Hierarchical multivariate covariance analysis of metabolic connectivity

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dc.contributor.authorCarbonell, Fen_AU
dc.contributor.authorCharil, Aen_AU
dc.contributor.authorZijdenbos, APen_AU
dc.contributor.authorEvans, ACen_AU
dc.contributor.authorBedell, BJen_AU
dc.date.accessioned2020-03-30T01:00:02Zen_AU
dc.date.available2020-03-30T01:00:02Zen_AU
dc.date.issued2014-10-08en_AU
dc.date.statistics2020-03-20en_AU
dc.description.abstractConventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI).© 2014,SAGE Publicationsen_AU
dc.identifier.citationCarbonell, F., Charil, A., Zijdenbos, A. P., Evans, A. C., & Bedell, B. J. (2014). Hierarchical multivariate covariance analysis of metabolic connectivity. Journal of Cerebral Blood Flow & Metabolism, 34(12), 1936–1943. doi:10.1038/jcbfm.2014.165en_AU
dc.identifier.govdoc8693en_AU
dc.identifier.issn1559-7016en_AU
dc.identifier.issue12en_AU
dc.identifier.journaltitleJournal of Cerebral Blood Flow & Metabolismen_AU
dc.identifier.pagination1936-1943en_AU
dc.identifier.urihttps://doi.org/10.1038/jcbfm.2014.165en_AU
dc.identifier.urihttp://apo.ansto.gov.au/dspace/handle/10238/9306en_AU
dc.identifier.volume34en_AU
dc.language.isoenen_AU
dc.publisherSAGE Publicationsen_AU
dc.subjectMultivariate analysisen_AU
dc.subjectMathematicsen_AU
dc.subjectMetabolic diseasesen_AU
dc.subjectBrainen_AU
dc.subjectFluorine 18en_AU
dc.subjectAgingen_AU
dc.subjectDiseasesen_AU
dc.subjectPositron computed tomographyen_AU
dc.subjectMetabolismen_AU
dc.titleHierarchical multivariate covariance analysis of metabolic connectivityen_AU
dc.typeJournal Articleen_AU
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