教員業績データベース |
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論文種別 | 原著 |
言語種別 | 英語 |
査読の有無 | 査読あり |
表題 | A computational model of the respiratory network challenged and optimized by data from optogenetic manipulation of glycinergic neurons. |
掲載誌名 | 正式名:Neuroscience 略 称:Neuroscience ISSNコード:1873754403064522 |
掲載区分 | 国外 |
巻・号・頁 | 347,pp.111-122 |
著者・共著者 | Oku Yoshitaka, Hülsmann Swen |
発行年月 | 2017/04 |
概要 | 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 |