A Communicative Model: Can We Interpret Neural Dynamics of Understanding?

  • Yongtao Li
  • Ichiro Tsuda
Conference paper


In this paper, a communicative model with two nonequilibrium neural networks is proposed to emulate the dynamical process of how we can understand each other. A novelty-induced learning process is introduced to realize memory transmission between heterogeneous neural network models. The simulation results suggest that the communicative model could subserve to interpret the underlying neural mechanism of understanding.


Pyramidal Neuron Memory Retrieval Communicative Model Mirror Neuron Hopfield Neural Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was partially supported by a Grant-in-Aid for Scientific Research on Innovative Areas (No.4103)(21120002) from MEXT in Japan and partially supported by HFSPO(HFSP:RGP0039).


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Research Center for Integrative MathematicsHokkaido UniversitySapporoJapan
  2. 2.Research Institute for Electronic ScienceHokkaido UniversitySapporoJapan

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