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Open AccessArticle

Manifold Learning of Dynamic Functional Connectivity Reliably Identifies Functionally Consistent Coupling Patterns in Human Brains

1
College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China
2
Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing 100850, China
*
Author to whom correspondence should be addressed.
Brain Sci. 2019, 9(11), 309; https://doi.org/10.3390/brainsci9110309
Received: 10 October 2019 / Revised: 31 October 2019 / Accepted: 1 November 2019 / Published: 4 November 2019
(This article belongs to the Section Neuroimaging)
Most previous work on dynamic functional connectivity (dFC) has focused on analyzing temporal traits of functional connectivity (similar coupling patterns at different timepoints), dividing them into functional connectivity states and detecting their between-group differences. However, the coherent functional connectivity of brain activity among the temporal dynamics of functional connectivity remains unknown. In the study, we applied manifold learning of local linear embedding to explore the consistent coupling patterns (CCPs) that reflect functionally homogeneous regions underlying dFC throughout the entire scanning period. By embedding the whole-brain functional connectivity in a low-dimensional manifold space based on the Human Connectome Project (HCP) resting-state data, we identified ten stable patterns of functional coupling across regions that underpin the temporal evolution of dFC. Moreover, some of these CCPs exhibited significant neurophysiological meaning. Furthermore, we apply this method to HCP rsfMR and tfMRI data as well as sleep-deprivation data and found that the topological organization of these low-dimensional structures has high potential for predicting sleep-deprivation states (classification accuracy of 92.3%) and task types (100% identification for all seven tasks).In summary, this work provides a methodology for distilling coherent low-dimensional functional connectivity structures in complex brain dynamics that play an important role in performing tasks or characterizing specific states of the brain. View Full-Text
Keywords: manifold learning; consist coupling patterns; resting state; dynamic functional connectivity; sleep deprivation manifold learning; consist coupling patterns; resting state; dynamic functional connectivity; sleep deprivation
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Yang, Y.; Wang, L.; Lei, Y.; Zhu, Y.; Shen, H. Manifold Learning of Dynamic Functional Connectivity Reliably Identifies Functionally Consistent Coupling Patterns in Human Brains. Brain Sci. 2019, 9, 309.

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