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Computational Intelligence Methods for Bioinformatics and Biostatistics

Volume 7548 of the series Lecture Notes in Computer Science pp 1-9

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

  • Nikola KasabovAffiliated withKEDRI, Auckland University of TechnologyInstitute for Neuroinformatics, ETH and University of Zurich
  • , Stefan SchliebsAffiliated withKEDRI, Auckland University of Technology
  • , Ammar MohemmedAffiliated withKEDRI, Auckland University of Technology

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Abstract

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.