Literature DB >> 28827337

Dynamic connectivity modulates local activity in the core regions of the default-mode network.

Wei Tang1, Hesheng Liu1, Linda Douw2,3, Mark A Kramer4, Uri T Eden4, Matti S Hämäläinen2, Steven M Stufflebeam2.   

Abstract

Segregation and integration are distinctive features of large-scale brain activity. Although neuroimaging studies have been unraveling their neural correlates, how integration takes place over segregated modules remains elusive. Central to this problem is the mechanism by which a brain region adjusts its activity according to the influence it receives from other regions. In this study, we explore how dynamic connectivity between two regions affects the neural activity within a participating region. Combining functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) in the same group of subjects, we analyzed resting-state data from the core of the default-mode network. We observed directed influence from the posterior cingulate cortex (PCC) to the anterior cingulate cortex (ACC) in the 10-Hz range. This time-varying influence was associated with the power alteration in the ACC: strong influence corresponded with a decrease of power around 13-16 Hz and an increase of power in the lower (1-7 Hz) and higher (30-55 Hz) ends of the spectrum. We also found that the amplitude of the 30- to 55-Hz activity was coupled to the phase of the 3- to 4-Hz activity in the ACC. These results characterized the local spectral changes associated with network interactions. The specific spectral information both highlights the functional roles of PCC-ACC connectivity in the resting state and provides insights into the dynamic relationship between local activity and coupling dynamics of a network.

Keywords:  MEG; default-mode network; fMRI; functional connectivity; resting state

Mesh:

Year:  2017        PMID: 28827337      PMCID: PMC5594646          DOI: 10.1073/pnas.1702027114

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


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