{"title":"Synapse dynamics in CMOS derived from a model of neurotransmitter release","authors":"M. Noack, C. Mayr, J. Partzsch, R. Schüffny","doi":"10.1109/ECCTD.2011.6043316","DOIUrl":null,"url":null,"abstract":"Neuromorphic realizations of the short-term dynamics at a synapse often use simplistic circuit models. In this paper, we present a more biologically realistic VLSI implementation of these mechanisms. Our circuit approach is analytically derived from a model of neurotransmitter release, so that it can be directly related to simulation results and biological measurements. We present a reduced implementation of this approach that is highly configurable, allowing for an individual adjustment of all model parameters. Furthermore, it achieves a high robustness against process variations and successfully reproduces biological paired-pulse depression experiments.","PeriodicalId":126960,"journal":{"name":"2011 20th European Conference on Circuit Theory and Design (ECCTD)","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 20th European Conference on Circuit Theory and Design (ECCTD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECCTD.2011.6043316","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
Neuromorphic realizations of the short-term dynamics at a synapse often use simplistic circuit models. In this paper, we present a more biologically realistic VLSI implementation of these mechanisms. Our circuit approach is analytically derived from a model of neurotransmitter release, so that it can be directly related to simulation results and biological measurements. We present a reduced implementation of this approach that is highly configurable, allowing for an individual adjustment of all model parameters. Furthermore, it achieves a high robustness against process variations and successfully reproduces biological paired-pulse depression experiments.