Abstract
Neural networks control complex motor outputs by generating several rhythmic neuronal activities, often with different time scales. One example of such a network is the preBötzinger complex respiratory network (preBötC) that can simultaneously generate fast, small amplitude, mono-phasic eupneic breaths together with slow, high-amplitude, bi-phasic augmented breaths (sighs). However, the underlying rhythmogenic mechanisms for this bimodal discharge pattern remain unclear, leaving two possible explanations: the existence of either reconfiguring processes within the same network or two distinct subnetworks. Based on recent in vitro data obtained in the mouse embryo we have built a computational model consisting of two compartments, interconnected through appropriate synapses. One compartment generates sighs and the other produces eupneic bursts. The model reproduces basic features of simultaneous sigh and eupnea generation (two types of bursts differing in terms of shape, amplitude and frequency of occurrence) and mimics the effect of blocking glycinergic synapses. Furthermore, we used this model to make predictions that were subsequently tested on the isolated preBötC in mouse brainstem slice preparations. Through a combination of in vitro and in silico approaches we find that 1) sigh events are less sensitive to network excitability than eupneic activity, 2) calcium-dependent mechanisms and the current play a prominent role in sigh generation, and 3) specific parameters of activation set the low sensitivity to excitability in the sigh neuronal subset. Altogether, our results strongly support the hypothesis that distinct subpopulations within the preBötC network are responsible for sigh and eupnea rhythmogenesis.
Significance Statement: How a single neural network can generate several rhythmic activities at different time scales remains an open question. Here, in addition to the already described reconfiguring process, we propose a new mechanism by which the respiratory network can generate simultaneously two distinct inspiration-related activities (eupnea and sigh) at different frequencies. By combining physiological recordings of fictive inspiratory activities in vitro with computational modeling, we test the possibility that eupnea and sigh rhythmogenesis rely on the interaction between two distinct subpopulations within the respiratory network. Our in silico and in vitro results provide evidence supporting this hypothesis and thus bring new insights regarding possible mechanisms allowing one network to generate rhythmic activities differing in terms of frequencies of occurrence.
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