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

doi:10.1117/12.810909

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 +

Proceedings Volume 7262, Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging; 72621X (2009) https://doi.org/10.1117/12.810909
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States

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.

Citation Download Citation

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

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE