Abstract
BackgroundGraph-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 FindingsfMRI 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/SignificanceThese 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.
Highlights
While much effort has been expended in order to understand localization of function in the human brain over the past thirty years, there is growing interest in using new methodologies to address other important issues in neuroscience
This paper examines functional connectivity within the human brain using a voxel-based examination of functional Magnetic Resonance Imaging data that allows information from the entire brain to be used in network construction
We explored the meaning of these differences by mapping the network nodes throughout the brain that were connected to the top fifteen percent of the local efficiency and degree nodes within the regions of interest (ROI)
Summary
They are based on the idea that a network is composed of a collection of nodes that are connected by edges, and that these metrics can provide important information about the whole network, individual nodes, and anywhere in between In neuroscience, these measures have been applied extensively to resting state fMRI data, and have been useful in characterizing normal brain organization and how that changes in disease states such as schizophrenia [4]. Stability of Regional Network Metrics Moussa et al [15] compared network topology for resting state, visual processing, and multisensory processing They found no significant task-related effects on whole brain network measures. Networks were constructed for five participants during five resting state and five working memory 2-back sessions that were alternated
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