Analysis of the electronic integrate and fire neuron model
dc.authorid | isik, ibrahim/0000-0003-1355-9420 | |
dc.authorwosid | isik, ibrahim/AAG-5915-2019 | |
dc.contributor.author | Isik, Ibrahim | |
dc.contributor.author | Tagluk, Mehmet Emin | |
dc.date.accessioned | 2024-08-04T20:51:45Z | |
dc.date.available | 2024-08-04T20:51:45Z | |
dc.date.issued | 2022 | |
dc.department | İnönü Üniversitesi | en_US |
dc.description.abstract | Nano-scale devices are thought to intervene in natural life for a variety of responsibilities. For understanding the intrinsic communication of such nano-scale devices, software and hardware modalities have been introduced. Some of these models are of neuro-spike communication systems which employ spiking neuron circuits. In this study, the previously designed electronic integrate and fire circuit inspired by Hodgkin Huxley membrane model is analyzed and interrelated to the Izhikevich's systematic integrate and fire model. The generated action potentials with this model are very similar to the ones generated by real biophysical neurons which are thought as the inter-neuronal ionic transporters of information. The superiority of the analyzed model to the existing models is that it can show pulse trains whose characteristics are almost similar to those produced by nerve cells. The analytical, hardware and simulation results have shown that the model has the potential of employment in the smart nano-scale systems and medical treatment strategies. (c) 2022 Elsevier B.V. All rights reserved. | en_US |
dc.description.sponsorship | Inonu University Scientifics Researchers Project Department (BAP) [FDK-2019-1359] | en_US |
dc.description.sponsorship | Acknowledgments This study is supported by the Inonu University Scientifics Researchers Project Department (BAP) under project ID: FDK-2019-1359. We thank to HP Turkey section for providing a power-ful computer for computational tasks in this study. | en_US |
dc.identifier.doi | 10.1016/j.neucom.2022.02.064 | |
dc.identifier.endpage | 270 | en_US |
dc.identifier.issn | 0925-2312 | |
dc.identifier.issn | 1872-8286 | |
dc.identifier.scopus | 2-s2.0-85125910632 | en_US |
dc.identifier.scopusquality | Q1 | en_US |
dc.identifier.startpage | 261 | en_US |
dc.identifier.uri | https://doi.org/10.1016/j.neucom.2022.02.064 | |
dc.identifier.uri | https://hdl.handle.net/11616/100519 | |
dc.identifier.volume | 488 | en_US |
dc.identifier.wos | WOS:000789677800004 | en_US |
dc.identifier.wosquality | Q2 | en_US |
dc.indekslendigikaynak | Web of Science | en_US |
dc.indekslendigikaynak | Scopus | en_US |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.relation.ispartof | Neurocomputing | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Neuron | en_US |
dc.subject | Bipolar junction transistor | en_US |
dc.subject | Unipolar junction transistor | en_US |
dc.subject | Neuronal communication | en_US |
dc.title | Analysis of the electronic integrate and fire neuron model | en_US |
dc.type | Article | en_US |