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. 2013 Aug 5;8(8):e70275.
doi: 10.1371/journal.pone.0070275. Print 2013.

Stability of Whole Brain and Regional Network Topology Within and Between Resting and Cognitive States

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Free PMC article

Stability of Whole Brain and Regional Network Topology Within and Between Resting and Cognitive States

Justyna K Rzucidlo et al. PLoS One. .
Free PMC article

Abstract

Background: Graph-theory based analyses of resting state functional Magnetic Resonance Imaging (fMRI) data have been used to map the network organization of the brain. While numerous analyses of resting state brain organization exist, many questions remain unexplored. The present study examines the stability of findings based on this approach over repeated resting state and working memory state sessions within the same individuals. This allows assessment of stability of network topology within the same state for both rest and working memory, and between rest and working memory as well.

Methodology/principal findings: fMRI scans were performed on five participants while at rest and while performing the 2-back working memory task five times each, with task state alternating while they were in the scanner. Voxel-based whole brain network analyses were performed on the resulting data along with analyses of functional connectivity in regions associated with resting state and working memory. Network topology was fairly stable across repeated sessions of the same task, but varied significantly between rest and working memory. In the whole brain analysis, local efficiency, Eloc, differed significantly between rest and working memory. Analyses of network statistics for the precuneus and dorsolateral prefrontal cortex revealed significant differences in degree as a function of task state for both regions and in local efficiency for the precuneus. Conversely, no significant differences were observed across repeated sessions of the same state.

Conclusions/significance: These findings suggest that network topology is fairly stable within individuals across time for the same state, but also fluid between states. Whole brain voxel-based network analyses may prove to be a valuable tool for exploring how functional connectivity changes in response to task demands.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Top overlap maps of local efficiency (Eloc) and K (Degree) for a sample participant showing the consistency of the location of nodes in the top 20% across 5 sessions for Rest (A) and n-back (B).
The color scale indicates the % of sessions that each area was in the top 20% of nodes. Note that the K maps show greater consolidation and are more task-specific compared to the Eloc maps.
Figure 2
Figure 2. “Meta” consistency maps of Eloc showing the percentage of subjects for whom each brain region was consistently the location of high Eloc nodes.
The DLPFC exhibited greater consistency across subjexts for the n-back condition compared to the resting condition. The precuneus appeared to have similar consistency between the resting and n-back conditions. The figure includes two axial slices through DLPFC and 3 sagital slices through the precuneus. Only right hemisphere sagital slices are shown as the left side essentially mirrored the right. The arrows point to DLPFC and the circles highlight the precuneus.
Figure 3
Figure 3. “Meta” consistency maps of K showing the percentage of subjects for whom each brain region was consistently the location of high K nodes.
These maps exhibit clear task-specific patterns in the location of the consistently high K nodes. At rest, the precuneus was a major connecting hub in virtually every subject and every session. This consistency drops considerably in the n-back condition. However, the DLPFC becomes highly consistent in the n-back condition. The figure includes two axial slices through DLPFC and 3 sagital slices through the precuneus. Only right hemisphere sagital slices are shown as the left side essentially mirrored the right. The arrows point to DLPFC and the circles highlight the precuneus.
Figure 4
Figure 4. Nodes consistently connected to the top 15 percent high local efficiency nodes in the precuneus across sessions and subjects.
The figure demonstrates that these top local efficiency nodes were primarily connected to adjacent brain areas. At rest the focus of connectivity is ventral and includes the posterior cingulate. During n-back the focus of connectivity is more dorsal and includes posterior parietal cortex. A sagital and axial slice through the precuneus are shown.
Figure 5
Figure 5. Nodes consistently connected to the top 15 percent high degree nodes in the DLPFC across sessions and subjects.
The figure demonstrates that these top degree nodes changed connectivity considerably across conditions. At rest the connections were restricted to frontal cortex. During the n-back conditions connections were consistently present in the lateral parietal cortex. Two axial slices are shown to include the DLPFC and the lateral parietal cortex. The sagital slice is shown to include the precuneus (lacking any consistent connectivity) for comparison to other figures.

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Grant support

Internal institutional grants to the first and third author supported this research. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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