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. 2010 Oct;28(8):1051-7.
doi: 10.1016/j.mri.2010.03.021. Epub 2010 Apr 21.

Functional connectivity between task-positive and task-negative brain areas and its relation to working memory performance

Affiliations

Functional connectivity between task-positive and task-negative brain areas and its relation to working memory performance

Michelle Hampson et al. Magn Reson Imaging. 2010 Oct.

Abstract

Functional brain imaging studies have identified a set of brain areas typically activated during cognitive tasks (task-positive brain areas) and another set of brain areas typically deactivated during cognitive tasks (task-negative brain areas). Negative correlations, or anticorrelations, between task-positive and task-negative brain areas have been reported at rest. Furthermore, the strength of these anticorrelations appears to be related to cognitive function. However, studies examining anticorrelations have typically employed global regression or similar analysis steps that force anticorrelated relationships to exist between brain areas. Therefore the validity of these findings has been questioned. Here we examine anticorrelations between a task-negative region in the medial frontal gyrus/anterior cingulate cortex and dorsolateral prefrontal cortex, a classic task-positive area, using an analysis that does not include global regression. Instead, we control for whole-brain correlations in the group-level analysis. Using this approach, we demonstrate that the strength of the functional connection between the medial frontal cortex and the dorsolateral prefrontal cortex is related to cognitive function and that this relationship is not an artifact of global regression.

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Figures

Figure 1
Figure 1
A map of the regions of interest studied. Regions were identified based on activations and deactivations during the 3-back working memory task at an uncorrected threshold of p<0.005.
Figure 2
Figure 2
Illustration of the method for estimating whole-brain correlation to the seed region, Δij, for a single run i of a single subject j. The histogram of the values in the seed region correlation map (after the Fisher transform has been applied to the r-values to transform them to Gaussian values) is plotted in red. The Gaussian curve which best fits this distribution (to full-width at half-maximum) is computed (shown in blue). The mean of that Gaussian curve is Δij, an estimate of the whole-brain correlation in that run.
Figure 3
Figure 3
Composite map of correlations to the MFC at a threshold of p<0.05, uncorrected. Positive correlations throughout the brain are apparent and there are no negative correlations in task-positive regions. This is true even when the threshold is reduced to p<0.5.
Figure 4
Figure 4
Maps showing how connectivity to the MFC seed region is related to working memory performance when connectivity-behavior relationships are computed using two different approaches to adjust for synchronized global activity. A) Global timecourse is removed during the computation of functional connectivity in each subject (Strategy 1). B) No removal of global timecourse in the computation of functional connectivity maps, but the magnitude of whole-brain correlation (Δ) is adjusted for the group-level analysis (Strategy 3). These images depicts the axial slice located at z=14 in Talairach coordinates, shown at an uncorrected threshold of p<0.05. Arrows indicate the location of the two ROIs where we found significant connectivity-behavior relationships: a negative relationship in left DLPFC (white arrow) and a positive one in PCC (black arrow). Here results from the two analyses converge. Differences in the two maps are also apparent in several locations, as highlighted by the red circles.

References

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