A nonparametric test of group distributional differences for hierarchically clustered functional data.

ABSTRACT: Biological sex and gender are critical variables in biomedical research, but are complicated by the presence of sex-specific natural hormone cycles, such as the estrous cycle in female rodents, typically divided into phases. A common feature of these cycles are fluctuating hormone levels that induce sex differences in many behaviors controlled by the electrophysiology of neurons, such as neuronal membrane potential in response to electrical stimulus, typically summarized using a priori defined metrics. In this paper, we propose a method to test for differences in the electrophysiological properties across estrous cycle phase without first defining a metric of interest. We do this by modeling membrane potential data in the frequency domain as realizations of a bivariate process, also depend

SUBMITTER: Long AS 

PROVIDER: S-EPMC10695330 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature