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. 2022 Sep;17(9):2014-2021.
doi: 10.4103/1673-5374.332161.

Abnormal characterization of dynamic functional connectivity in Alzheimer's disease

Cui Zhao  1 , Wei-Jie Huang  2 , Feng Feng  3 , Bo Zhou  4 , Hong-Xiang Yao  5 , Yan-E Guo  4 , Pan Wang  6 , Lu-Ning Wang  4 , Ni Shu  2 , Xi Zhang  4
Affiliations

Abnormal characterization of dynamic functional connectivity in Alzheimer's disease

Cui Zhao et al. Neural Regen Res. 2022 Sep.

Abstract

Numerous studies have shown abnormal brain functional connectivity in individuals with Alzheimer's disease (AD) or amnestic mild cognitive impairment (aMCI). However, most studies examined traditional resting state functional connections, ignoring the instantaneous connection mode of the whole brain. In this case-control study, we used a new method called dynamic functional connectivity (DFC) to look for abnormalities in patients with AD and aMCI. We calculated dynamic functional connectivity strength from functional magnetic resonance imaging data for each participant, and then used a support vector machine to classify AD patients and normal controls. Finally, we highlighted brain regions and brain networks that made the largest contributions to the classification. We found differences in dynamic function connectivity strength in the left precuneus, default mode network, and dorsal attention network among normal controls, aMCI patients, and AD patients. These abnormalities are potential imaging markers for the early diagnosis of AD.

Keywords: Alzheimer’s disease; amnestic mild cognitive impairment; blood oxygen level-dependent; default mode network; dynamic functional connectivity; frontoparietal network; resting-state functional magnetic resonance imaging; support vector machine.

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Conflict of interest statement

None

Figures

Figure 1
Figure 1
Patient flow chart. AD: Alzheimer's disease; aMCI: amnestic mild cognitive impairment; fMRI: functional magnetic resonance imaging; NC: normal control.
Figure 2
Figure 2
Process of dFCS calculation. (A) Raw fMRI. (B) Preprocessed fMRI. (C) Calculation of dFCS atlas using a sliding-window approach. (D) Final atlas of dFCS variance. dFCS: Dynamic functional connectivity strength; fMRI: functional magnetic resonance imaging.
Figure 3
Figure 3
Five-fold cross validation. The dataset was divided into five parts for 5-fold cross validation. One part was selected as the test dataset, while the remaining four parts were used as the training dataset. This was repeated five times so that each fold of the data was selected as a test set once, enabling us to obtain the predicted labels for all of the data. ‘b’ and ‘w’ in the figure are the parameters of the SVM. Different colored balls represent the samples with different labels.
Figure 4
Figure 4
The difference in dFCS among the NC, aMCI, and AD groups. (A) The voxel-based analysis revealed a difference in dFCS variance among the NC, aMCI, and AD groups in the left precuneus (red circle). (B) The NC group showed larger dFCS variance in the precuneus than the aMCI and AD groups. Data were analyzed using a two-tailed two-sample t-test. **P < 0.01; ***P < 0.001. AD: Alzheimer's disease; aMCI: amnestic mild cognitive impairment; dFCS: dynamic functional connectivity strength; L: left; NC: normal control R: right.
Figure 5
Figure 5
Correlations between the mean dFCS variance in the precuneus with MMSE (A) and MoCA (B) scores. Data were analyzed via partial correlation analysis. AD: Alzheimer's disease; aMCI: amnestic mild cognitive impairment; dFCS: dynamic functional connectivity strength; MMSE: Mini-Mental Status Examination; NC: normal control.
Figure 6
Figure 6
Correlations between decision value and MMSE (A) and MoCA (B) scores. Data were analyzed via partial correlation analysis. AD: Alzheimer's disease; aMCI: amnestic mild cognitive impairment; dFCS: dynamic functional connectivity strength; MMSE: Mini-Mental Status Examination; NC: normal control.
Figure 7
Figure 7
The weight of classifying the aMCI from the NC group. (A) The distribution of negative weight. (B) The distribution of positive weight. (C) The weight of different functional networks. (D) The normalized weight (by the volume of the functional network) of different functional weights. “Default” represents the default mode areas. aMCI: Amnestic mild cognitive impairment; L: left; NC: normal control; R; right.
Figure 8
Figure 8
The weight of classifying the AD from the NC group. (A) The distribution of negative weight. (B) The distribution of positive weight. (C) The weight of different functional networks. (D) The normalized weight (by the volume of the functional network) of different functional weights. AD: Alzheimer's disease; L: left; NC: normal control; R; right.
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