CNN with chaotic elements for modelling biological functions

The patterns with visible spatial regularity emerging from cooperation of a large number of chaotic dynamic elements are referred to as self-organization. In this paper we propose to use cellular neural network (CNN) with chaotic neurons having spatial irregularities as possible models of dynamics of biological functions. Two kinds of inhomogeneous structures are analysed: defects introduced by cutting off connections in some cells in one row with the neighboring rows; and spatial defects obtained by removing the cells positioned in some small area within the network. We confirm that such irregularities in some cases can cause target waves to lose their circular regularity and give rise to spiral waves-similar to those observed in abnormal operation of cardiac tissue. Another type of phenomena observed is the robustness of the spatial memory effect on the removal of cells in the network which could serve as model of some types of biological tissues where functionality is maintained despite of the fact that some of the cells die or are removed from the tissue.