{"title":"通过设计脉冲神经元模型对不同神经元行为进行分类","authors":"A. Kumar, S. Kansal, M. Hanmandlu","doi":"10.1109/ICE-CCN.2013.6528592","DOIUrl":null,"url":null,"abstract":"We have presented a simple two equation model which produces the rich behavior of biological neurons, including tonic spiking, tonic bursting, mixed mode firing, spike frequency adaptation, resonator, integrator etc. Our model is capable of producing 19 different kinds of dynamics of real biological neuron. We have illustrated the richness and complexity of spiking behavior of individual neuron in response to simple pulses of dc current.","PeriodicalId":286830,"journal":{"name":"2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Classification of different neuron behavior by designing spiking neuron model\",\"authors\":\"A. Kumar, S. Kansal, M. Hanmandlu\",\"doi\":\"10.1109/ICE-CCN.2013.6528592\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We have presented a simple two equation model which produces the rich behavior of biological neurons, including tonic spiking, tonic bursting, mixed mode firing, spike frequency adaptation, resonator, integrator etc. Our model is capable of producing 19 different kinds of dynamics of real biological neuron. We have illustrated the richness and complexity of spiking behavior of individual neuron in response to simple pulses of dc current.\",\"PeriodicalId\":286830,\"journal\":{\"name\":\"2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN)\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-03-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICE-CCN.2013.6528592\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICE-CCN.2013.6528592","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Classification of different neuron behavior by designing spiking neuron model
We have presented a simple two equation model which produces the rich behavior of biological neurons, including tonic spiking, tonic bursting, mixed mode firing, spike frequency adaptation, resonator, integrator etc. Our model is capable of producing 19 different kinds of dynamics of real biological neuron. We have illustrated the richness and complexity of spiking behavior of individual neuron in response to simple pulses of dc current.
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