Cargando…

Voltage–Time Transformation Model for Threshold Switching Spiking Neuron Based on Nucleation Theory

In this study, we constructed a voltage–time transformation model (V–t Model) to predict and simulate the spiking behavior of threshold-switching selector-based neurons (TS neurons). The V–t Model combines the physical nucleation theory and the resistor–capacitor (RC) equivalent circuit and successf...

Descripción completa

Detalles Bibliográficos
Autores principales: Yap, Suk-Min, Wang, I-Ting, Wu, Ming-Hung, Hou, Tuo-Hung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9043246/
https://www.ncbi.nlm.nih.gov/pubmed/35495030
http://dx.doi.org/10.3389/fnins.2022.868671
_version_ 1784694832708452352
author Yap, Suk-Min
Wang, I-Ting
Wu, Ming-Hung
Hou, Tuo-Hung
author_facet Yap, Suk-Min
Wang, I-Ting
Wu, Ming-Hung
Hou, Tuo-Hung
author_sort Yap, Suk-Min
collection PubMed
description In this study, we constructed a voltage–time transformation model (V–t Model) to predict and simulate the spiking behavior of threshold-switching selector-based neurons (TS neurons). The V–t Model combines the physical nucleation theory and the resistor–capacitor (RC) equivalent circuit and successfully depicts the history-dependent threshold voltage of TS selectors, which has not yet been modeled in TS neurons. Moreover, based on our model, we analyzed the currently reported TS devices, including ovonic threshold switching (OTS), insulator-metal transition, and silver- (Ag-) based selectors, and compared the behaviors of the predicted neurons. The results suggest that the OTS neuron is the most promising and potentially achieves the highest spike frequency of GHz and the lowest operating voltage and area overhead. The proposed V–t Model provides an engineering pathway toward the future development of TS neurons for neuromorphic computing applications.
format Online
Article
Text
id pubmed-9043246
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-90432462022-04-28 Voltage–Time Transformation Model for Threshold Switching Spiking Neuron Based on Nucleation Theory Yap, Suk-Min Wang, I-Ting Wu, Ming-Hung Hou, Tuo-Hung Front Neurosci Neuroscience In this study, we constructed a voltage–time transformation model (V–t Model) to predict and simulate the spiking behavior of threshold-switching selector-based neurons (TS neurons). The V–t Model combines the physical nucleation theory and the resistor–capacitor (RC) equivalent circuit and successfully depicts the history-dependent threshold voltage of TS selectors, which has not yet been modeled in TS neurons. Moreover, based on our model, we analyzed the currently reported TS devices, including ovonic threshold switching (OTS), insulator-metal transition, and silver- (Ag-) based selectors, and compared the behaviors of the predicted neurons. The results suggest that the OTS neuron is the most promising and potentially achieves the highest spike frequency of GHz and the lowest operating voltage and area overhead. The proposed V–t Model provides an engineering pathway toward the future development of TS neurons for neuromorphic computing applications. Frontiers Media S.A. 2022-04-13 /pmc/articles/PMC9043246/ /pubmed/35495030 http://dx.doi.org/10.3389/fnins.2022.868671 Text en Copyright © 2022 Yap, Wang, Wu and Hou. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Yap, Suk-Min
Wang, I-Ting
Wu, Ming-Hung
Hou, Tuo-Hung
Voltage–Time Transformation Model for Threshold Switching Spiking Neuron Based on Nucleation Theory
title Voltage–Time Transformation Model for Threshold Switching Spiking Neuron Based on Nucleation Theory
title_full Voltage–Time Transformation Model for Threshold Switching Spiking Neuron Based on Nucleation Theory
title_fullStr Voltage–Time Transformation Model for Threshold Switching Spiking Neuron Based on Nucleation Theory
title_full_unstemmed Voltage–Time Transformation Model for Threshold Switching Spiking Neuron Based on Nucleation Theory
title_short Voltage–Time Transformation Model for Threshold Switching Spiking Neuron Based on Nucleation Theory
title_sort voltage–time transformation model for threshold switching spiking neuron based on nucleation theory
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9043246/
https://www.ncbi.nlm.nih.gov/pubmed/35495030
http://dx.doi.org/10.3389/fnins.2022.868671
work_keys_str_mv AT yapsukmin voltagetimetransformationmodelforthresholdswitchingspikingneuronbasedonnucleationtheory
AT wangiting voltagetimetransformationmodelforthresholdswitchingspikingneuronbasedonnucleationtheory
AT wuminghung voltagetimetransformationmodelforthresholdswitchingspikingneuronbasedonnucleationtheory
AT houtuohung voltagetimetransformationmodelforthresholdswitchingspikingneuronbasedonnucleationtheory