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

Friedman EJ, Young K, Tremper G, Liang J, Landsberg AS, Schuff N, Alzheimer's Disease Neuroimaging Initiati - PLoS ONE (2015)

Bottom Line: This is in contrast to previous studies which have relied on simulations and in vitro analysis of non-human brains.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.

View Article: PubMed Central - PubMed

Affiliation: International Computer Science Institute, Berkeley, CA, United States of America; Department of Computer Science, University of California, Berkeley, Berkeley, CA, United States of America.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus

Motif frequencies for NC, MCI, CONV and AD.Significance refers to NC/AD comparisons.
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pone.0124453.g005: Motif frequencies for NC, MCI, CONV and AD.Significance refers to NC/AD comparisons.

Mentions: The average 3-motif frequencies for the most significant motifs are shown in Fig 5. While the rank ordering of the motifs is fairly consistent among all subject types, significant differences in their motif frequencies are observable between normal control (NC) subjects and AD patients for most of the common motifs. In fact, twelve of the top thirteen 3-motifs are statistically significant for separating NC from AD (each at the 5% confidence level), with the majority of these significant at the 0.1% level. Hence these constitute new imaging markers for distinguishing AD from NC.


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

Friedman EJ, Young K, Tremper G, Liang J, Landsberg AS, Schuff N, Alzheimer's Disease Neuroimaging Initiati - PLoS ONE (2015)

Motif frequencies for NC, MCI, CONV and AD.Significance refers to NC/AD comparisons.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4400037&req=5

pone.0124453.g005: Motif frequencies for NC, MCI, CONV and AD.Significance refers to NC/AD comparisons.
Mentions: The average 3-motif frequencies for the most significant motifs are shown in Fig 5. While the rank ordering of the motifs is fairly consistent among all subject types, significant differences in their motif frequencies are observable between normal control (NC) subjects and AD patients for most of the common motifs. In fact, twelve of the top thirteen 3-motifs are statistically significant for separating NC from AD (each at the 5% confidence level), with the majority of these significant at the 0.1% level. Hence these constitute new imaging markers for distinguishing AD from NC.

Bottom Line: This is in contrast to previous studies which have relied on simulations and in vitro analysis of non-human brains.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.

View Article: PubMed Central - PubMed

Affiliation: International Computer Science Institute, Berkeley, CA, United States of America; Department of Computer Science, University of California, Berkeley, Berkeley, CA, United States of America.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus