2015
DOI: 10.1371/journal.pone.0126775
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Auditory Mismatch Negativity and Repetition Suppression Deficits in Schizophrenia Explained by Irregular Computation of Prediction Error

Abstract: BackgroundThe predictive coding model is rapidly gaining attention in schizophrenia research. It posits the neuronal computation of residual variance (‘prediction error’) between sensory information and top-down expectation through multiple hierarchical levels. Event-related potentials (ERP) reflect cortical processing stages that are increasingly interpreted in the light of the predictive coding hypothesis. Both mismatch negativity (MMN) and repetition suppression (RS) measures are considered a prediction err… Show more

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Cited by 40 publications
(22 citation statements)
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“…This thought has recently been experimentally confirmed by Wacongne et al [2012] who showed that MMN complies with assumptions derived from the predictive coding model rather than the habituation model, at least in the auditory modality. Another paper by Rentzsch et al [2015] further corroborates the generative model by demonstrating a strong correlation of auditory MMN with a repetition suppression measure, which is thought to rely on minimization of prediction error [Friston, 2005].…”
Section: Introductionmentioning
confidence: 68%
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“…This thought has recently been experimentally confirmed by Wacongne et al [2012] who showed that MMN complies with assumptions derived from the predictive coding model rather than the habituation model, at least in the auditory modality. Another paper by Rentzsch et al [2015] further corroborates the generative model by demonstrating a strong correlation of auditory MMN with a repetition suppression measure, which is thought to rely on minimization of prediction error [Friston, 2005].…”
Section: Introductionmentioning
confidence: 68%
“…The MMN response is computed by subtracting the response to standard stimuli from the response to deviant stimuli and is thus thought to directly represent the residual variance between higher cortical predictions and sensory information, that is, the prediction error [Friston, 2005]. Another paper by Rentzsch et al [2015] further corroborates the generative model by demonstrating a strong correlation of auditory MMN with a repetition suppression measure, which is thought to rely on minimization of prediction error [Friston, 2005]. Another paper by Rentzsch et al [2015] further corroborates the generative model by demonstrating a strong correlation of auditory MMN with a repetition suppression measure, which is thought to rely on minimization of prediction error [Friston, 2005].…”
Section: Introductionmentioning
confidence: 99%
“…While these findings support deficits in cortical modulation of sensory responses to self-generated actions in schizophrenia, a broader range of studies implicate deficits in predictive coding based on recent sensory contextual information (37, 43-48). For example, the widely replicated deficit in mismatch negativity (MMN) (46), an ERP component elicited by deviant auditory stimuli in auditory oddball sequences, has been considered to reflect deficient predictive coding of recent contextual information in schizophrenia (33, 35, 36, 43, 45, 48-52). …”
Section: Introductionmentioning
confidence: 79%
“…Additionally, while MMN is traditionally measured using pure tones that can easily be varied on parameters like pitch and duration, RS studies in schizophrenia commonly use broadband paired-click stimuli to elicit stimulus-general sensory “gating” of AEPs. Relationships have been identified between stimulus-general RS measured with sensory gating paradigms and MMN to deviations in tone pitch (Kisley et al 2004; Gjini et al 2010; Rentzsch et al 2015); however, it is unclear whether similar relationships would be identified using pure tone stimuli. Furthermore, although MMN is certainly related to RS both conceptually (i.e.…”
Section: Introductionmentioning
confidence: 99%