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Abstract Details
Activity Number:
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119
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Type:
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Topic Contributed
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Date/Time:
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Monday, July 30, 2012 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics in Epidemiology
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Abstract - #306009 |
Title:
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Statistical Aspects of the Morris-Lecar Model of Neural Activity
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Author(s):
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Satish Iyengar*+
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Companies:
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University of Pittsburgh
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Address:
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Dept. of Statistics, Pittsburgh, PA, 15260, United States
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Keywords:
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spike train ;
diffusion ;
estimation
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Abstract:
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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 membrane's electrical properties. Ditlevson and Greenwood recently showed that the Morris-Lecar model, which is regarded as more realistic than earlier I-F models, is well approximated by a bivariate Ornstein-Uhlenbeck process. I will describe the parameter estimation for this approximation and preliminary results for the Morris-Lecar model itself.
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