To help evaluate the hypothesis that the central respiratory rhythm is
generated by a network of interacting neurons, a network model of res
piratory rhythmogenesis is formulated and examined computationally. Th
e neural elements of the network are driven by tonic inputs and genera
te a continuous variable representing firing rate. Each neural element
in the model can be described by an activation time constant, an adap
tation time constant, and a step nonlinearity. Initial network connect
ivity was based on an earlier proposed model of the central respirator
y pattern generator. These connections were adjusted interactively unt
il the model trajectories resembled those observed electrophysiologica
lly. The properties of the resulting network were examined computation
ally by simulation, determination of the phase resetting behavior of t
he network oscillator, and examination of the localized eigenstructure
of the network. These results demonstrate that the network model can
account for a number of diverse physiological observations, and, thus,
support the network hypothesis of respiratory rhymogenesis.