• DocumentCode
    2311160
  • Title

    Computational neurogenetic modelling: gene networks within neural networks

  • Author

    Kasabov, Nikola ; Benuskova, Lubica ; Wysoski, Sirnei Gomes

  • Author_Institution
    Knowledge Eng. & Discovery Res. Inst., Auckland Univ. of Technol., New Zealand
  • Volume
    2
  • fYear
    2004
  • fDate
    25-29 July 2004
  • Firstpage
    1203
  • Abstract
    This paper introduces a novel connectionist approach to neural network modelling that integrates dynamic gene networks within neurons with a neural network model. Interaction of genes in neurons affects the dynamics of the whole neural network. Through tuning the gene interaction network and the initial gene/protein expression values, different states of the neural network operation 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 (SNN). Functioning of the SNN can be evaluated for instance by the field potentials, thus making it possible to attempt modelling the role of genes in different brain states such as epilepsy, schizophrenia, and other states, where EEG data is available to test the model predictions.
  • Keywords
    brain; electroencephalography; genetics; neural nets; proteins; EEG data; brain states; dynamic gene networks; epilepsy state; gene interaction network; generic computational neurogenetic model; neural network modelling; neural network operation; protein expression values; schizophrenia state; spiking neural network; Biological neural networks; Brain modeling; Computational modeling; Computer networks; Electroencephalography; Epilepsy; Neural networks; Neurons; Predictive models; Proteins;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-8359-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2004.1380113
  • Filename
    1380113