Interpreting the Mismatch Negativity

TLDR

The mismatch negativity (MMN) ERP is traditionally explained by a memory‑mismatch theory in which a sensory memory trace of a repetitive standard sound is violated, a view largely supported by oddball paradigms but increasingly challenged by MMN observed in non‑repeating stimulus sequences. This study proposes an alternative memory‑mismatch variant that aims to unify all observed MMN phenomena. The proposed mechanism posits that MMN arises from regularity representations that encode intersound rules, generate temporally aligned predictions, and are updated when acoustic input mismatches those predictions. The authors argue that the MMN‑driven predictive models underpin temporal grouping, thereby organizing sound into auditory objects.

Abstract

The widely accepted “memory-mismatch” interpretation of the mismatch negativity (MMN) event-related brain potential (ERP) suggests that an MMN is elicited when an acoustic event deviates from a memory record describing the immediate history of the sound sequence. The first variant of the memory-mismatch theory suggested that the memory underlying MMN generation was a strong auditory sensory memory trace, which encoded the repetitive standard sound. This “trace-mismatch” explanation of MMN has been primarily based on results obtained in the auditory oddball paradigm. However, in recent years, MMN has been observed in stimulus paradigms containing no frequently repeating sound. We now suggest a different variant of the memory-mismatch interpretation of MMN in order to provide a unified explanation of all MMN phenomena. The regularity-violation explanation of MMN assumes that the memory records retaining the history of auditory stimulation are regularity representations. These representations encode rules extracted from the regular intersound relationships, which are mapped to the concrete sound sequence by finely detailed auditory sensory information. Auditory events are compared with temporally aligned predictions drawn from the regularity representations (predictive models) and the observable MMN response reflects a process updating the representations of those detected regularities whose prediction was mismatched by the acoustic input. It is further suggested that the auditory deviance detection system serves to organize sound in the brain: The predictive models maintained by the MMN-generating process provide the basis of temporal grouping, a crucial step in the formation of auditory objects.