An Asymmetry in the Automatic Detection of the Presence or Absence of a Frequency Modulation within a Tone: A Mismatch Negativity Study

Abstract

The infrequent occurrence of a transient feature (deviance; e.g., frequency modulation, FM) in one of the regular occurring sinusoidal tones (standards) elicits the deviance related mismatch negativity (MMN) component of the event-related brain potential. Based on a memory-based comparison, MMN reflects the mismatch between the representations of incoming and standard sounds. The present study investigated to what extent the infrequent exclusion of an FM is detected by the MMN system. For that purpose we measured MMN to deviances that either consisted of the exclusion or inclusion of an FM at an early or late position within the sound that was present or absent, respectively, in the standard. According to the information-content hypothesis, deviance detection relies on the difference in informational content of the deviant relative to that of the standard. As this difference between deviants with FM and standards without FM is the same as in the reversed case, comparable MMNs should be elicited to FM inclusions and exclusions. According to the feature-detector hypothesis, however, the deviance detection depends on the increased activation of feature detectors to additional sound features. Thus, rare exclusions of the FM should elicit no or smaller MMN than FM inclusions. In passive listening condition, MMN was obtained only for the early inclusion, but not for the exclusions nor for the late inclusion of an FM. This asymmetry in automatic deviance detection seems to partly reflect the contribution of feature detectors even though it cannot fully account for the missing MMN to late FM inclusions. Importantly, the behavioral deviance detection performance in the active listening condition did not reveal such an asymmetry, suggesting that the intentional detection of the deviants is based on the difference in informational content. On a more general level, the results partly support the “fresh-afferent” account or an extended memory-comparison based account of MMN.