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
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