Many neurons in the nervous system exhibit subthreshold membrane potential oscillations with related action potential generation when the oscillations reach the spike threshold. Such oscillations are an intrinsic property of the neurons and result from the interplay of different ionic conductances. In addition, stochastic fluctuations play an important role for the responses because the noise can essentially determine whether a spike is triggered or not when oscillations are near spike threshold. In the present study we investigate the stimulus-dependent tuning properties of a noisy ionic conductance model for intrinsic subthreshold oscillations and spiking. On depolarization by an applied current, the model exhibits subthreshold oscillatory activity with occasional spike generation. We examine how the amount of applied current, the noise intensity, variation of maximum conductance values and scaling to different temperature ranges alter the responses of the model with respect to voltage traces, interspike intervals and their statistics and the mean spike frequency curves. We demonstrate that subthreshold oscillatory neurons in the presence of noise can sensitively and also selectively be tuned by stimulus-dependent variation of model parameters. Our findings agree well with experimental data and demonstrate a significant role for subthreshold oscillatory neurons for signal encoding and neuromodulation.