Computational neurogenetic modelling: gene networks within neural networks

dc.contributor.authorKasabov, N
dc.contributor.authorBenuskova, L.
dc.contributor.authorGomes Wysoski, S.
dc.date.accessioned2009-05-27T22:18:56Z
dc.date.available2009-05-27T22:18:56Z
dc.date.copyright2004
dc.date.created2004
dc.date.issued2004
dc.description.abstractThis 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.
dc.identifier.doi10.1109/IJCNN.2004.1380113
dc.identifier.urihttps://hdl.handle.net/10292/617
dc.publisherIEEE
dc.rights©2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
dc.rights.accessrightsOpenAccess
dc.source2004 IEEE International Joint Conference on Neural Networks, Budapest, Hungary, 2, 1203-1208
dc.titleComputational neurogenetic modelling: gene networks within neural networks
dc.typeConference Proceedings
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