Simulating Synaptic Behaviors through Frequency Modulation in a Capacitor-Memristor Circuit.

Hebbian-like learning mechanism LTD LTP memristors synaptic plasticity

Journal

Micromachines
ISSN: 2072-666X
Titre abrégé: Micromachines (Basel)
Pays: Switzerland
ID NLM: 101640903

Informations de publication

Date de publication:
29 Oct 2023
Historique:
received: 29 09 2023
revised: 20 10 2023
accepted: 27 10 2023
medline: 25 11 2023
pubmed: 25 11 2023
entrez: 25 11 2023
Statut: epublish

Résumé

Memristors, known for their adjustable and non-volatile resistance, offer a promising avenue for emulating synapses. However, achieving pulse frequency-dependent synaptic plasticity in memristors or memristive systems necessitates further exploration. In this study, we present a novel approach to modulate the conductance of a memristor in a capacitor-memristor circuit by finely tuning the frequency of input pulses. Our experimental results demonstrate that these phenomena align with the long-term depression (LTD) and long-term potentiation (LTP) observed in synapses, which are induced by the frequency of action potentials. Additionally, we successfully implement a Hebbian-like learning mechanism in a simple circuit that connects a pair of memristors to a capacitor, resulting in observed associative memory formation and forgetting processes. Our findings highlight the potential of capacitor-memristor circuits in faithfully replicating the frequency-dependent behavior of synapses, thereby offering a valuable contribution to the development of brain-inspired neural networks.

Identifiants

pubmed: 38004871
pii: mi14112014
doi: 10.3390/mi14112014
pmc: PMC10673497
pii:
doi:

Types de publication

Journal Article

Langues

eng

Références

Annu Rev Neurosci. 2001;24:139-66
pubmed: 11283308
Micromachines (Basel). 2023 Jan 17;14(2):
pubmed: 36837935
Nanotechnology. 2012 Jun 1;23(21):215202
pubmed: 22551985
Proc Natl Acad Sci U S A. 1992 May 15;89(10):4363-7
pubmed: 1350090
Nano Lett. 2010 Apr 14;10(4):1297-301
pubmed: 20192230
Micromachines (Basel). 2022 Oct 15;13(10):
pubmed: 36296097
IEEE Trans Biomed Circuits Syst. 2022 Oct;16(5):926-938
pubmed: 36070275
Adv Mater. 2018 Mar;30(12):e1706717
pubmed: 29399893
Annu Rev Neurosci. 2000;23:649-711
pubmed: 10845078
Nano Lett. 2015 Mar 11;15(3):2203-11
pubmed: 25710872
IEEE Trans Cybern. 2020 Jul;50(7):2935-2945
pubmed: 31751264
Nature. 2008 May 1;453(7191):80-3
pubmed: 18451858
IEEE Trans Cybern. 2023 May;53(5):3351-3362
pubmed: 36129863
Sci Rep. 2013;3:1680
pubmed: 23604263
Nat Mater. 2017 Jan;16(1):101-108
pubmed: 27669052
Neural Netw. 2010 Sep;23(7):881-6
pubmed: 20605401
Nat Commun. 2018 Aug 10;9(1):3208
pubmed: 30097585
Nat Commun. 2020 Aug 25;11(1):4234
pubmed: 32843643
Nanotechnology. 2011 Jun 24;22(25):254022
pubmed: 21572207
ACS Nano. 2014 Mar 25;8(3):2369-76
pubmed: 24571386

Auteurs

Kuibo Yin (K)

SEU-FEI Nano-Pico Center, Key Laboratory of MEMS of Ministry of Education, Southeast University, Nanjing 210096, China.

Jingcang Li (J)

SEU-FEI Nano-Pico Center, Key Laboratory of MEMS of Ministry of Education, Southeast University, Nanjing 210096, China.

Yuwei Xiong (Y)

SEU-FEI Nano-Pico Center, Key Laboratory of MEMS of Ministry of Education, Southeast University, Nanjing 210096, China.

Mingyun Zhu (M)

SEU-FEI Nano-Pico Center, Key Laboratory of MEMS of Ministry of Education, Southeast University, Nanjing 210096, China.

Zhiyuan Tan (Z)

SEU-FEI Nano-Pico Center, Key Laboratory of MEMS of Ministry of Education, Southeast University, Nanjing 210096, China.

Zhanrui Jin (Z)

SEU-FEI Nano-Pico Center, Key Laboratory of MEMS of Ministry of Education, Southeast University, Nanjing 210096, China.

Classifications MeSH