New computational models of the respiratory oscillator in mammals

Abstract

Understanding how respiratory oscillations are generated and controlled in the mammalian brainstem requires synthesis of neural function at cellular, synaptic, and network levels. Modeling the respiratory network has entered a new era where simulations incorporating complex cellular properties and network interactions exhibited by respiratory neurons are possible. Given the complexity and unknowns of the real system, there are obvious limitations of the modeling in its present form. Nevertheless, if we are to produce neurobiologically satisfying, mechanistic explanations that synthesize cellular and network phenomena, the modeling approach outlined here should have distinct advantages. The approach allows a close interaction between experimental and computational studies, and will enable simulations with increasing neurobiological realism as additional experimental data becomes available. The modeling summarized here represents the initial stages of establishing a computational framework for storing information about neuron and network properties, and for exploring complex dynamical properties in ways not possible experimentally.