The relative merits of different population coding schemes have mostly been studied in the framework of stimulus reconstruction using Fisher Information, minimum mean square error or mutual information. Here, we analyze neural population codes using the minimal discrimination error (MDE) and the Jensen-Shannon information in a two alternatives forced choice (2AFC) task. In a certain sense, this approach is more informative than the previous ones as it defines an error that is specific to any pair of possible stimuli-in particular, it includes Fisher Information as a special case. We demonstrate several advantages of the minimal discrimination error:(1) it is very intuitive and easier to compare to experimental data,(2) it is easier to compute than mutual information or minimum mean square error,(3) it allows studying assumption about prior distributions, and (4) it provides a more reliable assessment of coding …