Temporal encoding in auditory evoked neuromagnetic fields: Stochastic resonance

Recent investigations have demonstrated that temporal patterns of sensory neural activity detected by magnetoencephalography (MEG) reflect features of the stimulus. In this study, neuromagnetic activity was investigated using an event detection algorithm based on the correlation coefficient. The results of the technique are compared with widely used methods of analysis in two experimental conditions and are shown to identify features in the single-trial MEG response that are not apparent in the response obtained by averaging across repeated trials. As an example of the technique, the physiologic jitter in latency associated with the M100 of auditory evoked fields was reproducibly measured. Specifically, higher intensity sounds were associated with an increased reliability. The technique was also applied to the noise-enhanced evoked auditory response, producing an objective demonstration of a cortical manifestation of the phenomenon of stochastic resonance-the paradoxical enhancement in the measurement of the signal-to-noise ratio (SNR) induced by optimal addition of noise to system input.