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. 2021 Jan-Feb;44(1):9-16.
doi: 10.1097/WNF.0000000000000427.

Effects of Rivastigmine on Brain Functional Networks in Patients With Alzheimer Disease Based on the Graph Theory

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Effects of Rivastigmine on Brain Functional Networks in Patients With Alzheimer Disease Based on the Graph Theory

Jiangtao Zhang et al. Clin Neuropharmacol. 2021 Jan-Feb.

Abstract

Objective: The aim of this study was to explore the effect of rivastigmine on brain function in Alzheimer disease (AD) by analyzing brain functional network based on the graph theory.

Methods: We enrolled 9 patients with mild to moderate AD who received rivastigmine treatment and 9 healthy controls (HC). Subsequently, we used resting-state functional magnetic resonance imaging data to establish the whole-brain functional network using a graph theory-based analysis. Furthermore, we compared systemic and local network indicators between pre- and posttreatment.

Results: Patients with AD exhibited a posttreatment increase in the Mini-Mental State Examination scores and a decrease in the Alzheimer's Disease Assessment Scale cognitive subscale scores and activities of daily living. The systemic network for HC and patients with AD had good pre- and posttreatment clustering coefficients. There was no change in the Cp, Lp, Gamma, Lambda, and Sigma in patients with AD. There were no significant between-group differences in the pre- and posttreatment systemic network measures. Regarding the regional network, patients with AD showed increased betweenness centrality in the bilateral caudate nucleus and right superior temporal pole after treatment with rivastigmine. However, there was no between-group difference in the pre- and posttreatment betweenness centrality of these regions. There were no significant correlations between regional network measure changes and clinical score alterations in patients with AD.

Conclusions: There are similar systemic network properties between patients with AD and HC. Rivastigmine cannot alter systemic network attributes in patients with AD. However, it improves the topological properties of regional networks and between-node information transmission in patients with AD.

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Conflict of interest statement

Conflicts of Interest and Source of Funding: This work was funded by grants from the Medical Health Science and Technology Project of Zhejiang Provincial Health Commission (2015KYB073), the Traditional Chinese Medicine Technology Project of Zhejiang Province (2015ZA018) to Jiangtao Zhang, and the Project of Basic Public Welfare Research of Zhejiang (LGF18H090021) to Jianan Cheng. The authors have no conflicts of interest to declare.

Figures

FIGURE 1
FIGURE 1
Posttreatment changes in the clinical assessments. ADAT, patients with AD after treatment; ADBT, patients with AD before treatment.
FIGURE 2
FIGURE 2
Small-world property metrics as a function of sparsity thresholds. Regarding the defined threshold range, HC and patients with AD before and after treatment showed normalized clustering coefficients (Gamma) and small-worldness (Sigma) substantially greater than 1, and normalized characteristic path lengths (Lambda) approximately equal to 1. This was indicative of a typical small-world topology. ADAT, patients with AD after treatment; ADBT, patients with AD before treatment.
FIGURE 3
FIGURE 3
Changes in systemic network measures between the pre- and posttreatment measurements and between patients and controls. Error bars represent standard errors. ADAT, patients with AD after treatment; ADBT, patients with AD before treatment.
FIGURE 4
FIGURE 4
Changes in regional network measure between pre- and posttreatment measurements and between patients and controls. Error bars represent standard errors. ADAT, patients with AD after treatment; ADBT, patients with AD before treatment; L, left; R, right; TPOsup, superior temporal pole.

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