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Kuramoto Model-Based Analysis Reveals Oxytocin Effects on Brain Network Dynamics
Zheng, Shuhan1; Liang, Zhichao1; Qu, Youzhi1; Wu, Qingyuan2; Wu, Haiyan3; Liu, Quanying4
2022-02-01
Source PublicationInternational Journal of Neural Systems
ISSN0129-0657
Volume32Issue:2
Abstract

The oxytocin effects on large-scale brain networks such as Default Mode Network (DMN) and Frontoparietal Network (FPN) have been largely studied using fMRI data. However, these studies are mainly based on the statistical correlation or Bayesian causality inference, lacking interpretability at the physical and neuroscience level. Here, we propose a physics-based framework of the Kuramoto model to investigate oxytocin effects on the phase dynamic neural coupling in DMN and FPN. Testing on fMRI data of 59 participants administrated with either oxytocin or placebo, we demonstrate that oxytocin changes the topology of brain communities in DMN and FPN, leading to higher synchronization in the FPN and lower synchronization in the DMN, as well as a higher variance of the coupling strength within the DMN and more flexible coupling patterns at group level. These results together indicate that oxytocin may increase the ability to overcome the corresponding internal oscillation dispersion and support the flexibility in neural synchrony in various social contexts, providing new evidence for explaining the oxytocin modulated social behaviors. Our proposed Kuramoto model-based framework can be a potential tool in network neuroscience and offers physical and neural insights into phase dynamics of the brain.

KeywordDefault Mode Network Fmri Frontoparietal Network Kuramoto Model Oxytocin Effects
DOI10.1142/S0129065722500022
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000745070100003
Scopus ID2-s2.0-85121133681
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Cited Times [WOS]:1   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionINSTITUTE OF COLLABORATIVE INNOVATION
Corresponding AuthorWu, Haiyan; Liu, Quanying
Affiliation1.Shenzhen Key Laboratory of Smart Healthcare Engineering, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, 518055, China
2.State Key Laboratory of Cognitive, Neuroscience and Learning and IDG/McGovern, Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
3.Centre for Cognitive and Brain Sciences and Department of Psychology, University of Macau, Macau, Macao
4.Shenzhen Key Laboratory of Smart Healthcare Engineering, Southern University of Science and Technology, Shenzhen, 518005, China
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Zheng, Shuhan,Liang, Zhichao,Qu, Youzhi,et al. Kuramoto Model-Based Analysis Reveals Oxytocin Effects on Brain Network Dynamics[J]. International Journal of Neural Systems,2022,32(2).
APA Zheng, Shuhan,Liang, Zhichao,Qu, Youzhi,Wu, Qingyuan,Wu, Haiyan,&Liu, Quanying.(2022).Kuramoto Model-Based Analysis Reveals Oxytocin Effects on Brain Network Dynamics.International Journal of Neural Systems,32(2).
MLA Zheng, Shuhan,et al."Kuramoto Model-Based Analysis Reveals Oxytocin Effects on Brain Network Dynamics".International Journal of Neural Systems 32.2(2022).
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