The mismatch negativity: A review of underlying mechanisms

By Marta Isabel Garrido, James M. Kilner, Klaas E. Stephan, Karl J. Friston. Clinical Neurophysiology, 2009

1,379 citations recorded by the source corpus.

The mismatch negativity (MMN) is a brain response to violations of a rule, established by a sequence of sensory stimuli (typically in the auditory domain) [Näätänen R. Attention and brain function. Hillsdale, NJ: Lawrence Erlbaum; 1992]. The MMN reflects the brain’s ability to perform automatic comparisons between consecutive stimuli and provides an electrophysiological index of sensory learning and perceptual accuracy. Although the MMN has been studied extensively, the neurophysiological mechanisms underlying the MMN are not well understood. Several hypotheses have been put forward to explain the generation of the MMN; amongst these accounts, the “adaptation hypothesis” and the “model adjustment hypothesis” have received the most attention. This paper presents a review of studies that focus on neuronal mechanisms underlying the MMN generation, discusses the two major explanatory hypotheses, and proposes predictive coding as a general framework that attempts to unify both.

Subfields: Cognitive Neuroscience, Signal Processing

View Paper: https://www.semanticscholar.org/paper/ad1fb331b219b79a3c2ea98f1241675c7c1f33bf

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Citations in the corpus

Interplay between acoustic/phonetic and semantic processes during spoken sentence comprehension: an ERP study. (2011, neutral): “As to the MMN, it has been proposed that this early automatic response results from a comparison between the auditory input encoded in the auditory cortex with a memory trace embodied in top-down predictions generated in prefrontal regions (Garrido et al., 2009; Winkler, 2007).”
Primary Visual Cortex Represents the Difference Between Past and Present (2013, background): “Finally, responses to stimulus differences fit well conceptually with predictive coding principles, proposing that deviations from cortically generated predictions are propagated up the visual hierarchy as error signals (Friston 2005; Garrido et al. 2009).”
Dopamine, Affordance and Active Inference (2012, background): “The proposed mechanism rests on prediction errors that are afforded too much precision [138].”
Repetition Suppression and Expectation Suppression Are Dissociable in Time in Early Auditory Evoked Fields (2012, background): “…ES a viable alternative explanation for the observed RS. Recent theoretical models of sensory processing inspire the hypothesis that RS and ES may be manifestations of prediction errors on different time scales (Friston, 2005; Kiebel et al., 2008; Garrido et al., 2009; Wacongne et al., 2012).”
Canonical microcircuits for predictive coding. (2012, neutral): “are enhanced relative to predicted stimuli (Garrido et al., 2009).”
A Hierarchy of Responses to Auditory Regularities in the Macaque Brain (2014, positive): “Predictive coding models postulate that the human mismatch response does not merely reflect a passive stimulus-specific adaptation (SSA) process, but an active process of predicting the next sound (Garrido et al., 2009).”
An aberrant precision account of autism (2014, neutral): “Conversely, the exuberant responses associated with the MMN can, in part, the attributed to a failure to attenuate sensory precision during the processing of unexpected " oddball " stimuli (Garrido et al., 2009).”
A Bayesian account of ‘hysteria’ (2012, background): “…fundamental mathematical and computational imperatives for adaptive biological systems like the brain (Friston et al., 2006), and also makes very specific predictions about both its functional anatomy and the kinds of measurable responses it should generate (Friston, 2005b; Garrido et al., 2009).”