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Information flow in heterogeneously interacting systems

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Abstract

Motivated by studies on the dynamics of heterogeneously interacting systems in neocortical neural networks, we studied heterogeneously-coupled chaotic systems. We used information-theoretic measures to investigate directions of information flow in heterogeneously coupled Rössler systems, which we selected as a typical chaotic system. In bi-directionally coupled systems, spontaneous and irregular switchings of the phase difference between two chaotic oscillators were observed. The direction of information transmission spontaneously switched in an intermittent manner, depending on the phase difference between the two systems. When two further oscillatory inputs are added to the coupled systems, this system dynamically selects one of the two inputs by synchronizing, selection depending on the internal phase differences between the two systems. These results indicate that the effective direction of information transmission dynamically changes, induced by a switching of phase differences between the two systems.

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Acknowledgments

We would like to thank H. Fujii for fruitful discussions. This work was supported by a Grant-in-Aid for Scientific Research on Innovative Areas “The study on the neural dynamics for understanding communication in terms of complex hetero systems (No. 4103)” (21120002) of The Ministry of Education, Culture, Sports, Science, and Technology, Japan.

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Authors and Affiliations

  1. Research Institute for Electronic Science, Hokkaido University, N12W7, Kita-ku, Sapporo, 060-0812, Japan

    Yutaka Yamaguti & Ichiro Tsuda

  2. Research Center for Integrative Mathematics, Hokkaido University, N12W7, Kita-ku, Sapporo, 060-0812, Japan

    Yutaka Yamaguti & Ichiro Tsuda

  3. Institute of Industrial Science, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo, 153-8505, Japan

    Yoichiro Takahashi

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  1. Yutaka Yamaguti
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  2. Ichiro Tsuda
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  3. Yoichiro Takahashi
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Correspondence to Yutaka Yamaguti.

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Yamaguti, Y., Tsuda, I. & Takahashi, Y. Information flow in heterogeneously interacting systems. Cogn Neurodyn 8, 17–26 (2014). https://doi.org/10.1007/s11571-013-9259-8

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  • DOI: https://doi.org/10.1007/s11571-013-9259-8

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