A computational model of the respiratory network challenged and optimized by data from optogenetic manipulation of glycinergic neurons. (7th April 2017)

• Record Type: Journal Article
• Authors: Oku, Yoshitaka; Hülsmann, Swen
• Is Part Of: Neuroscience. Volume 347(2017)
• Page Start: 111
• Page End: 122
• Publication Date: 2017-04-07
• Subjects: Arch Archaerhodopsin -- BötC Bötzinger Complex -- preBötC pre-Bötzinger Complex -- rVRG rostral ventrolateral respiratory group; computational neuroscience -- breathing -- network topology -- inhibitory neurons; Neurochemistry -- Periodicals; Neurophysiology -- Periodicals; Neurology -- Periodicals; Neurochimie -- Périodiques; Neurophysiologie -- Périodiques; Neurochemistry; Neurophysiology; Electronic journals; Periodicals; Electronic journals; 612.8
• DOI: 10.1016/j.neuroscience.2017.01.041
• Languages: English
• ISSNs: 0306-4522

Abstract

Highlights: A neural mass model of consisting of five neuron populations is sufficient to explain recent experimental data. Modulation of inhibitory neurons can strongly modulate respiratory network activity. The model allows to make predictions for future optogenetic experiments. 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.