Inference for integrate-and-fire neuron models

来源 :上海交通大学 | 被引量 : 0次 | 上传用户：a263537545

【摘要】

：

【作者】

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Satish Iyengar

【机构】

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Statistics Department,University of Pittsburgh,Pittsburgh,PA,15260 USA

【出处】

：

上海交通大学

【发表日期】

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2016年4期

【关键词】

：

Diffusion First-passage time Laplace transform Maximum likelihood

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　　Stochastic models of neural activity are a well developed application in biology.Diffusion models for integrate-and-fire(I-F)neurons hold a prominent place because of the many synaptic inputs to a neuron,and because these models arise out of noisy versions of differential equations for the neural membranes electrical properties.

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Inference for integrate-and-fire neuron models

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