IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v500y2025ics009630032500164x.html
   My bibliography  Save this article

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

Author

Listed:
  • Antonacci, Yuri
  • Barà, Chiara
  • de Felice, Giulio
  • Sferlazza, Antonino
  • Pernice, Riccardo
  • Faes, Luca

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.

Suggested Citation

  • Antonacci, Yuri & Barà, Chiara & de Felice, Giulio & Sferlazza, Antonino & Pernice, Riccardo & Faes, Luca, 2025. "Exploring transient neurophysiological states through local and time-varying measures of information dynamics," Applied Mathematics and Computation, Elsevier, vol. 500(C).
    • Handle: RePEc:eee:apmaco:v:500:y:2025:i:c:s009630032500164x
    DOI: 10.1016/j.amc.2025.129437
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S009630032500164X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2025.129437?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Amos Golan & John Harte, 2022. "Information theory: A foundation for complexity science," Decision Analysis, INFORMS, vol. 119(33), pages 2119089119-, August.
    2. Amos Golan & John Harte, 2022. "Information theory: A foundation for complexity science," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 119(33), pages 2119089119-, August.
    3. Mattia F Pagnotta & Gijs Plomp, 2018. "Time-varying MVAR algorithms for directed connectivity analysis: Critical comparison in simulations and benchmark EEG data," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-27, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Riera, Rodrigo & Fath, Brian D. & Herrera, Ada M. & Rodríguez, Ricardo A., 2023. "Concerns regarding the proposal for an ecological equation of state: an assessment starting from the organic biophysics of ecosystems (OBEC)," Ecological Modelling, Elsevier, vol. 484(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:apmaco:v:500:y:2025:i:c:s009630032500164x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.