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
Link To Document :
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