Altered default mode network connectivity in alzheimer's disease-A resting functional MRI and bayesian network study
A number of functional magnetic resonance imaging (fMRI) studies reported the existence of default mode network (DMN) and its disruption due to the presence of a disease such as Alzheimer's disease (AD). In this investigation, first, we used the independent component analysis (ICA) technique to...
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Veröffentlicht in: | Human brain mapping 2011-11, Vol.32 (11), p.1868-1881 |
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Sprache: | eng |
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Zusammenfassung: | A number of functional magnetic resonance imaging (fMRI) studies reported the existence of default mode network (DMN) and its disruption due to the presence of a disease such as Alzheimer's disease (AD). In this investigation, first, we used the independent component analysis (ICA) technique to confirm the DMN difference between patients with AD and normal control (NC) reported in previous studies. Consistent with the previous studies, the decreased resting‐state functional connectivity of DMN in AD was identified in posterior cingulated cortex (PCC), medial prefrontal cortex (MPFC), inferior parietal cortex (IPC), inferior temporal cortex (ITC), and hippocampus (HC). Moreover, we introduced Bayesian network (BN) to study the effective connectivity of DMN and the difference between AD and NC. When compared the DMN effective connectivity in AD with the one in NC using a nonparametric random permutation test, we found that connections from left HC to left IPC, left ITC to right HC, right HC to left IPC, to MPFC and to PCC were all lost. In addition, in AD group, the connection directions between right HC and left HC, between left HC and left ITC, and between right IPC and right ITC were opposite to those in NC group. The connections of right HC to other regions, except left HC, within the BN were all statistically in‐distinguishable from 0, suggesting an increased right hippocampal pathological and functional burden in AD. The altered effective connectivity in patients with AD may reveal more characteristics of the disease and may serve as a potential biomarker. Hum Brain Mapp, 2011. © 2011 Wiley‐Liss, Inc. |
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ISSN: | 1065-9471 1097-0193 1097-0193 |
DOI: | 10.1002/hbm.21153 |