Directed network motifs in Alzheimer's disease and mild cognitive impairment

Directed network motifs are the building blocks of complex networks, such as human brain networks, and capture deep connectivity information that is not contained in standard network measures. In this paper we present the first application of directed network motifs in vivo to human brain networks,...

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Published inPloS one Vol. 10; no. 4; p. e0124453
Main Authors Friedman, Eric J, Young, Karl, Tremper, Graham, Liang, Jason, Landsberg, Adam S, Schuff, Norbert
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 16.04.2015
Public Library of Science (PLoS)
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Summary:Directed network motifs are the building blocks of complex networks, such as human brain networks, and capture deep connectivity information that is not contained in standard network measures. In this paper we present the first application of directed network motifs in vivo to human brain networks, utilizing recently developed directed progression networks which are built upon rates of cortical thickness changes between brain regions. This is in contrast to previous studies which have relied on simulations and in vitro analysis of non-human brains. We show that frequencies of specific directed network motifs can be used to distinguish between patients with Alzheimer's disease (AD) and normal control (NC) subjects. Especially interesting from a clinical standpoint, these motif frequencies can also distinguish between subjects with mild cognitive impairment who remained stable over three years (MCI) and those who converted to AD (CONV). Furthermore, we find that the entropy of the distribution of directed network motifs increased from MCI to CONV to AD, implying that the distribution of pathology is more structured in MCI but becomes less so as it progresses to CONV and further to AD. Thus, directed network motifs frequencies and distributional properties provide new insights into the progression of Alzheimer's disease as well as new imaging markers for distinguishing between normal controls, stable mild cognitive impairment, MCI converters and Alzheimer's disease.
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Competing Interests: NS received consulting honoraria from Eli Lilly as financial interest. This does not alter the authors’ adherence to PLOS ONE policies on sharing data and materials.
Conceived and designed the experiments: EJF KY NS. Performed the experiments: EJF GT JL. Analyzed the data: EJF GT JL NS KY ASL. Contributed reagents/materials/analysis tools: NS EJF. Wrote the paper: EJF GT JL NS KY ASL.
Membership of the Alzheimer's Disease Neuroimaging Initiative is provided in the Acknowledgments.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0124453