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Topographical Information-Based High-Order Functional Connectivity and Its Application in Abnormality Detection for Mild Cognitive Impairment
Univ North Carolina Chapel Hill, Dept Radiol, Chapel Hill, NC USA.;Univ North Carolina Chapel Hill, BRIC, Chapel Hill, NC USA..
Univ North Carolina Chapel Hill, Dept Radiol, Chapel Hill, NC USA.;Univ North Carolina Chapel Hill, BRIC, Chapel Hill, NC USA..
Univ North Carolina Chapel Hill, Dept Radiol, Chapel Hill, NC USA.;Univ North Carolina Chapel Hill, BRIC, Chapel Hill, NC USA..
Univ North Carolina Chapel Hill, Dept Radiol, Chapel Hill, NC USA.;Univ North Carolina Chapel Hill, BRIC, Chapel Hill, NC USA..
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2016 (English)In: Journal of Alzheimer's Disease, ISSN 1387-2877, E-ISSN 1875-8908, Vol. 54, no 3, 1095-1112 p.Article in journal (Refereed) Published
Abstract [en]

Temporal synchronization-based functional connectivity (FC) has long been used by the neuroscience community. However, topographical FC information may provide additional information to characterize the advanced relationship between two brain regions. Accordingly, we proposed a novel method, namely high-order functional connectivity (HOFC), to capture this second-level relationship using inter-regional resemblance of the FC topographical profiles. Specifically, HOFC first calculates an FC profile for each brain region, notably between the given brain region and other brain regions. Based on these FC profiles, a second layer of correlations is computed between all pairs of brain regions (i.e., correlation's correlation). On this basis, we generated an HOFC network, where "high-order" network properties were computed. We found that HOFC was discordant with the traditional FC in several links, indicating additional information being revealed by the new metrics. We applied HOFC to identify biomarkers for early detection of Alzheimer's disease by comparing 77 mild cognitive impairment patients with 89 healthy individuals (control group). Sensitivity in detection of group difference was consistently improved by similar to 25% using HOFC compared to using FC. An HOFC network analysis also provided complementary information to an FC network analysis. For example, HOFC between olfactory and orbitofrontal cortices was found significantly reduced in patients, besides extensive alterations in HOFC network properties. In conclusion, our results showed promise in using HOFC to comprehensively map the human brain connectome.

Place, publisher, year, edition, pages
2016. Vol. 54, no 3, 1095-1112 p.
Keyword [en]
Alzheimer's disease, biomarker, early detection, functional connectivity, functional magnetic resonance imaging (fMRI), high-order connectivity, mild cognitive impairment, resting state fMRI
National Category
Neurosciences
Identifiers
URN: urn:nbn:se:uu:diva-308062DOI: 10.3233/JAD-160092ISI: 000385651800023PubMedID: 27567817OAI: oai:DiVA.org:uu-308062DiVA: diva2:1050985
Available from: 2016-11-30 Created: 2016-11-23 Last updated: 2016-11-30Bibliographically approved

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Haller, Sven
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