Exploring transient neurophysiological states through local and time-varying measures of information dynamics

Yuri Antonacci, Chiara Barà, Giulio de Felice, Antonino Sferlazza, Riccardo Pernice and Luca Faes

Applied Mathematics and Computation, 2025, vol. 500, issue C

Abstract: Studying the temporal evolution of complex systems requires tools able to quantify the strength of predictable dynamics within their output signals. Among information theoretic measures, information storage (IS) reflects the regularity of system dynamics by measuring the information shared between the present and the past system states.

Keywords: Information dynamics; Time-resolved information measures; Time series analysis; Autoregressive models; Sleep apneas; Epicranial electroencephalogram (EEG) (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:500:y:2025:i:c:s009630032500164x

DOI: 10.1016/j.amc.2025.129437

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