Cognitive Neurodynamics

, 2:319 | Cite as

Modeling brain dynamics using computational neurogenetic approach

  • Lubica BenuskovaEmail author
  • Nikola Kasabov
Research Article


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.


Computational neurogenetic modeling Gene regulatory networks Neuroinformatics Gene expression data Local field potential 



The paper is supported by the Knowledge Engineering and Discovery Research Institute KEDRI (, Auckland University of Technology and the FRST funded grant AUTX02001 (2002–2007). We would like to thank Simei Gomes Wysoski for implementing the CNGM simulator. Alessandro E. P. Villa is gratefully acknowledged for discussions on brain experimental data gathering and processing.


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Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of Otago, 90 Union Place EastDunedinNew Zealand
  2. 2.Knowledge Engineering and Discovery Research InstituteAuckland University of TechnologyPenrose, AucklandNew Zealand

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