COMBINED EFFECTS OF PARAMETER HETEROGENEITY AND NOISE ON SPATIAL COHERENCE IN MAP-BASED NEURONS

Abstract

We herein present a numerical investigation of the combined effects of parameter heterogeneity and noise, which are unavoidable in excitable medium, on spatial coherence in map-based neurons. Our results show that, the neurons' spatial coherence can be improved by changing parameter heterogeneity (or noise intensity) in the condition that the control parameter is below the threshold and noise intensity (or parameter heterogeneity) is small. Interestingly, there exists an optimal parameter heterogeneity (or noise intensity) at which the neurons' spatial coherence is maximized. However, when the control parameter is above the threshold, the system's spatial coherence cannot be enhanced by parameter heterogeneity (or noise). The underlying mechanism of these effects is discussed in terms of the neuron's bifurcation and the coupling interaction between the neurons.