Spatial Dependencies between Large-Scale Brain Networks
File(s)
Author(s)
Type
Journal Article
Abstract
<p>Functional neuroimaging reveals both increases (task-positive) and decreases (task-negative) in neural activation with many tasks. Many studies show a <italic>temporal</italic> relationship between task positive and task negative networks that is important for efficient cognitive functioning. Here we provide evidence for a <italic>spatial</italic> relationship between task positive and negative networks. There are strong spatial similarities between many reported task negative brain networks, termed the default mode network, which is typically assumed to be a spatially fixed network. However, this is not the case. The spatial structure of the DMN varies depending on what specific task is being performed. We test whether there is a fundamental <italic>spatial</italic> relationship between task positive and negative networks. Specifically, we hypothesize that the distance between task positive and negative voxels is consistent despite different spatial patterns of activation and deactivation evoked by different cognitive tasks. We show significantly reduced variability in the distance between within-condition task positive and task negative voxels than across-condition distances for four different sensory, motor and cognitive tasks - implying that deactivation patterns are spatially dependent on activation patterns (and <italic>vice versa</italic>), and that both are modulated by specific task demands. We also show a similar relationship between positively and negatively correlated networks from a third ‘rest’ dataset, in the absence of a specific task. We propose that this spatial relationship may be the macroscopic analogue of microscopic neuronal organization reported in sensory cortical systems, and that this organization may reflect homeostatic plasticity necessary for efficient brain function.</p>
Date Issued
2014-06-02
Citation
PLoS ONE, 2014, 9 (6), pp.e98500-
ISSN
1932-6203
Publisher
Public Library of Science
Start Page
e98500
Journal / Book Title
PLoS ONE
Volume
9
Issue
6
Copyright Statement
© 2014 Leech et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
License URL
Description
13.10.14 KB. OK to add published version to spiral, OA paper
Identifier
http://dx.doi.org/10.1371/journal.pone.0098500
Publication Status
Published