The log-likelihood is just the (natural, usually) logarithm of the ordinary likelihood function. It is numerically easier to work with, and since log is a monotonic function, equivalent.<BR><BR ...

We introduce a deviance function that can be used in conjunction with the quasi-likelihood method. The need for such functions arises when the quasi-log likelihood function is not uniquely defined.

By combining these results we obtain general globally convergent iterative procedures for maximizing the likelihood function in any regular k-dimensional exponential family. The likelihood function ...

The log likelihood is a weighted sum of neuronal responses, where the weight of each neuron is determined by the log of its own tuning function; for the case of motion, this is a cosinusoidal ...

We then extended this model and developed an empirical decoding framework that learned the parameters of the log-likelihood function from the measured neuronal response distributions.