Evolving Networks Processing Signals with a Mixed Paradigm, Inspired by Gene Regulatory Networks and Spiking Neurons

  • Borys Wróbel
  • Ahmed Abdelmotaleb
  • Michał Joachimczak
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 134)


In this paper we extend our artificial life platform, called GReaNs (for Genetic Regulatory evolving artificial Networks) to allow evolution of spiking neural networks performing simple computational tasks. GReaNs has been previously used to model evolution of gene regulatory networks for processing signals, and also for controlling the behaviour of unicellular animats and the development of multicellular structures in two and three dimensions. The connectivity of the regulatory network in GReaNs is encoded in a linear genome. No explicit restrictions are set for the size of the genome or the size of the network. In our previous work, the way the nodes in the regulatory network worked was inspired by biological transcriptional units. In the extension presented here we modify the equations governing the behaviour of the units so that they describe spiking neurons: either leaky integrate and fire neurons with a fixed threshold or adaptive-exponential integrate and fire neurons. As a proof-of-principle, we report the evolution of spiking networks that match desired spiking patterns.


Evolutionary algorithms Gene regulatory networks Spiking neural networks Signal processing Leaky integrate and fire neurons Adaptive-exponential neurons 



This work was supported by the Polish Ministry of Science and Higher Education (project 2011/03/B/ST6/00399 to BW); BW acknowledges the support of the Swiss-Polish Research Fund, AA the support of the Foundation for Polish Science, co-financed by EU Regional Development Fund (Innovative Economy Operational Programme 2007–2013). We are also grateful to Volker Steuber for discussions.


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Copyright information

© Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2014

Authors and Affiliations

  • Borys Wróbel
    • 1
    • 2
    • 3
  • Ahmed Abdelmotaleb
    • 2
  • Michał Joachimczak
    • 3
  1. 1.Institute of NeuroinformaticsUniversity of Zurich/ETHZZurichSwitzerland
  2. 2.Evolutionary Systems LaboratoryAdam Mickiewicz University in PoznanPoznanPoland
  3. 3.Systems Modelling LaboratoryIOPAS in SopotSopotPoland

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