Paper
27 February 2009 Functional network connectivity analysis based on partial correlation in Alzheimer's disease
Nan Zhang, Xiaoting Guan, Yumei Zhang, Jingjing Li, Hongyan Chen, Kewei Chen, Adam Fleisher, Li Yao, Xia Wu
Author Affiliations +
Abstract
Functional network connectivity (FNC) measures the temporal dependency among the time courses of functional networks. However, the marginal correlation between two networks used in the classic FNC analysis approach doesn't separate the FNC from the direct/indirect effects of other networks. In this study, we proposed an alternative approach based on partial correlation to evaluate the FNC, since partial correlation based FNC can reveal the direct interaction between a pair of networks, removing dependencies or influences from others. Previous studies have demonstrated less task-specific activation and less rest-state activity in Alzheimer's disease (AD). We applied present approach to contrast FNC differences of resting state network (RSN) between AD and normal controls (NC). The fMRI data under resting condition were collected from 15 AD and 16 NC. FNC was calculated for each pair of six RSNs identified using Group ICA, thus resulting in 15 (2 out of 6) pairs for each subject. Partial correlation based FNC analysis indicated 6 pairs significant differences between groups, while marginal correlation only revealed 2 pairs (involved in the partial correlation results). Additionally, patients showed lower correlation than controls among most of the FNC differences. Our results provide new evidences for the disconnection hypothesis in AD.
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Nan Zhang, Xiaoting Guan, Yumei Zhang, Jingjing Li, Hongyan Chen, Kewei Chen, Adam Fleisher, Li Yao, and Xia Wu "Functional network connectivity analysis based on partial correlation in Alzheimer's disease", Proc. SPIE 7262, Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging, 72621X (27 February 2009); https://doi.org/10.1117/12.810909
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KEYWORDS
Control systems

Independent component analysis

Brain

Visualization

Alzheimer's disease

Functional magnetic resonance imaging

Network security

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