Modelling the Effect of Genes on the Dynamics of Probabilistic Spiking Neural Networks for Computational Neurogenetic Modelling

  • Nikola Kasabov
  • Stefan Schliebs
  • Ammar Mohemmed
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7548)


Computational neuro-genetic models (CNGM) combine two dynamic models – a gene regulatory network (GRN) model at a lower level, and a spiking neural network (SNN) model at a higher level to model the dynamic interaction between genes and spiking patterns of activity under certain conditions. The paper demonstrates that it is possible to model and trace over time the effect of a gene on the total spiking behavior of the SNN when the gene controls a parameter of a stochastic spiking neuron model used to build the SNN. Such CNGM can be potentially used to study neurodegenerative diseases or develop CNGM for cognitive robotics.


Gene Regulatory Network Spike Neural Network Spike Neuron Model Gene Regulatory Network Model Probabilistic Spike 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Nikola Kasabov
    • 1
    • 2
  • Stefan Schliebs
    • 1
  • Ammar Mohemmed
    • 1
  1. 1.KEDRIAuckland University of TechnologyNew Zealand
  2. 2.Institute for NeuroinformaticsETH and University of ZurichSwitzerland

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