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Neural network model of an amphibian ventilatory central pattern generator

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Abstract

The neuronal multiunit model presented here is a formal model of the central pattern generator (CPG) of the amphibian ventilatory neural network, inspired by experimental data from Pelophylax ridibundus. The kernel of the CPG consists of three pacemakers and two follower neurons (buccal and lung respectively). This kernel is connected to a chain of excitatory and inhibitory neurons organized in loops. Simulations are performed with Izhikevich-type neurons. When driven by the buccal follower, the excitatory neurons transmit and reorganize the follower activity pattern along the chain, and when driven by the lung follower, the excitatory and inhibitory neurons of the chain fire in synchrony. The additive effects of synaptic inputs from the pacemakers on the buccal follower account for (1) the low frequency buccal rhythm, (2) the intra-burst high frequency oscillations, and (3) the episodic lung activity. Chemosensitivity to acidosis is implemented by an increase in the firing frequency of one of the pacemakers. This frequency increase leads to both a decrease in the buccal burst frequency and an increase in the lung episode frequency. The rhythmogenic properties of the model are robust against synaptic noise and pacemaker jitter. To validate the rhythm and pattern genesis of this formal CPG, neurograms were built from simulated motoneuron activity, and compared with experimental neurograms. The basic principles of our model account for several experimental observations, and we suggest that these principles may be generic for amphibian ventilation.

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Acknowledgments

We thank Jeremy Cabessa for his critical reading of the paper and Douglas Carnall for his help with English style.

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Authors and Affiliations

  1. Équipe de Statistique Appliquée, ESPCI-Paris, PSL Research University, F-75005, Paris, France

    Ginette Horcholle-Bossavit & Brigitte Quenet

  2. Neurophysiologie respiratoire expérimentale et clinique, INSERM, UMRS1158, Sorbonne Université, F-75005, Paris, France

    Ginette Horcholle-Bossavit & Brigitte Quenet

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  1. Ginette Horcholle-Bossavit
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Correspondence to Brigitte Quenet.

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Horcholle-Bossavit, G., Quenet, B. Neural network model of an amphibian ventilatory central pattern generator. J Comput Neurosci 46, 299–320 (2019). https://doi.org/10.1007/s10827-019-00718-4

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