Comparing Structural Brain Connectivity by the Infinite Relational Model

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2013

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The growing focus in neuroimaging on analyzing brain connectivity calls for powerful and reliable statistical modeling tools. We examine the Infinite Relational Model (IRM) as a tool to identify and compare structure in brain connectivity graphs by contrasting its performance on graphs from the same subject versus graphs from different subjects. The inferred structure is most consistent between graphs from the same subject, however, the model is able to predict links in graphs from different subjects on par with results within a subject. The framework proposed can be used as a statistical modeling tool for the identification of structure and quantification of similarity in graphs of brain connectivity in general.
Original languageEnglish
Title of host publication2013 International Workshop on Pattern Recognition in Neuroimaging (PRNI)
PublisherIEEE
Publication date2013
Pages50-53
ISBN (print)978-0-7695-5061-9
DOIs
StatePublished - 2013
Event3rd International Workshop on Pattern Recognition in NeuroImaging (PRNI 2013) - Philadelphia, PA, United States

Conference

Conference3rd International Workshop on Pattern Recognition in NeuroImaging (PRNI 2013)
CountryUnited States
CityPhiladelphia, PA
Period22/06/201324/06/2013
Internet address
CitationsWeb of Science® Times Cited: 5
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