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Neuroimage. 2014 Nov 15;102 Pt 1:118-27. doi: 10.1016/j.neuroimage.2013.12.022. Epub 2013 Dec 21.

The structural and functional connectivity of the posterior cingulate cortex: comparison between deterministic and probabilistic tractography for the investigation of structure-function relationships.

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  • 1School of Psychology, University of Birmingham, Birmingham, UK; Birmingham University Imaging Centre (BUIC), University of Birmingham, Birmingham, UK; Department of Neuropsychiatry, The Barberry Centre for Mental Health, Birmingham, UK.
  • 2School of Psychology, University of Birmingham, Birmingham, UK; Birmingham University Imaging Centre (BUIC), University of Birmingham, Birmingham, UK.
  • 3Department of Experimental Psychology, Oxford University, Oxford, UK.
  • 4Department of Neuropsychiatry, The Barberry Centre for Mental Health, Birmingham, UK.
  • 5School of Psychology, University of Birmingham, Birmingham, UK; Birmingham University Imaging Centre (BUIC), University of Birmingham, Birmingham, UK. Electronic address: a.p.bagshaw@bham.ac.uk.

Abstract

The default mode network (DMN) is one of the most studied resting-state networks, and is thought to be involved in the maintenance of consciousness within the alert human brain. Although many studies have examined the functional connectivity (FC) of the DMN, few have investigated its underlying structural connectivity (SC), or the relationship between the two. We investigated this question in fifteen healthy subjects, concentrating on connections to the precuneus/posterior cingulate cortex (PCC), commonly considered as the central node of the DMN. We used group independent component analysis (GICA) and seed-based correlation analysis of fMRI data to quantify FC, and streamline and probabilistic tractography to identify structural tracts from diffusion tensor imaging (DTI) data. We first assessed the presence of structural connections between the DMN regions identified with GICA. Of the 15 subjects, when using the probabilistic approach 15 (15) demonstrated connections between the PCC and mesial prefrontal cortex (mPFC), 11 (15) showed connections from the PCC to the right inferior parietal cortex (rIPC) and 8 (15) to the left IPC. Next, we assessed the strength of FC (magnitude of temporal correlation) and SC (mean fractional anisotropy of reconstructed tracts (streamline), number of super-threshold voxels within the mask region (probabilistic)). The lIPC had significantly reduced FC to the PCC compared to the mPFC and rIPC. No difference in SC strength between connections was found using the streamline approach. For the probabilistic approach, mPFC had significantly lower SC than both IPCs. The two measures of SC strength were significantly correlated, but not for all paired connections. Finally, we observed a significant correlation between SC and FC for both tractography approaches when data were pooled across PCC-lIPL, PCC-rIPL and PCC-mPFC connections, and for some individual paired connections. Our results suggest that the streamline approach is advantageous for characterising the connectivity of long white matter tracts (PCC-mPFC), whilst the probabilistic approach was more reliable at identifying PCC-IPC connections. The direct comparison of FC and SC indicated that pairs of nodes with stronger structural connections also had stronger functional connectivity, and that this was maintained with both tractography approaches. Whilst the definition of SC strength remains controversial, our results could be considered to provide some degree of validation for the measures of SC strength that we have used. Direct comparisons of SC and FC are necessary in order to understand the structural basis of functional connectivity, and to characterise and quantify the changes in the brain's functional architecture that occur as a result of normal physiology or pathology.

Copyright © 2014 Elsevier Inc. All rights reserved.

KEYWORDS:

DMN; Diffusion tensor imaging; Functional connectivity; Precuneus; Structural connectivity; Tractography; fMRI

PMID:
24365673
[PubMed - indexed for MEDLINE]
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