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Phenomenological models of Na(V)1.5. A side by side, procedural, hands-on comparison between Hodgkin-Huxley and kinetic formalisms
Univ Naples Federico II, Dept Elect Engn & Informat Technol DIETI, Naples, Italy.;Ist Clin Sci Maugeri IRCCS, Dept Bioengn, Telese Terme Inst, Telese Terme, BN, Italy..
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Computational Science and Technology (CST).
Ist Clin Sci Maugeri IRCCS, Dept Bioengn, Telese Terme Inst, Telese Terme, BN, Italy..
Univ Naples Federico II, Dept Elect Engn & Informat Technol DIETI, Naples, Italy.;Ist Clin Sci Maugeri IRCCS, Dept Bioengn, Telese Terme Inst, Telese Terme, BN, Italy..
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2019 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 9, article id 17493Article in journal (Refereed) Published
Abstract [en]

Computational models of ion channels represent the building blocks of conductance-based, biologically inspired models of neurons and neural networks. Ion channels are still widely modelled by means of the formalism developed by the seminal work of Hodgkin and Huxley (HH), although the electrophysiological features of the channels are currently known to be better fitted by means of kinetic Markov-type models. The present study is aimed at showing why simplified Markov-type kinetic models are more suitable for ion channels modelling as compared to HH ones, and how a manual optimization process can be rationally carried out for both. Previously published experimental data of an illustrative ion channel (Na(V)1.5) are exploited to develop a step by step optimization of the two models in close comparison. A conflicting practical limitation is recognized for the HH model, which only supplies one parameter to model two distinct electrophysiological behaviours. In addition, a step by step procedure is provided to correctly optimize the kinetic Markov-type model. Simplified Markov-type kinetic models are currently the best option to closely approximate the known complexity of the macroscopic currents of ion channels. Their optimization can be achieved through a rationally guided procedure, and allows to obtain models with a computational burden that is comparable with HH models one.

Place, publisher, year, edition, pages
Nature Publishing Group, 2019. Vol. 9, article id 17493
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Other Engineering and Technologies
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URN: urn:nbn:se:kth:diva-265482DOI: 10.1038/s41598-019-53662-9ISI: 000498517600001PubMedID: 31767896Scopus ID: 2-s2.0-85075547366OAI: oai:DiVA.org:kth-265482DiVA, id: diva2:1379981
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QC 20191218

Available from: 2019-12-18 Created: 2019-12-18 Last updated: 2020-01-09Bibliographically approved

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