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Dynamic effective connectivity in resting state fMRI

Authors
 Hae-Jeong Park  ;  Karl J. Friston  ;  Chongwon Pae  ;  Bumhee Park  ;  Adeel Razi 
Citation
 Neuroimage, Vol.180(Special SI) : 594-608, 2018 
Journal Title
 Neuroimage 
ISSN
 1053-8119 
Issue Date
2018
Abstract
Context-sensitive and activity-dependent fluctuations in connectivity underlie functional integration in the brain and have been studied widely in terms of synaptic plasticity, learning and condition-specific (e.g., attentional) modulations of synaptic efficacy. This dynamic aspect of brain connectivity has recently attracted a lot of attention in the resting state fMRI community. To explain dynamic functional connectivity in terms of directed effective connectivity among brain regions, we introduce a novel method to identify dynamic effective connectivity using spectral dynamic causal modelling (spDCM). We used parametric empirical Bayes (PEB) to model fluctuations in directed coupling over consecutive windows of resting state fMRI time series. Hierarchical PEB can model random effects on connectivity parameters at the second (between-window) level given connectivity estimates from the first (within-window) level. In this work, we used a discrete cosine transform basis set or eigenvariates (i.e., expression of principal components) to model fluctuations in effective connectivity over windows. We evaluated the ensuing dynamic effective connectivity in terms of the consistency of baseline connectivity within default mode network (DMN), using the resting state fMRI from Human Connectome Project (HCP). To model group-level baseline and dynamic effective connectivity for DMN, we extended the PEB approach by conducting a multilevel PEB analysis of between-session and between-subject group effects. Model comparison clearly spoke to dynamic fluctuations in effective connectivity - and the dynamic functional connectivity these changes explain. Furthermore, baseline effective connectivity was consistent across independent sessions - and notably more consistent than estimates based upon conventional models. This work illustrates the advantage of hierarchical modelling with spDCM, in characterizing the dynamics of effective connectivity.
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DOI
10.1016/j.neuroimage.2017.11.033
Appears in Collections:
1. Journal Papers (연구논문) > 1. College of Medicine (의과대학) > Dept. of Nuclear Medicine (핵의학교실)
Yonsei Authors
박해정(Park, Hae Jeong) ORCID logo https://orcid.org/0000-0002-4633-0756
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URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/163675
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