COMPUTATIONAL ASPECTS OF THE RESPIRATORY PATTERN GENERATOR

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.