Dynamical analysis of neural oscillators in an olfactory cortex model
This paper presents a theoretical approach to understand the basic dynamics of a hierarchical and realistic computational model of the olfactory system proposed by W. J. Freeman. While the system's parameter space could be scanned to obtain the desired dynamical behavior, our approach exploits the hierarchical organization and focuses on understanding the simplest building block of this highly connected network. Based on bifurcation analysis, we obtain analytical solutions of how to control the qualitative behavior of a reduced KII set taking into consideration both the internal coupling coefficients and the external stimulus. This also provides useful insights for investigating higher level structures that are composed of the same basic structure. Experimental results are presented to verify our theoretical analysis.