Eigenvector Centrality of the Visual Network exceeds the Default Mode Network during Rest
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2020-07-09
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en
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Abstract
The default mode network (DMN) is one of the resting state networks (RSNs) in the
brain that have been identified by investigating temporal correlations of spontaneous activity
fluctuations in resting state fMRI (rsfMRI). The DMN is crucial for efficient cognitive
functioning, although evidently decreasing in activity during many cognitive tasks. Even though the
DMN is typically identified by independent component analysis (ICA), other methods have been used
to extract and analyze the network as well and their relation to ICA has been explored. However, no
comparison of ICA and eigenvector centrality mapping, another data-driven, but graph-theory based
method has been reported yet. Here, we used 100 rsfMRI data sets to show that the medial visual
network, rather than the DMN, was the most central network during rest and that its eigenvector
centrality correlated negatively with the centrality of the DMN. Accordingly, the most central
areas during rest did not conform with the DMN extracted by ICA. Our results suggest that the
visual RSNs play a more versatile and not strictly modular function during rest and that the
investigation of their individual variations is more important than previously believed.
Keywords: DMN, visual network, eigenvector centrality, ICA, rsfMRI
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Faculteit der Sociale Wetenschappen