REGION-REFERENCED SPECTRAL POWER DYNAMICS OF EEG SIGNALS: A HIERARCHICAL MODELING APPROACH.

ABSTRACT: Functional brain imaging through electroencephalography (EEG) relies upon the analysis and interpretation of high-dimensional, spatially organized time series. We propose to represent time-localized frequency domain characterizations of EEG data as region-referenced functional data. This representation is coupled with a hierarchical regression modeling approach to multivariate functional observations. Within this familiar setting we discuss how several prior models relate to structural assumptions about multivariate covariance operators. An overarching modeling framework, based on infinite factorial decompositions, is finally proposed to balance flexibility and efficiency in estimation. The motivating application stems from a study of implicit auditory learning, in which typically developi

SUBMITTER: Li Q 

PROVIDER: S-EPMC8329765 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature