Estimation
The parameters of the LNP model consist of the linear filters and the nonlinearity . The estimation problem (also known as the problem of neural characterization) is the problem of determining these parameters from data consisting of a time-varying stimulus and the set of observed spike times. Techniques for estimating the LNP model parameters include:
- moment-based techniques, such as the spike-triggered average or spike-triggered covariance
- with information-maximization or maximum likelihood techniques.
Read more about this topic: Linear-nonlinear-Poisson Cascade Model
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