4.6 Article

Modulation of Brain Resting-State Networks by Sad Mood Induction

Journal

PLOS ONE
Volume 3, Issue 3, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0001794

Keywords

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Funding

  1. National Health and Medical Research Council (NHMRC) of Australia [236175, 400420, 350241]
  2. Ian Potter Foundation
  3. Clive and Vera Ramaciotti foundations [RA44/07]
  4. Spanish Ministry of Education [AP2006-02869]

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Background: There is growing interest in the nature of slow variations of the blood oxygen level-dependent (BOLD) signal observed in functional MRI resting-state studies. In humans, these slow BOLD variations are thought to reflect an underlying or intrinsic form of brain functional connectivity in discrete neuroanatomical systems. While these 'resting-state networks' may be relatively enduring phenomena, other evidence suggest that dynamic changes in their functional connectivity may also emerge depending on the brain state of subjects during scanning. Methodology/Principal Findings: In this study, we examined healthy subjects (n = 24) with a mood induction paradigm during two continuous fMRI recordings to assess the effects of a change in self-generated mood state (neutral to sad) on the functional connectivity of these resting-state networks (n = 24). Using independent component analysis, we identified five networks that were common to both experimental states, each showing dominant signal fluctuations in the very low frequency domain (similar to 0.04 Hz). Between the two states, we observed apparent increases and decreases in the overall functional connectivity of these networks. Primary findings included increased connectivity strength of a paralimbic network involving the dorsal anterior cingulate and anterior insula cortices with subjects' increasing sadness and decreased functional connectivity of the 'default mode network'. Conclusions/Significance: These findings support recent studies that suggest the functional connectivity of certain resting-state networks may, in part, reflect a dynamic image of the current brain state. In our study, this was linked to changes in subjective mood.

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