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. 2022 Dec 2;13:7432. doi: 10.1038/s41467-022-35160-1

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© The Author(s) 2022

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 2 — a Schematic of biological synapse, which could be emulated by artificial synapses with short-term and long-term plasticity. b Schematic of switching mechanism for short-term memory (STM) and long-term memory (LTM) in artificial synapse. Excitatory post-synaptic current (EPSC) could be inspired by electrical pulse applied to device. c Nonvolatile resistive switching curves with compliance current (CC) of 100 μA and 1 mA. d EPSC behaviors of artificial synapse under different electrical pulse amplitudes, including 1.5, 2, 2.5, 3, and 3.5 V. e Device transition from STM to LTM as a result of enhanced pulse amplitude, extracted from panel d. f Paired pulse facilitation (PPF) and paired pulse depression (PPD) characteristics generated by a pair of pulses with an interval of 1 s. g Real-time program and storage for letters of “L”, “T” and “M” based on synaptic weights of memristor array. h, i Long-term potentiation (LTP) and long-term depression (LTD) curves of artificial synapses with multi-level storage states, respectively.