Neural model of frog ventilatory rhythmogenesis

Abstract In the adult frog respiratory system, periods of rhythmic movements of the buccal floor are interspersed by lung ventilation episodes. The ventilatory activity results from the interaction of two hypothesized oscillators in the brainstem. Here, we model these oscillators with two coupled neural networks, whose co-activation results in the emergence of new dynamics. One of the networks is built with “loop chains” of excitatory and inhibitory neurones producing periodic activities. We define two groups of excitatory neurones whose oscillatory antiphasic sums of activities represent output signals as possible motor commands towards antagonist buccal muscles. The other oscillator is a small network with a self-modulated excitatory input to an excitatory neurone whose episodic firings synchronise some neurones of the first network chains. When this oscillator is silent, the output signals exhibit only regular oscillations, and, when active, the synchronisation process reconfigures the output signals whose new features are representative of lung ventilation motor patterns. The biological interest of this formal model is illustrated by the persistence of the relevant dynamical features when perturbations are introduced in the model, i.e. dynamic noises and architecture modifications. The implementation of the networks with clock-driven continuous time neurones provides simulations with physiological time scales.