Functional MRI-Specific Alterations in Salience Network in Mild Cognitive Impairment: An ALE Meta-Analysis - Song, Yu; Xu, Wenwen; Chen, Shanshan; Hu, Guanjie; Ge, Honglin; Xue, Chen; Qi, Wenzhang; Lin, Xingjian; Chen, Jiu (Frontiers in Aging Neuroscience, 2021)
Background: Mild cognitive impairment (MCI) is an intermediate stage between normal aging and dementia. Amnestic MCI (aMCI) and non-amnestic MCI are the two subtypes of MCI with the former having a higher risk for progressing to Alzheimer’s disease (AD). Compared with healthy elderly adults, individuals with MCI have specific functional alterations in the salience network (SN). However, no consistent results are documenting these changes. This meta-analysis aimed to investigate the specific functional alterations in SN in MCI and aMCI. Methods: We systematically searched PubMed, Embase, and Web of Science for scientific neuroimaging literature based on three research methods, functional connectivity (FC), regional homogeneity (ReHo), and the amplitude of low-frequency fluctuation or fractional amplitude of low-frequency fluctuation (ALFF/fALFF). Then, we conducted the coordinate-based meta-analysis by using the Activation Likelihood Estimation algorithm. Results: In total, 30 functional neuroimaging studies were included. After extracting the data and analyzing it, we obtained specific changes in some brain regions in SN including decreased ALFF/fALFF in the left superior temporal gyrus, the insula, the precentral gyrus, and the precuneus in MCI and aMCI, increased FC in the thalamus, the caudate, the superior temporal gyrus, the insula and the cingulate gyrus in MCI, and decreased ReHo in the anterior cingulate gyrus in aMCI. In addition, as to FC, interactions of SN with other networks including the default mode network and the central executive network were also observed mainly in the middle frontal gyrus and superior frontal gyrus in MCI and inferior frontal gyrus in aMCI. Conclusions: Specific functional alternations in SN and interactions of SN with other networks in MCI could be useful as potential imaging biomarkers for MCI or aMCI. Meanwhile, it provided a new insight in predicting the progression of health to MCI or aMCI and novel targets for proper intervention to delay the progression.