Abstract
The paper introduces a novel computational approach to brain dynamics modeling that integrates dynamic gene-protein regulatory networks with a neural network model. Interaction of genes and proteins in neurons affects the dynamics of the whole neural network. Through tuning the gene-protein interaction network and the initial gene/protein expression values, different states of the neural network dynamics can be achieved. A generic computational neurogenetic model is introduced that implements this approach. It is illustrated by means of a simple neurogenetic model of a spiking neural network of the generation of local field potential. Our approach allows for investigation of how deleted or mutated genes can alter the dynamics of a model neural network. We conclude with the proposal how to extend this approach to model cognitive neurodynamics. © 2008 Springer Science+Business Media B.V.
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Benuskova, L., & Kasabov, N. (2008). Modeling brain dynamics using computational neurogenetic approach. Cognitive Neurodynamics, 2(4), 319–334. https://doi.org/10.1007/s11571-008-9061-1
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