Emergent central pattern generator behavior in chemical coupled two-compartment models with time delay

This paper proposes that modified two-compartment Pinsky-Rinzel (PR) neural model can be used to develop the simple form of central pattern generator (CPG). The CPG is called as 'half-central oscillator', which constructed by two inhibitory chemical coupled PR neurons with time delay. Some key properties of PR neural model related to CPG are studied and proved to meet the requirements of CPG. Using the simple CPG network, we first study the relationship between rhythmical output and key factors, including ambient noise, sensory feedback signals, morphological character of single neuron as well as the coupling delay time. We demonstrate that, appropriate intensity noise can enhance synchronization between two coupled neurons. Different output rhythm of CPG network can be entrained by sensory feedback signals. We also show that the morphology of single neuron has strong effect on the output rhythm. The phase synchronization indexes decrease with the increase of morphology parameter's difference. Through adjusting coupled delay time, we can get absolutely phase synchronization and antiphase state of CPG. Those results of simulation show the feasibility of PR neural model as a valid CPG as well as the emergent behaviors of the particularly CPG.