The potential evoked by a 'train' of N equally spaced auditory clicks, with an inter-click period shorter than the duration of the response to an isolated click, is said to be a steady-state response (SSR). Extracting the individual responses evoked by the clicks of the train during steady state can be key to understanding of the neurophysiological mechanisms underlying SSR generation. In the literature, this task has been dealt with only under the (unwarranted) assumption that the response of the system does not vary during the presentation of the clicks, i.e. no neurophysiological adaptation is present. In this work, a new, non-parametric algorithm is proposed that, relaxing the time-invariance hypothesis, allows the extraction from the SSR of the N waveforms individually evoked by the N clicks of the train. The performance of the approach is evaluated on simulated SSRs and on real data recorded from the temporal cortex of awake rats. Results show that the method is able to detect and assess possible adaptation of the neurophysiological system in the generation of SSRs.