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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Modelling the Effect of Genes on the Dynamics of Probabilistic Spiking Neural Networks for Computational Neurogenetic Modelling
verfasst von : Nikola Kasabov, Stefan Schliebs, Ammar Mohemmed
Erschienen in: Computational Intelligence Methods for Bioinformatics and Biostatistics
Verlag: Springer Berlin Heidelberg
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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.