Literature DB >> 25765256

Influence of epoch length on measurement of dynamic functional connectivity in wakefulness and behavioural validation in sleep.

Rebecca S Wilson1, Stephen D Mayhew1, David T Rollings2, Aimee Goldstone1, Izabela Przezdzik1, Theodoros N Arvanitis3, Andrew P Bagshaw4.   

Abstract

Conventional functional connectivity (FC) analysis of fMRI data derives a single measurement from the entire scan, generally several minutes in duration, which neglects the brain's dynamic behaviour and potentially loses important temporal information. Short-interval dynamic FC is an attractive proposition if methodological issues can be resolved and the approach validated. This was addressed in two ways; firstly we assessed FC of the posterior cingulate cortex (PCC) node of the default mode network (DMN) using differing temporal intervals (8s to 5min) in the waking-resting state. We found that 30-second intervals and longer produce spatially similar correlation topography compared to 15-minute static FC measurements, while providing increased temporal information about changes in FC that were consistent across interval lengths. Secondly, we used NREM sleep as a behavioural validation for the use of 30-second temporal intervals due to the known fMRI FC changes with sleep stage that have been observed in previous studies using intervals of several minutes. We found significant decreases in DMN FC with sleep depth which were most pronounced during stage N2 and N3. Additionally, both the proportion of time with strong PCC-DMN connectivity and the variability in dynamic FC decreased with sleep. We therefore show that dynamic FC with epochs as short as tens of seconds is a viable method for characterising intrinsic brain activity.
Copyright © 2015 Elsevier Inc. All rights reserved.

Keywords:  Dynamic functional connectivity; NREM sleep; Seed-based analysis

Mesh:

Year:  2015        PMID: 25765256     DOI: 10.1016/j.neuroimage.2015.02.061

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  23 in total

Review 1.  Neural Correlates of Unconsciousness in Large-Scale Brain Networks.

Authors:  George A Mashour; Anthony G Hudetz
Journal:  Trends Neurosci       Date:  2018-02-03       Impact factor: 13.837

2.  Instability of brain connectivity during nonrapid eye movement sleep reflects altered properties of information integration.

Authors:  Yi-Chia Kung; Chia-Wei Li; Shuo Chen; Sharon Chia-Ju Chen; Chun-Yi Z Lo; Timothy J Lane; Bharat Biswal; Changwei W Wu; Ching-Po Lin
Journal:  Hum Brain Mapp       Date:  2019-04-02       Impact factor: 5.038

3.  Sliding window correlation analysis: Modulating window shape for dynamic brain connectivity in resting state.

Authors:  Fatemeh Mokhtari; Milad I Akhlaghi; Sean L Simpson; Guorong Wu; Paul J Laurienti
Journal:  Neuroimage       Date:  2019-02-02       Impact factor: 6.556

4.  Evaluation of sliding window correlation performance for characterizing dynamic functional connectivity and brain states.

Authors:  Sadia Shakil; Chin-Hui Lee; Shella Dawn Keilholz
Journal:  Neuroimage       Date:  2016-03-04       Impact factor: 6.556

Review 5.  Neural and metabolic basis of dynamic resting state fMRI.

Authors:  Garth J Thompson
Journal:  Neuroimage       Date:  2017-09-09       Impact factor: 6.556

6.  All-night functional magnetic resonance imaging sleep studies.

Authors:  Thomas M Moehlman; Jacco A de Zwart; Miranda G Chappel-Farley; Xiao Liu; Irene B McClain; Catie Chang; Hendrik Mandelkow; Pinar S Özbay; Nicholas L Johnson; Rebecca E Bieber; Katharine A Fernandez; Kelly A King; Christopher K Zalewski; Carmen C Brewer; Peter van Gelderen; Jeff H Duyn; Dante Picchioni
Journal:  J Neurosci Methods       Date:  2018-09-20       Impact factor: 2.390

Review 7.  Integrating sleep, neuroimaging, and computational approaches for precision psychiatry.

Authors:  Andrea N Goldstein-Piekarski; Bailey Holt-Gosselin; Kathleen O'Hora; Leanne M Williams
Journal:  Neuropsychopharmacology       Date:  2019-08-19       Impact factor: 7.853

8.  Dimensionality reduction impedes the extraction of dynamic functional connectivity states from fMRI recordings of resting wakefulness.

Authors:  MohammadMehdi Kafashan; Ben Julian A Palanca; ShiNung Ching
Journal:  J Neurosci Methods       Date:  2017-09-22       Impact factor: 2.390

9.  An average sliding window correlation method for dynamic functional connectivity.

Authors:  Victor M Vergara; Anees Abrol; Vince D Calhoun
Journal:  Hum Brain Mapp       Date:  2019-01-19       Impact factor: 5.038

10.  Dynamic functional network connectivity reveals unique and overlapping profiles of insula subdivisions.

Authors:  Jason S Nomi; Kristafor Farrant; Eswar Damaraju; Srinivas Rachakonda; Vince D Calhoun; Lucina Q Uddin
Journal:  Hum Brain Mapp       Date:  2016-02-16       Impact factor: 5.038

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.