J. B. Roldán, A. Cantudo, J. J. Torres, D. Maldonado, Yaqing Shen, Wenwen Zheng, Yue Yuan, M. Lanza
{"title":"Stochastic resonance in 2D materials based memristors","authors":"J. B. Roldán, A. Cantudo, J. J. Torres, D. Maldonado, Yaqing Shen, Wenwen Zheng, Yue Yuan, M. Lanza","doi":"10.1038/s41699-024-00444-1","DOIUrl":null,"url":null,"abstract":"Stochastic resonance is an essential phenomenon in neurobiology, it is connected to the constructive role of noise in the signals that take place in neuronal tissues, facilitating information communication, memory, etc. Memristive devices are known to be the cornerstone of hardware neuromorphic applications since they correctly mimic biological synapses in many different facets, such as short/long-term plasticity, spike-timing-dependent plasticity, pair-pulse facilitation, etc. Different types of neural networks can be built with circuit architectures based on memristive devices (mostly spiking neural networks and artificial neural networks). In this context, stochastic resonance is a critical issue to analyze in the memristive devices that will allow the fabrication of neuromorphic circuits. We do so here with h-BN based memristive devices from different perspectives. It is found that the devices we have fabricated and measured clearly show stochastic resonance behaviour. Consequently, neuromorphic applications can be developed to account for this effect, that describes a key issue in neurobiology with strong computational implications.","PeriodicalId":19227,"journal":{"name":"npj 2D Materials and Applications","volume":" ","pages":"1-6"},"PeriodicalIF":9.1000,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41699-024-00444-1.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"npj 2D Materials and Applications","FirstCategoryId":"88","ListUrlMain":"https://www.nature.com/articles/s41699-024-00444-1","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Stochastic resonance is an essential phenomenon in neurobiology, it is connected to the constructive role of noise in the signals that take place in neuronal tissues, facilitating information communication, memory, etc. Memristive devices are known to be the cornerstone of hardware neuromorphic applications since they correctly mimic biological synapses in many different facets, such as short/long-term plasticity, spike-timing-dependent plasticity, pair-pulse facilitation, etc. Different types of neural networks can be built with circuit architectures based on memristive devices (mostly spiking neural networks and artificial neural networks). In this context, stochastic resonance is a critical issue to analyze in the memristive devices that will allow the fabrication of neuromorphic circuits. We do so here with h-BN based memristive devices from different perspectives. It is found that the devices we have fabricated and measured clearly show stochastic resonance behaviour. Consequently, neuromorphic applications can be developed to account for this effect, that describes a key issue in neurobiology with strong computational implications.
期刊介绍:
npj 2D Materials and Applications publishes papers on the fundamental behavior, synthesis, properties and applications of existing and emerging 2D materials. By selecting papers with the potential for impact, the journal aims to facilitate the transfer of the research of 2D materials into wide-ranging applications.