In this study, effects of the heterogeneity in neuronal networks and subthreshold signal features on subthreshold signal detection in the nervous system is investigated. As most of studies in the literature investigate the subject by considering neuron populations as homogenous systems, in this study, the populations are considered as heterogeneous in terms of neuronal excitability. The information processing performance of the neuron populations is systematically studied by using mathematical equations for modeling the dynamics of the neurons, which are basic units of the system. As a result of the simulations performed, it is seen that the sub-threshold signal frequency and the heterogeneity in the excitability are important system parameters for optimizing the information encoding performance. It is shown that the population encoding performance is maximized depending on the subthreshold signal frequency at different optimum levels of heterogeneity in the population.