Time-varying information measures: an adaptive estimation of information storage with application to brain-heart interactions.

ABSTRACT: Network Physiology is a rapidly growing field of study that aims to understand how physiological systems interact to maintain health. Within the information theory framework the information storage (IS) allows to measure the regularity and predictability of a dynamic process under stationarity assumption. However, this assumption does not allow to track over time the transient pathways occurring in the dynamical activity of a physiological system. To address this limitation, we propose a time-varying approach based on the recursive least squares algorithm (RLS) for estimating IS at each time instant, in non-stationary conditions. We tested this approach in simulated time-varying dynamics and in the analysis of electroencephalographic (EEG) signals recorded from healthy volunteers and timed

SUBMITTER: Antonacci Y 

PROVIDER: S-EPMC10619917 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature