Faculty Information |
|
Article types | Original article |
Language | English |
Refereed paper | Refereed |
Title | A computational model of the respiratory network challenged and optimized by data from optogenetic manipulation of glycinergic neurons. |
Journal | Formal name:Neuroscience Abbreviation:Neuroscience ISSN code:1873754403064522 |
Domestic / Foregin | Foregin |
Volume, Number, Page | 347,pp.111-122 |
Papers・Author | Oku Yoshitaka, Hülsmann Swen |
Publication date | 2017/04 |
Papers・Description | 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. |
DOI | 10.1016/j.neuroscience.2017.01.041 |
PMID | 28215988 |