Brain activity reflects the predictability of word sequences in listened continuous speech: Brain activity predicts word sequences

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorKoskinen, Miikaen_US
dc.contributor.authorKurimo, Mikkoen_US
dc.contributor.authorGross, Joachimen_US
dc.contributor.authorHyvärinen, Aapoen_US
dc.contributor.authorHari, Riittaen_US
dc.contributor.departmentDepartment of Neuroscience and Biomedical Engineeringen
dc.contributor.departmentDepartment of Signal Processing and Acousticsen
dc.contributor.departmentDepartment of Arten
dc.contributor.groupauthorCentre of Excellence in Computational Inference, COINen
dc.contributor.groupauthorSpeech Recognitionen
dc.contributor.organizationUniversity of Glasgowen_US
dc.contributor.organizationUniversity of Helsinkien_US
dc.date.accessioned2020-06-25T08:39:59Z
dc.date.available2020-06-25T08:39:59Z
dc.date.issued2020-10-01en_US
dc.description.abstractNatural speech builds on contextual relations that can prompt predictions of upcoming utterances. To study the neural underpinnings of such predictive processing we asked 10 healthy adults to listen to a 1-h-long audiobook while their magnetoencephalographic (MEG) brain activity was recorded. We correlated the MEG signals with acoustic speech envelope, as well as with estimates of Bayesian word probability with and without the contextual word sequence (N-gram and Unigram, respectively), with a focus on time-lags. The MEG signals of auditory and sensorimotor cortices were strongly coupled to the speech envelope at the rates of syllables (4–8 ​Hz) and of prosody and intonation (0.5–2 ​Hz). The probability structure of word sequences, independently of the acoustical features, affected the ≤ 2-Hz signals extensively in auditory and rolandic regions, in precuneus, occipital cortices, and lateral and medial frontal regions. Fine-grained temporal progression patterns occurred across brain regions 100–1000 ​ms after word onsets. Although the acoustic effects were observed in both hemispheres, the contextual influences were statistically significantly lateralized to the left hemisphere. These results serve as a brain signature of the predictability of word sequences in listened continuous speech, confirming and extending previous results to demonstrate that deeply-learned knowledge and recent contextual information are employed dynamically and in a left-hemisphere-dominant manner in predicting the forthcoming words in natural speech.en
dc.description.versionPeer revieweden
dc.format.extent9
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationKoskinen, M, Kurimo, M, Gross, J, Hyvärinen, A & Hari, R 2020, 'Brain activity reflects the predictability of word sequences in listened continuous speech : Brain activity predicts word sequences', NeuroImage, vol. 219, 116936. https://doi.org/10.1016/j.neuroimage.2020.116936en
dc.identifier.doi10.1016/j.neuroimage.2020.116936en_US
dc.identifier.issn1053-8119
dc.identifier.issn1095-9572
dc.identifier.otherPURE UUID: 7b9dcf40-b508-4bae-9ddd-df869b4b2168en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/7b9dcf40-b508-4bae-9ddd-df869b4b2168en_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/43534523/Koskinen_Brain_activity_reflects_Neuroimage.pdf
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/45164
dc.identifier.urnURN:NBN:fi:aalto-202006254121
dc.language.isoenen
dc.publisherElsevier
dc.relation.ispartofseriesNeuroImageen
dc.relation.ispartofseriesVolume 219en
dc.rightsopenAccessen
dc.subject.keywordCerebral cortexen_US
dc.subject.keywordContinuous speechen_US
dc.subject.keywordLanguage modelen_US
dc.subject.keywordMEGen_US
dc.subject.keywordN-gramen_US
dc.subject.keywordNaturalistic neuroscienceen_US
dc.subject.keywordSpeech perceptionen_US
dc.subject.keywordSpeech–brain couplingen_US
dc.titleBrain activity reflects the predictability of word sequences in listened continuous speech: Brain activity predicts word sequencesen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
dc.type.versionpublishedVersion

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