Network-Based Statistic Show Aberrant Functional Connectivity in Alzheimer's Disease

Alzheimer's disease (AD) and mild cognitive impairment (MCI) have been associated with impaired communication among large-scale brain networks. Given nature that interconnected subnetworks are responsible for daily behavior than a single pair of functional connectivity, it is valid to use a net...

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Veröffentlicht in:IEEE journal of selected topics in signal processing Jg. 10; H. 7; S. 1182 - 1188
Hauptverfasser: Zhan, Yafeng, Yao, Hongxiang, Wang, Pan, Zhou, Bo, Zhang, Zengqiang, Guo, Yane, An, Ningyu, Ma, Jianhua, Zhang, Xi, Liu, Yong
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.10.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Alzheimer's disease
Analysis of variance
components of interest
Dementia
Hospitals
mild cognitive impairment
network-based statistic
NIST
Programmable logic arrays
ISSN:1932-4553, 1941-0484
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Zusammenfassung:Alzheimer's disease (AD) and mild cognitive impairment (MCI) have been associated with impaired communication among large-scale brain networks. Given nature that interconnected subnetworks are responsible for daily behavior than a single pair of functional connectivity, it is valid to use a network-based statistic (NBS) method to exploit the clustering structure of connectivity alterations in AD/MCI. We explored abnormal network components using NBS based on resting-state functional magnetic resonance imaging (fMRI)connectivity in a sample of patients with AD (N = 35), MCI (N = 27) and age-matched healthy subjects (N = 27). The results demonstrated that patients had reduced functional connectivity strength in several components, including the default mode network, sensorimotor network, visual-sensory network, and visual-attention network. In patients with AD, the functional connectivity of these components of interest (COIs) exhibited greater attenuation than that in MCI subjects compared with normal cognition. A greater degree of cognitive impairment was correlated with a greater decrease in functional connectivity in the identified COIs. These results indicate that the neurodegenerative disruption of fMRI connectivity is widely distributed in several networks in AD/MCI. These profiles deepen our understanding of the neural basis of AD/MCI dysfunction and indicate the potential of resting-state fMRI measures as biomarkers or predictors of AD.
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ISSN:1932-4553
1941-0484
DOI:10.1109/JSTSP.2016.2600298