Abnormal Dynamic Functional Networks in Subjective Cognitive Decline and Alzheimer's Disease

Abstract

Subjective cognitive decline (SCD) is considered to be the preclinical stage of Alzheimer's disease (AD) and has the potential for the early diagnosis and intervention of AD. It was implicated that CSF-tau, which increases very early in the disease process in AD, has a high sensitivity and specificity to differentiate AD from normal aging, and the highly connected brain regions behaved more tau burden in patients with AD. Thus, a highly connected state measured by dynamic functional connectivity may serve as the early changes of AD. In this study, forty-five normal controls (NC), thirty-six individuals with SCD, and thirty-five patients with AD were enrolled to obtain the resting-state functional magnetic resonance imaging scanning. Sliding windows, Pearson correlation, and clustering analysis were combined to investigate the different levels of information transformation states. Three states, namely, the low state, the middle state, and the high state, were characterized based on the strength of functional connectivity between each pair of brain regions. For the global dynamic functional connectivity analysis, statistically significant differences were found among groups in the three states, and the functional connectivity in the middle state was positively correlated with cognitive scales. Furthermore, the whole brain was parcellated into four networks, namely, default mode network (DMN), cognitive control network (CCN), sensorimotor network (SMN), and occipital-cerebellum network (OCN). For the local network analysis, statistically significant differences in CCN for low state and SMN for middle state and high state were found in normal controls and patients with AD. Meanwhile, the differences were also found in normal controls and individuals with SCD. In addition, the functional connectivity in SMN for high state was positively correlated with cognitive scales. Converging results showed the changes in dynamic functional states in individuals with SCD and patients with AD. In addition, the changes were mainly in the high strength of the functional connectivity state.

Keywords: Alzheimer's disease; clustering analysis; dynamic functional connectivity; resting-state fMRI; sensorimotor network; subjective cognitive decline.

Figure 1

The workflow of processing.

Figure 2

Variations of SSE with k and cluster centroids for different states in different groups. (A) A line plot between SSE (within-clusters sum of squared errors) vs. k (number of clusters). (B–D) The three FC states, namely, low state, middle state, and high state, of NC, SCD, and AD groups are shown in (B–D), respectively. The value in the matrix indicates the center of FC measured by Pearson correlation (Fisher's z-transformed) in each state.

Figure 3

Global differences among NC, SCD, and AD groups. (A) The top 5‰ (64/12720) functional connectivity of SMN in middle state. (B) The mean value of functional connectivity in each state. The statistically significant p-value is 0.01 (**) and Bonferroni corrected. (C,D) The plots of the mean value of functional connectivity in middle state vs. mean scores of the cognitive scales were shown in (C) for NC and SCD groups and in (D) for NC and AD groups. The statistically significant p-value is * < 0.05 or ** <0.01.

Figure 4

Local differences. The 160 ROIs were arranged along the circle. In each circle, the blue lines indicated the correlations between DMN and CCN (in the first column) or between DMN and SMN (in the second and third columns). The green lines indicated the correlations within CCN (in the first column) or between CCN and SMN (in the second and third columns). The purple lines indicated the correlations between SMN and CCN (in the first column) or within SMN (in the second and third columns). The orange lines indicated the correlations between OCN and CCN (in the first column) or between OCN and SMN (in the second and third columns). (A–C) In NC (A), SCD (B), and AD (C) groups, low state averaged FC between CCN and the other three networks (i.e., DMN, SMN, and OCN) was visualized. Similarly, middle state and high state averaged FC between SMN and the other three networks (i.e., DMN, CCN, and OCN) were visualized. For the visualization, the correlation coefficients larger than 0.4, 0.5, and 0.8 were shown in the first, second, and third column.

Figure 5

Local differences. (A) The statistically significant difference of the mean value of functional connectivity within four networks (i.e., DMN, CCN, SMN, and OCN) among groups (NC, SCD, and AD). The statistically significant p-value was 0.05 (*) or 0.01 (**) and Bonferroni corrected. The plots of the mean scores of the cognitive scales vs. the mean value of functional connectivity within SMN in middle state of NC and SCD groups, and SMN in high state of NC and SCD groups and NC and AD groups are shown in (B–D) respectively. The statistically significant p-value is (*) 0.05.