Literature DB >> 35060063

Frequency-Resolved Connectome Hubs and Their Test-Retest Reliability in the Resting Human Brain.

Lei Wang1,2,3, Xiaodan Chen4,5,6, Yuehua Xu1,2,3, Miao Cao7,8, Xuhong Liao9, Yong He10,11,12,13.   

Abstract

Functional hubs with disproportionately extensive connectivities play a crucial role in global information integration in human brain networks. However, most resting-state functional magnetic resonance imaging (R-fMRI) studies have identified functional hubs by examining spontaneous fluctuations of the blood oxygen level-dependent signal within a typical low-frequency band (e.g., 0.01-0.08 Hz or 0.01-0.1 Hz). Little is known about how the spatial distributions of functional hubs depend on frequency bands of interest. Here, we used repeatedly measured R-fMRI data from 53 healthy young adults and a degree centrality analysis to identify voxelwise frequency-resolved functional hubs and further examined their test-retest reliability across two sessions. We showed that a wide-range frequency band (0.01-0.24 Hz) accessible with a typical sampling rate (fsample = 0.5 Hz) could be classified into three frequency bands with distinct patterns, namely, low-frequency (LF, 0.01-0.06 Hz), middle-frequency (MF, 0.06-0.16 Hz), and high-frequency (HF, 0.16-0.24 Hz) bands. The functional hubs were mainly located in the medial and lateral frontal and parietal cortices in the LF band, and in the medial prefrontal cortex, superior temporal gyrus, parahippocampal gyrus, amygdala, and several cerebellar regions in the MF and HF bands. These hub regions exhibited fair to good test-retest reliability, regardless of the frequency band. The presence of the three frequency bands was well replicated using an independent R-fMRI dataset from 45 healthy young adults. Our findings demonstrate reliable frequency-resolved functional connectivity hubs in three categories, thus providing insights into the frequency-specific connectome organization in healthy and disordered brains.
© 2022. Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences.

Entities:  

Keywords:  Connectome; Degree centrality; Frequency; Hubs; Test-retest reliability

Mesh:

Year:  2022        PMID: 35060063      PMCID: PMC9106786          DOI: 10.1007/s12264-021-00812-7

Source DB:  PubMed          Journal:  Neurosci Bull        ISSN: 1995-8218            Impact factor:   5.271


  61 in total

1.  Network centrality in the human functional connectome.

Authors:  Xi-Nian Zuo; Ross Ehmke; Maarten Mennes; Davide Imperati; F Xavier Castellanos; Olaf Sporns; Michael P Milham
Journal:  Cereb Cortex       Date:  2011-10-02       Impact factor: 5.357

2.  Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI.

Authors:  Rasmus M Birn; Jason B Diamond; Monica A Smith; Peter A Bandettini
Journal:  Neuroimage       Date:  2006-04-24       Impact factor: 6.556

3.  Development and Emergence of Individual Variability in the Functional Connectivity Architecture of the Preterm Human Brain.

Authors:  Yuehua Xu; Miao Cao; Xuhong Liao; Mingrui Xia; Xindi Wang; Tina Jeon; Minhui Ouyang; Lina Chalak; Nancy Rollins; Hao Huang; Yong He
Journal:  Cereb Cortex       Date:  2019-09-13       Impact factor: 5.357

4.  Identifying the brain's most globally connected regions.

Authors:  Michael W Cole; Sudhir Pathak; Walter Schneider
Journal:  Neuroimage       Date:  2009-11-10       Impact factor: 6.556

5.  Identifying and Mapping Connectivity Patterns of Brain Network Hubs in Alzheimer's Disease.

Authors:  Zhengjia Dai; Chaogan Yan; Kuncheng Li; Zhiqun Wang; Jinhui Wang; Miao Cao; Qixiang Lin; Ni Shu; Mingrui Xia; Yanchao Bi; Yong He
Journal:  Cereb Cortex       Date:  2014-10-19       Impact factor: 5.357

6.  Functional connectivity in the motor cortex of resting human brain using echo-planar MRI.

Authors:  B Biswal; F Z Yetkin; V M Haughton; J S Hyde
Journal:  Magn Reson Med       Date:  1995-10       Impact factor: 4.668

7.  The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?

Authors:  Kevin Murphy; Rasmus M Birn; Daniel A Handwerker; Tyler B Jones; Peter A Bandettini
Journal:  Neuroimage       Date:  2008-10-11       Impact factor: 6.556

8.  Functional connectivity of the human amygdala using resting state fMRI.

Authors:  Amy Krain Roy; Zarrar Shehzad; Daniel S Margulies; A M Clare Kelly; Lucina Q Uddin; Kristin Gotimer; Bharat B Biswal; F Xavier Castellanos; Michael P Milham
Journal:  Neuroimage       Date:  2008-12-09       Impact factor: 6.556

9.  Beyond Noise: Using Temporal ICA to Extract Meaningful Information from High-Frequency fMRI Signal Fluctuations during Rest.

Authors:  Roland N Boubela; Klaudius Kalcher; Wolfgang Huf; Claudia Kronnerwetter; Peter Filzmoser; Ewald Moser
Journal:  Front Hum Neurosci       Date:  2013-05-01       Impact factor: 3.169

10.  Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity.

Authors:  Emily S Finn; Xilin Shen; Dustin Scheinost; Monica D Rosenberg; Jessica Huang; Marvin M Chun; Xenophon Papademetris; R Todd Constable
Journal:  Nat Neurosci       Date:  2015-10-12       Impact factor: 24.884

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