Dissociating group and individual profile of functional connectivity using low rank matrix recovery
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 11266 LNCS, Page: 646-654
2018
- 2Captures
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Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Captures2
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Conference Paper Description
Brain connectivity network consists of general substrate and specific traits, yet their characteristic and relationships were still unknown. Here, we systematically investigate the substrate and traits of functional connectivity (FC) network. We calculated the resting-state functional magnetic resonance imaging-based FC using data from the Human Connectome Project. Subjects’ FC was decomposed into general substrate and specific traits via a novel low rank matrix recovery method. Then we investigated the relationships between FC traits and the cognitive behaviors. We found that FC traits were significantly associated with the cognitive behaviors. Our findings suggest that individual differences in FC traits could mainly account for inter-subject variability of the cognition and behaviors. This could advance our understanding of substrate and traits of brain function.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85057104978&origin=inward; http://dx.doi.org/10.1007/978-3-030-02698-1_56; https://link.springer.com/10.1007/978-3-030-02698-1_56; https://dx.doi.org/10.1007/978-3-030-02698-1_56; https://link.springer.com/chapter/10.1007/978-3-030-02698-1_56
Springer Science and Business Media LLC
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