Multistage classification identifies altered cortical phase- and amplitude-coupling in Multiple Sclerosis.

ABSTRACT: Distinguishing groups of subjects or experimental conditions in a high-dimensional feature space is a common goal in modern neuroimaging studies. Successful classification depends on the selection of relevant features as not every neuronal signal component or parameter is informative about the research question at hand. Here, we developed a novel unsupervised multistage analysis approach that combines dimensionality reduction, bootstrap aggregating and multivariate classification to select relevant neuronal features. We tested the approach by identifying changes of brain-wide electrophysiological coupling in Multiple Sclerosis. Multiple Sclerosis is a demyelinating disease of the central nervous system that can result in cognitive decline and physical disability. However, related changes i

SUBMITTER: Siems M 

PROVIDER: S-EPMC9771829 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature