The spectrotemporal response function (STRF) model of neural encoding quantitatively associates dynamic auditory neural (output) responses to a spectrogram-like representation of a dynamic (input) stimulus. STRFs were experimentally obtained via whole-head human cortical responses to dynamic auditory stimuli using magnetoencephalography (MEG). The stimuli employed consisted of unpredictable pure tones presented at a range of rates. The predictive power of the estimated STRFs was found to be comparable to those obtained from the cortical single and multiunit activity literature. The STRFs were also qualitatively consistent with those obtained from electrophysiological studies in animal models; in particular their local-field-potential-generated spectral distributions and multiunit-activity-generated temporal distributions. Comparison of these MEG STRFs with others obtained using natural speech and music stimuli reveal a general structure consistent with common baseline auditory processing, including evidence for a transition in low-level neural representations of natural speech by 100 ms, when an appropriately chosen stimulus representation was used. It is also demonstrated that MEG-based STRFs contain information similar to that obtained using classic auditory evoked potential based approaches, but with extended applications to long-duration, non-repeated stimuli