Literature DB >> 27341264

Information Flows? A Critique of Transfer Entropies.

Ryan G James1,2, Nix Barnett1,3, James P Crutchfield1,2,3.   

Abstract

A central task in analyzing complex dynamics is to determine the loci of information storage and the communication topology of information flows within a system. Over the last decade and a half, diagnostics for the latter have come to be dominated by the transfer entropy. Via straightforward examples, we show that it and a derivative quantity, the causation entropy, do not, in fact, quantify the flow of information. At one and the same time they can overestimate flow or underestimate influence. We isolate why this is the case and propose several avenues to alternate measures for information flow. We also address an auxiliary consequence: The proliferation of networks as a now-common theoretical model for large-scale systems, in concert with the use of transferlike entropies, has shoehorned dyadic relationships into our structural interpretation of the organization and behavior of complex systems. This interpretation thus fails to include the effects of polyadic dependencies. The net result is that much of the sophisticated organization of complex systems may go undetected.

Year:  2016        PMID: 27341264     DOI: 10.1103/PhysRevLett.116.238701

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  20 in total

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2.  Ensemble stacking mitigates biases in inference of synaptic connectivity.

Authors:  Brendan Chambers; Maayan Levy; Joseph B Dechery; Jason N MacLean
Journal:  Netw Neurosci       Date:  2018-03-01

3.  Transfer Information Energy: A Quantitative Indicator of Information Transfer between Time Series.

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Journal:  Entropy (Basel)       Date:  2018-04-27       Impact factor: 2.524

4.  Can Transfer Entropy Infer Information Flow in Neuronal Circuits for Cognitive Processing?

Authors:  Ali Tehrani-Saleh; Christoph Adami
Journal:  Entropy (Basel)       Date:  2020-03-28       Impact factor: 2.524

5.  Minimising the Kullback-Leibler Divergence for Model Selection in Distributed Nonlinear Systems.

Authors:  Oliver M Cliff; Mikhail Prokopenko; Robert Fitch
Journal:  Entropy (Basel)       Date:  2018-01-23       Impact factor: 2.524

6.  Four-Types of IIT-Induced Group Integrity of Plecoglossus altivelis.

Authors:  Takayuki Niizato; Kotaro Sakamoto; Yoh-Ichi Mototake; Hisashi Murakami; Takenori Tomaru; Tomotaro Hoshika; Toshiki Fukushima
Journal:  Entropy (Basel)       Date:  2020-06-30       Impact factor: 2.524

7.  Optimal Microbiome Networks: Macroecology and Criticality.

Authors:  Jie Li; Matteo Convertino
Journal:  Entropy (Basel)       Date:  2019-05-17       Impact factor: 2.524

8.  Transfer entropy dependent on distance among agents in quantifying leader-follower relationships.

Authors:  Udoy S Basak; Sulimon Sattari; Motaleb Hossain; Kazuki Horikawa; Tamiki Komatsuzaki
Journal:  Biophys Physicobiol       Date:  2021-05-15

9.  New perspectives in the study of the Earth's magnetic field and climate connection: The use of transfer entropy.

Authors:  S A Campuzano; A De Santis; F J Pavón-Carrasco; M L Osete; E Qamili
Journal:  PLoS One       Date:  2018-11-15       Impact factor: 3.240

10.  Decoding collective communications using information theory tools.

Authors:  K R Pilkiewicz; B H Lemasson; M A Rowland; A Hein; J Sun; A Berdahl; M L Mayo; J Moehlis; M Porfiri; E Fernández-Juricic; S Garnier; E M Bollt; J M Carlson; M R Tarampi; K L Macuga; L Rossi; C-C Shen
Journal:  J R Soc Interface       Date:  2020-03-18       Impact factor: 4.118

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