Options
A COMPUTATIONAL MODEL OF THE RESPIRATORY NETWORK CHALLENGED AND OPTIMIZED BY DATA FROM OPTOGENETIC MANIPULATION OF GLYCINERGIC NEURONS
ISSN
1873-7544
0306-4522
Date Issued
2017
Author(s)
Oku, Yoshitaka
DOI
10.1016/j.neuroscience.2017.01.041
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/1) and (I-AUG) neurons can be applied to explain experimental observations made by stimulating or inhibiting inhibitory neurons by light sensitive ion channels. (C) 2017 IBRO. Published by Elsevier Ltd. All rights reserved.