Discrete Time Rescaling Theorem: Determining Goodness of Fit for Discrete Time Statistical Models of Neural Spiking
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چکیده
منابع مشابه
Discrete Time Rescaling Theorem: Determining Goodness of Fit for Discrete Time Statistical Models of Neural Spiking
One approach for understanding the encoding of information by spike trains is to fit statistical models and then test their goodness of fit. The time-rescaling theorem provides a goodness-of-fit test consistent with the point process nature of spike trains. The interspike intervals (ISIs) are rescaled (as a function of the model's spike probability) to be independent and exponentially distribut...
متن کاملDiscrete Time Rescaling Theorem: Determining Goodness of Fit for Statistical Models of Neural Spiking
One approach for understanding the encoding of information by spike trains is to fit statistical models and then test their goodness of fit. The time rescaling theorem provides a goodness of fit test consistent with the point process nature of spike trains. The interspike intervals (ISIs) are rescaled (as a function of the model’s spike probability) to be independent and exponentially distribut...
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ژورنال
عنوان ژورنال: Neural Computation
سال: 2010
ISSN: 0899-7667,1530-888X
DOI: 10.1162/neco_a_00015