Abstract
Recent work on functional magnetic resonance imaging large-scale brain networks under resting conditions demonstrated its potential to evaluate the integrity of brain function under normal and pathological conditions. A similar approach is used in this work to study a group of chronic back pain patients and healthy controls to determine the impact of long enduring pain over brain dynamics. Correlation networks were constructed from the mutual partial correlations of brain activity's time series selected from ninety regions using a well validated brain parcellation atlas. The study of the resulting networks revealed an organization of up to six communities with similar modularity in both groups, but with important differences in the membership of key communities of frontal and temporal regions. The bulk of these findings were confirmed by a surprisingly naive analysis based on the pairwise correlations of the strongest and weakest correlated healthy regions. Beside confirming the brain effects of long enduring pain, these results provide a framework to study the effect of other chronic conditions over cortical function.
Highlights
Since the initial work of Eguiluz et al (2005), complex networks has been widely used to represent functional brain networks
Qmax depends on NL, no significant differences where found between HCP and chronic back pain (CBP), for any www.frontiersin.org given NL
The major aim of the present study was to examine the modular organization of functional brain networks in CBP
Summary
Since the initial work of Eguiluz et al (2005), complex networks has been widely used to represent functional brain networks. The organization of resting state brain activity in groups of networks or modules has been studied using different strategies, ranging from univariate analysis as seed correlation (Fox et al, 2005, for example), multivariate linear approaches, as probabilistic independent component analysis (ICA) (Beckmann et al, 2005; Smith et al, 2009) and modular organization in complex networks (Stanberry et al, 2008; Meunier et al, 2009a,b) These analyses has been useful to evaluate the integrity of brain function under normal (Damoiseaux et al, 2006) and pathological conditions (Broyd et al, 2009), including Alzheimer disease (He et al, 2008), schizophrenia (Garrity et al, 2007), and epilepsy (Laufs et al, 2007; Lui et al, 2008), but has not been used in analyzing chronic back pain (CBP) condition. The modular organization of these networks in both groups is analyzed and significant changes in the communities are contrasted within a pairwise correlations approach
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