Emotional speech synchronizes brains across listeners and engages large-scale dynamic brain networks

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Nummenmaa, L.
dc.contributor.author Saarimäki, H.
dc.contributor.author Glerean, E.
dc.contributor.author Gotsopoulos, A.
dc.contributor.author Hari, R.
dc.contributor.author Sams, M
dc.date.accessioned 2017-05-11T08:31:22Z
dc.date.available 2017-05-11T08:31:22Z
dc.date.issued 2014-11-15
dc.identifier.citation Nummenmaa , L , Saarimäki , H , Glerean , E , Gotsopoulos , A , Hari , R & Sams , M 2014 , ' Emotional speech synchronizes brains across listeners and engages large-scale dynamic brain networks ' NEUROIMAGE , vol 102 , pp. 498-509 . DOI: 10.1016/j.neuroimage.2014.07.063 en
dc.identifier.issn 1053-8119
dc.identifier.issn 1095-9572
dc.identifier.other PURE UUID: 835f0dd1-f270-4fb4-a34a-c9dedc2fe58a
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/emotional-speech-synchronizes-brains-across-listeners-and-engages-largescale-dynamic-brain-networks(835f0dd1-f270-4fb4-a34a-c9dedc2fe58a).html
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/11716297/1_s2.0_S1053811914006466_main.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/25657
dc.description.abstract Speech provides a powerful means for sharing emotions. Here we implement novel intersubject phase synchronization and whole-brain dynamic connectivity measures to show that networks of brain areas become synchronized across participants who are listening to emotional episodes in spoken narratives. Twenty participants' hemodynamic brain activity was measured with functional magnetic resonance imaging (fMRI) while they listened to 45-s narratives describing unpleasant, neutral, and pleasant events spoken in neutral voice. After scanning, participants listened to the narratives again and rated continuously their feelings of pleasantness–unpleasantness (valence) and of arousal–calmness. Instantaneous intersubject phase synchronization (ISPS) measures were computed to derive both multi-subject voxel-wise similarity measures of hemodynamic activity and inter-area functional dynamic connectivity (seed-based phase synchronization, SBPS). Valence and arousal time series were subsequently used to predict the ISPS and SBPS time series. High arousal was associated with increased ISPS in the auditory cortices and in Broca's area, and negative valence was associated with enhanced ISPS in the thalamus, anterior cingulate, lateral prefrontal, and orbitofrontal cortices. Negative valence affected functional connectivity of fronto-parietal, limbic (insula, cingulum) and fronto-opercular circuitries, and positive arousal affected the connectivity of the striatum, amygdala, thalamus, cerebellum, and dorsal frontal cortex. Positive valence and negative arousal had markedly smaller effects. We propose that high arousal synchronizes the listeners' sound-processing and speech-comprehension networks, whereas negative valence synchronizes circuitries supporting emotional and self-referential processing. en
dc.format.extent 12
dc.format.extent 498-509
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries NEUROIMAGE en
dc.relation.ispartofseries Volume 102 en
dc.rights openAccess en
dc.subject.other 114 Physical sciences en
dc.subject.other 221 Nanotechnology en
dc.subject.other 214 Mechanical engineering en
dc.subject.other 218 Environmental engineering en
dc.title Emotional speech synchronizes brains across listeners and engages large-scale dynamic brain networks en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Department of Neuroscience and Biomedical Engineering
dc.subject.keyword Emotion
dc.subject.keyword Connectivity
dc.subject.keyword Synchronization
dc.subject.keyword Speech comprehension
dc.subject.keyword Network
dc.subject.keyword 114 Physical sciences
dc.subject.keyword 221 Nanotechnology
dc.subject.keyword 214 Mechanical engineering
dc.subject.keyword 218 Environmental engineering
dc.identifier.urn URN:NBN:fi:aalto-201705114041
dc.identifier.doi 10.1016/j.neuroimage.2014.07.063
dc.type.version publishedVersion

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