varying hemodynamic response function (HRF) and also relatively low sampling rate. This limits the range of detectable frequency bands in fMRI and consequently there has been no evidence of cross-frequency dependence in fMRI data. In the present work we uncover recurring patterns of spectral power in network timecourses which provides new insight on the actual nature of frequency variation in fMRI network activations. Moreover, we introduce a new measure of dependence between pairs of rs-fMRI networks which reveals significant cross-frequency dependence between functional brain networks specifically default-mode, cerebellar and visual networks. This is the first strong evidence of cross-frequency dependence between functional networks in fMRI and our subject group analysis based on age and gender supports usefulness of this observation for future clinical applications.
format Online
Article
Text
id pubmed-5305250
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-53052502017-02-28 Time-varying spectral power of resting-state fMRI networks reveal cross-frequency dependence in dynamic connectivity Yaesoubi, Maziar Miller, Robyn L. Calhoun, Vince D. PLoS One Research Article Brain oscillations and synchronicity among brain regions (brain connectivity) have been studied in resting-state (RS) and task-induced settings. RS-connectivity which captures brain functional integration during an unconstrained state is shown to vary with the frequency of oscillations. Indeed, high temporal resolution modalities have demonstrated both between and cross-frequency connectivity spanning across frequency bands such as theta and gamma. Despite high spatial resolution, functional magnetic resonance imaging (fMRI) suffers from low temporal resolution due to modulation with slow-varying hemodynamic response function (HRF) and also relatively low sampling rate. This limits the range of detectable frequency bands in fMRI and consequently there has been no evidence of cross-frequency dependence in fMRI data. In the present work we uncover recurring patterns of spectral power in network timecourses which provides new insight on the actual nature of frequency variation in fMRI network activations. Moreover, we introduce a new measure of dependence between pairs of rs-fMRI networks which reveals significant cross-frequency dependence between functional brain networks specifically default-mode, cerebellar and visual networks. This is the first strong evidence of cross-frequency dependence between functional networks in fMRI and our subject group analysis based on age and gender supports usefulness of this observation for future clinical applications. Public Library of Science 2017-02-13 /pmc/articles/PMC5305250/ /pubmed/28192457 http://dx.doi.org/10.1371/journal.pone.0171647 Text en © 2017 Yaesoubi 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
Yaesoubi, Maziar
Miller, Robyn L.
Calhoun, Vince D.
Time-varying spectral power of resting-state fMRI networks reveal cross-frequency dependence in dynamic connectivity
title Time-varying spectral power of resting-state fMRI networks reveal cross-frequency dependence in dynamic connectivity
title_full Time-varying spectral power of resting-state fMRI networks reveal cross-frequency dependence in dynamic connectivity
title_fullStr Time-varying spectral power of resting-state fMRI networks reveal cross-frequency dependence in dynamic connectivity
title_full_unstemmed Time-varying spectral power of resting-state fMRI networks reveal cross-frequency dependence in dynamic connectivity
title_short Time-varying spectral power of resting-state fMRI networks reveal cross-frequency dependence in dynamic connectivity
title_sort time-varying spectral power of resting-state fmri networks reveal cross-frequency dependence in dynamic connectivity
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5305250/
https://www.ncbi.nlm.nih.gov/pubmed/28192457
http://dx.doi.org/10.1371/journal.pone.0171647
work_keys_str_mv AT yaesoubimaziar timevaryingspectralpowerofrestingstatefmrinetworksrevealcrossfrequencydependenceindynamicconnectivity
AT millerrobynl timevaryingspectralpowerofrestingstatefmrinetworksrevealcrossfrequencydependenceindynamicconnectivity
AT calhounvinced timevaryingspectralpowerofrestingstatefmrinetworksrevealcrossfrequencydependenceindynamicconnectivity