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Article: Functional connectivity profiles of the default mode and visual networks reflect temporal accumulative effects of sustained naturalistic emotional experience

TitleFunctional connectivity profiles of the default mode and visual networks reflect temporal accumulative effects of sustained naturalistic emotional experience
Authors
KeywordsEmotion classification
fMRI
Functional connectivity
Movie clips
Naturalistic stimulation
Issue Date2023
Citation
NeuroImage, 2023, v. 269, article no. 119941 How to Cite?
AbstractDetermining and decoding emotional brain processes under ecologically valid conditions remains a key challenge in affective neuroscience. The current functional Magnetic Resonance Imaging (fMRI) based emotion decoding studies are mainly based on brief and isolated episodes of emotion induction, while sustained emotional experience in naturalistic environments that mirror daily life experiences are scarce. Here we used 12 different 10-minute movie clips as ecologically valid emotion-evoking procedures in n = 52 individuals to explore emotion-specific fMRI functional connectivity (FC) profiles on the whole-brain level at high spatial resolution (432 parcellations including cortical and subcortical structures). Employing machine-learning based decoding and cross validation procedures allowed to investigate FC profiles contributing to classification that can accurately distinguish sustained happiness and sadness and that generalize across subjects, movie clips, and parcellations. Both functional brain network-based and subnetwork-based emotion classification results suggested that emotion manifests as distributed representation of multiple networks, rather than a single functional network or subnetwork. Further, the results showed that the Visual Network (VN) and Default Mode Network (DMN) associated functional networks, especially VN-DMN, exhibited a strong contribution to emotion classification. To further estimate the temporal accumulative effect of naturalistic long-term movie-based video-evoking emotions, we divided the 10-min episode into three stages: early stimulation (1∼200 s), middle stimulation (201∼400 s), and late stimulation (401∼600 s) and examined the emotion classification performance at different stimulation stages. We found that the late stimulation contributes most to the classification (accuracy=85.32%, F1-score=85.62%) compared to early and middle stimulation stages, implying that continuous exposure to emotional stimulation can lead to more intense emotions and further enhance emotion-specific distinguishable representations. The present work demonstrated that sustained happiness and sadness under naturalistic conditions are presented in emotion-specific network profiles and these expressions may play different roles in the generation and modulation of emotions. These findings elucidated the importance of network level adaptations for sustained emotional experiences during naturalistic contexts and open new venues for imaging network level contributions under naturalistic conditions.
Persistent Identifierhttp://hdl.handle.net/10722/330322
ISSN
2023 Impact Factor: 4.7
2023 SCImago Journal Rankings: 2.436
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorXu, Shuyue-
dc.contributor.authorZhang, Zhiguo-
dc.contributor.authorLi, Linling-
dc.contributor.authorZhou, Yongjie-
dc.contributor.authorLin, Danyi-
dc.contributor.authorZhang, Min-
dc.contributor.authorZhang, Li-
dc.contributor.authorHuang, Gan-
dc.contributor.authorLiu, Xiqin-
dc.contributor.authorBecker, Benjamin-
dc.contributor.authorLiang, Zhen-
dc.date.accessioned2023-09-05T12:09:35Z-
dc.date.available2023-09-05T12:09:35Z-
dc.date.issued2023-
dc.identifier.citationNeuroImage, 2023, v. 269, article no. 119941-
dc.identifier.issn1053-8119-
dc.identifier.urihttp://hdl.handle.net/10722/330322-
dc.description.abstractDetermining and decoding emotional brain processes under ecologically valid conditions remains a key challenge in affective neuroscience. The current functional Magnetic Resonance Imaging (fMRI) based emotion decoding studies are mainly based on brief and isolated episodes of emotion induction, while sustained emotional experience in naturalistic environments that mirror daily life experiences are scarce. Here we used 12 different 10-minute movie clips as ecologically valid emotion-evoking procedures in n = 52 individuals to explore emotion-specific fMRI functional connectivity (FC) profiles on the whole-brain level at high spatial resolution (432 parcellations including cortical and subcortical structures). Employing machine-learning based decoding and cross validation procedures allowed to investigate FC profiles contributing to classification that can accurately distinguish sustained happiness and sadness and that generalize across subjects, movie clips, and parcellations. Both functional brain network-based and subnetwork-based emotion classification results suggested that emotion manifests as distributed representation of multiple networks, rather than a single functional network or subnetwork. Further, the results showed that the Visual Network (VN) and Default Mode Network (DMN) associated functional networks, especially VN-DMN, exhibited a strong contribution to emotion classification. To further estimate the temporal accumulative effect of naturalistic long-term movie-based video-evoking emotions, we divided the 10-min episode into three stages: early stimulation (1∼200 s), middle stimulation (201∼400 s), and late stimulation (401∼600 s) and examined the emotion classification performance at different stimulation stages. We found that the late stimulation contributes most to the classification (accuracy=85.32%, F1-score=85.62%) compared to early and middle stimulation stages, implying that continuous exposure to emotional stimulation can lead to more intense emotions and further enhance emotion-specific distinguishable representations. The present work demonstrated that sustained happiness and sadness under naturalistic conditions are presented in emotion-specific network profiles and these expressions may play different roles in the generation and modulation of emotions. These findings elucidated the importance of network level adaptations for sustained emotional experiences during naturalistic contexts and open new venues for imaging network level contributions under naturalistic conditions.-
dc.languageeng-
dc.relation.ispartofNeuroImage-
dc.subjectEmotion classification-
dc.subjectfMRI-
dc.subjectFunctional connectivity-
dc.subjectMovie clips-
dc.subjectNaturalistic stimulation-
dc.titleFunctional connectivity profiles of the default mode and visual networks reflect temporal accumulative effects of sustained naturalistic emotional experience-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.neuroimage.2023.119941-
dc.identifier.pmid36791897-
dc.identifier.scopuseid_2-s2.0-85148351674-
dc.identifier.volume269-
dc.identifier.spagearticle no. 119941-
dc.identifier.epagearticle no. 119941-
dc.identifier.eissn1095-9572-
dc.identifier.isiWOS:000944922200001-

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