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. 2009 Feb;30(2):625-37.
doi: 10.1002/hbm.20531.

Functional connectivity of default mode network components: correlation, anticorrelation, and causality

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Functional connectivity of default mode network components: correlation, anticorrelation, and causality

Lucina Q Uddin et al. Hum Brain Mapp. 2009 Feb.

Abstract

The default mode network (DMN), based in ventromedial prefrontal cortex (vmPFC) and posterior cingulate cortex (PCC), exhibits higher metabolic activity at rest than during performance of externally oriented cognitive tasks. Recent studies have suggested that competitive relationships between the DMN and various task-positive networks involved in task performance are intrinsically represented in the brain in the form of strong negative correlations (anticorrelations) between spontaneous fluctuations in these networks. Most neuroimaging studies characterize the DMN as a homogenous network, thus few have examined the differential contributions of DMN components to such competitive relationships. Here, we examined functional differentiation within the DMN, with an emphasis on understanding competitive relationships between this and other networks. We used a seed correlation approach on resting-state data to assess differences in functional connectivity between these two regions and their anticorrelated networks. While the positively correlated networks for the vmPFC and PCC seeds largely overlapped, the anticorrelated networks for each showed striking differences. Activity in vmPFC negatively predicted activity in parietal visual spatial and temporal attention networks, whereas activity in PCC negatively predicted activity in prefrontal-based motor control circuits. Granger causality analyses suggest that vmPFC and PCC exert greater influence on their anticorrelated networks than the other way around, suggesting that these two default mode nodes may directly modulate activity in task-positive networks. Thus, the two major nodes comprising the DMN are differentiated with respect to the specific brain systems with which they interact, suggesting greater heterogeneity within this network than is commonly appreciated.

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Figures

Figure 1
Figure 1
(a) Diagram of data processing steps. (b) Locations of seeds used for correlation analysis (vmPFC Talairach coordinates = 2, 54, −3; PCC Talairach coordinates = −2, −51, 27). [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]
Figure 2
Figure 2
Positive and negative correlations with each seeded region. (a) vmPFC (orange) and its anticorrelated network (blue). (b) PCC (orange) and its anticorrelated network (blue). [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]
Figure 3
Figure 3
Direct comparisons between positive and negative networks for each seed. (a) vmPFC (red) and PCC (pink) positively correlated networks. (b) vmPFC (blue) and PCC (green) negatively correlated networks. [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]
Figure 4
Figure 4
Correlation between DMN components and antinetworks. [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]
Figure 5
Figure 5
Granger causality results. Significant relationships between DMN components and antinetworks. The percentage values indicate proportion of subjects showing significant relationship at P < 0.1. As indicated by the binomial test, a significant relationship at that threshold in 30% or more subjects is significant at P < 0.01.

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