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Special Issue "Information Dynamics in Brain and Physiological Networks"

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory".

Deadline for manuscript submissions: 30 December 2018

Special Issue Editors

Guest Editor
Prof. Dr. Luca Faes

Department of Energy, Information engineering and Mathematical models (DEIM), University of Palermo, Viale delle Scienze, Ed. 9, 90128 Palermo, Italy
Website | E-Mail
Interests: biomedical signal processing; computational physiology and neuroscience; statistical physics; time series analysis
Guest Editor
Prof. Dr. Alberto Porta

Department of Biomedical Sciences for Health, University of Milan, Milan, Italy and Department of Cardiothoracic, Vascular Anesthesia and Intensive Care, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy
Interests: time series analysis; cardiovascular control; complexity
Guest Editor
Prof. Dr. Sebastiano Stramaglia

Dipartimento Interateneo di Fisica, Università di Bari, and INFN Sezione di Bari. 70126 Bari, Italy
Website | E-Mail
Interests: time series analysis; network neuroscience; network physiology

Special Issue Information

Dear Colleagues,

It is, nowadays, widely acknowledged that the brain and several other organ systems, including the cardiovascular, respiratory, and muscular systems, among others, exhibit complex dynamic behaviors that result from the combined effects of multiple regulatory mechanisms, coupling effects and feedback interactions, acting in both space and time.

The field of information theory is becoming more and more relevant for the theoretical description and quantitative assessment of the dynamics of the brain and physiological networks, defining concepts, such as those of information generation, storage, transfer, and modification. These concepts are quantified by several information measures (e.g., approximate entropy, conditional entropy, multiscale entropy, transfer entropy, redundancy and synergy, and many others), which are being increasingly used to investigate how physiological dynamics arise from the activity and connectivity of different structural units, and evolve across a variety of physiological states and pathological conditions.

This Special Issue focuses on blending theoretical developments in the new emerging field of information dynamics with innovative applications targeted to the analysis of complex brain and physiological networks in health and disease. To favor this multidisciplinary view, contributions are welcome from different fields, ranging from mathematics and physics to biomedical engineering, neuroscience, and physiology.

Prof. Dr. Luca Faes
Prof. Dr. Alberto Porta
Prof. Dr. Sebastiano Stramaglia
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • Dynamical complexity,
  • Multivariate time series analysis,
  • Information storage,
  • Transfer entropy,
  • Redundancy and synergy,
  • Network physiology,
  • Brain connectivity,
  • Cardiovascular oscillations,
  • Neuroscience


Published Papers (1 paper)

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Open AccessArticle Interaction Information Along Lifespan of the Resting Brain Dynamics Reveals a Major Redundant Role of the Default Mode Network
Entropy 2018, 20(10), 742; https://doi.org/10.3390/e20100742
Received: 1 August 2018 / Revised: 7 September 2018 / Accepted: 24 September 2018 / Published: 28 September 2018
PDF Full-text (2633 KB) | HTML Full-text | XML Full-text | Supplementary Files
Interaction Information (II) generalizes the univariate Shannon entropy to triplets of variables, allowing the detection of redundant (R) or synergetic (S) interactions in dynamical networks. Here, we calculated II from functional magnetic resonance imaging data and asked whether R or S vary across
[...] Read more.
Interaction Information (II) generalizes the univariate Shannon entropy to triplets of variables, allowing the detection of redundant (R) or synergetic (S) interactions in dynamical networks. Here, we calculated II from functional magnetic resonance imaging data and asked whether R or S vary across brain regions and along lifespan. Preserved along lifespan, we found high overlapping between the pattern of high R and the default mode network, whereas high values of S were overlapping with different cognitive domains, such as spatial and temporal memory, emotion processing and motor skills. Moreover, we have found a robust balance between R and S among different age intervals, indicating informational compensatory mechanisms in brain networks. Full article
(This article belongs to the Special Issue Information Dynamics in Brain and Physiological Networks)

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