Magnetoencephalography (MEG) detects the brain's magnetic fields as generated by neuronal electric currents arising from synaptic ion flow. It is noninvasive, has excellent temporal resolution, and it can localize neuronal activity with good precision. For these reasons, many scientists interested in the localization of brain functions have turned to MEG. The technique, however, is not without its drawbacks. Those reluctant to employ it cite its relative awkwardness among pediatric populations because MEG requires subjects to be fairly still during experiments. Due to these methodological challenges, infant MEG studies are not commonly pursued. In the present study, MEG was employed to study auditory discrimination in infants. We had two goals: first, to determine whether reliable results could be obtained from infants despite their movements; and second, to improve MEG data analysis methods. To get more reliable results from infants we employed novel hardware (real-time head-position tracking system) and software (signal space separation method, SSS) solutions to better deal with noise and movement. With these solutions, the location and orientation of the head can be tracked in real time and we were able to reduce noise and artifacts originating outside the helmet significantly. In the present study, these new methods were used to study the biomagnetic equivalents of event-related potentials (ERPs) in response to duration changes in harmonic tones in sleeping, healthy, full-term newborns. Our findings indicate that with the use of these new analysis routines, MEG will prove to be a very useful and more accessible experimental technique among pediatric populations.