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dc.contributor.authorTsogli, Barbara
dc.contributor.authorJentschke, Sebastian
dc.contributor.authorDaikoku, Tatsuya
dc.contributor.authorKölsch, Stefan
dc.date.accessioned2019-07-05T09:07:32Z
dc.date.available2019-07-05T09:07:32Z
dc.date.issued2019-04-03
dc.PublishedTsogli B, Jentschke S, Daikoku T, Kölsch S. When the statistical MMN meets the physical MMN. Scientific Reports. 2019;9:5563eng
dc.identifier.issn2045-2322
dc.identifier.urihttps://hdl.handle.net/1956/20559
dc.description.abstractHow do listeners respond to prediction errors within patterned sequence of sounds? To answer this question we carried out a statistical learning study using electroencephalography (EEG). In a continuous auditory stream of sound triplets the deviations were either (a) statistical, in terms of transitional probability, (b) physical, due to a change in sound location (left or right speaker) or (c) a double deviants, i.e. a combination of the two. Statistical and physical deviants elicited a statistical mismatch negativity and a physical MMN respectively. Most importantly, we found that efects of statistical and physical deviants interacted (the statistical MMN was smaller when co-occurring with a physical deviant). Results show, for the frst time, that processing of prediction errors due to statistical learning is afected by prediction errors due to physical deviance. Our fndings thus show that the statistical MMN interacts with the physical MMN, implying that prediction error processing due to physical sound attributes suppresses processing of learned statistical properties of sounds.en_US
dc.language.isoengeng
dc.publisherNature Researcheng
dc.rightsAttribution CC BYeng
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/eng
dc.titleWhen the statistical MMN meets the physical MMNeng
dc.typePeer reviewed
dc.typeJournal article
dc.date.updated2019-04-29T06:44:46Z
dc.description.versionpublishedVersion
dc.rights.holderCopyright 2019 The Authorseng
dc.identifier.doihttps://doi.org/10.1038/s41598-019-42066-4
dc.identifier.cristin1694422
dc.source.journalScientific Reports
dc.identifier.citationScientific Reports. 2019, 9, 5563.


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