Examining phase response curve of nerve cell by using three different methods
Author(s) -
Hasan Eskalen,
Şükrü Özğan
Publication year - 2018
Publication title -
international journal of chemistry and technology
Language(s) - English
Resource type - Journals
ISSN - 2602-277X
DOI - 10.32571/ijct.338403
Subject(s) - phase response curve , phase response , oscillation (cell signaling) , biological system , perturbation (astronomy) , nerve cells , measure (data warehouse) , phase (matter) , computer science , mathematics , mathematical analysis , neuroscience , physics , chemistry , circadian rhythm , biology , circadian clock , quantum mechanics , biochemistry , database , microbiology and biotechnology
Rhythmic motion is observed in a variety of different field including physical, chemical and biological systems. Neural system, that consists of billions of neurons are also exhibited periodic motion. Phase Response Curves (PRCs); act like a bridge between, a single neuron and neural network; briefly measure change in period of oscillation by giving perturbation at different points of oscillation. PRCs can determined from measurements of electrical activities of neurons by experimental methods or theoretically derived from three different methods. As far as we know from the literature, these three different methods have never been used at the same time before. The main purpose of this computational study is to the obtain Phase Response Curve by three different methods and compare them in terms of simulation times and peak to baseline ratio. First, the kinds of excitability of neurons, the types of Phase Response Curve and peak to baseline ratio are mentioned. After then, these three different methods to obtain PRC are explained deeply. At a final step, Phase Response Curves are obtained from three theoretical methods and compared regarding to peak to baseline ratio, simulation time and applicability.
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