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A computational model of the respiratory network challenged and optimized by data from optogenetic manipulation of
Yoshitaka Oku1, Swen Hülsmann2
1Department of Physiology, Hyogo College of Medicine, Nishinomiya, Hyogo 663-8501, Japan.
Abstract:
The topology of the respiratory network in the brainstem has been addressed using different computational models, which help to understand the functional properties of the system. We tested a neural mass model by comparing the result of activation and inhibition of inhibitory neurons in silico with recently published results of optogenetic manipulation of glycinergic neurons [Sherman, et al. (2015) Nat Neurosci 18:408]. The comparison revealed that a five-cell type model consisting of three classes of inhibitory neurons [I-DEC, E-AUG, E-DEC (PI)] and two excitatory populations (pre-I/I) and (I-AUG) neurons can be applied to explain experimental observations made by stimulating or inhibiting inhibitory neurons by light sensitive ion channels.
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