{"title":"神经元尖峰模型的Fokker-Planck解","authors":"Derek J. Daniel","doi":"10.1080/00411450903404820","DOIUrl":null,"url":null,"abstract":"The stochastic dynamics of a neuronal spiking model in neuroscience, when viewed as a large simulated network, are known to reduce to the classic problem of solving the Fokker-Planck equation, or the equivalent Kolmogorov differential equation in probability theory, for the numerical evaluation of the statistical properties of neurons as a random injection of ion currents. The problem here, however, is that the initial condition for the Fokker-Planck equation is a Dirac delta function so the actual implementation of Delta functions that at the same time can attain numerical stability can become problematic in computational neuroscience. Therefore, in this brief communication, a computational method for implementing such an initial condition is suggested, which itself has led to an exact solution for this problem.","PeriodicalId":49420,"journal":{"name":"Transport Theory and Statistical Physics","volume":"38 1","pages":"383 - 391"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/00411450903404820","citationCount":"0","resultStr":"{\"title\":\"Fokker-Planck Solution for a Neuronal Spiking Model\",\"authors\":\"Derek J. Daniel\",\"doi\":\"10.1080/00411450903404820\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The stochastic dynamics of a neuronal spiking model in neuroscience, when viewed as a large simulated network, are known to reduce to the classic problem of solving the Fokker-Planck equation, or the equivalent Kolmogorov differential equation in probability theory, for the numerical evaluation of the statistical properties of neurons as a random injection of ion currents. The problem here, however, is that the initial condition for the Fokker-Planck equation is a Dirac delta function so the actual implementation of Delta functions that at the same time can attain numerical stability can become problematic in computational neuroscience. Therefore, in this brief communication, a computational method for implementing such an initial condition is suggested, which itself has led to an exact solution for this problem.\",\"PeriodicalId\":49420,\"journal\":{\"name\":\"Transport Theory and Statistical Physics\",\"volume\":\"38 1\",\"pages\":\"383 - 391\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/00411450903404820\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transport Theory and Statistical Physics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/00411450903404820\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transport Theory and Statistical Physics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/00411450903404820","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fokker-Planck Solution for a Neuronal Spiking Model
The stochastic dynamics of a neuronal spiking model in neuroscience, when viewed as a large simulated network, are known to reduce to the classic problem of solving the Fokker-Planck equation, or the equivalent Kolmogorov differential equation in probability theory, for the numerical evaluation of the statistical properties of neurons as a random injection of ion currents. The problem here, however, is that the initial condition for the Fokker-Planck equation is a Dirac delta function so the actual implementation of Delta functions that at the same time can attain numerical stability can become problematic in computational neuroscience. Therefore, in this brief communication, a computational method for implementing such an initial condition is suggested, which itself has led to an exact solution for this problem.