Distance-based analysis of variance for brain connectivity.

ABSTRACT: The field of neuroimaging dedicated to mapping connections in the brain is increasingly being recognized as key for understanding neurodevelopment and pathology. Networks of these connections are quantitatively represented using complex structures, including matrices, functions, and graphs, which require specialized statistical techniques for estimation and inference about developmental and disorder-related changes. Unfortunately, classical statistical testing procedures are not well suited to high-dimensional testing problems. In the context of global or regional tests for differences in neuroimaging data, traditional analysis of variance (ANOVA) is not directly applicable without first summarizing the data into univariate or low-dimensional features, a process that might mask the salient

SUBMITTER: Shinohara RT 

PROVIDER: S-EPMC7653688 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature