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. 2021 Jun 3:13:630677.
doi: 10.3389/fnagi.2021.630677. eCollection 2021.

Disrupted Network Topology Contributed to Spatial Navigation Impairment in Patients With Mild Cognitive Impairment

Affiliations

Disrupted Network Topology Contributed to Spatial Navigation Impairment in Patients With Mild Cognitive Impairment

Weiping Li et al. Front Aging Neurosci. .

Abstract

Impairment in spatial navigation (SN) and structural network topology is not limited to patients with Alzheimer's disease (AD) dementia and can be detected earlier in patients with mild cognitive impairment (MCI). We recruited 32 MCI patients (65.91 ± 11.33 years old) and 28 normal cognition patients (NC; 69.68 ± 10.79 years old), all of whom underwent a computer-based battery of SN tests evaluating egocentric, allocentric, and mixed SN strategies and diffusion-weighted and T1-weighted Magnetic Resonance Imaging (MRI). To evaluate the topological features of the structural connectivity network, we calculated its measures such as the global efficiency, local efficiency, clustering coefficient, and shortest path length with GRETNA. We determined the correlation between SN accuracy and network topological properties. Compared to NC, MCI subjects demonstrated a lower egocentric navigation accuracy. Compared with NC, MCI subjects showed significantly decreased clustering coefficients in the left middle frontal gyrus, right rectus, right superior parietal gyrus, and right inferior parietal gyrus and decreased shortest path length in the left paracentral lobule. We observed significant positive correlations of the shortest path length in the left paracentral lobule with both the mixed allocentric-egocentric and the allocentric accuracy measured by the average total errors. A decreased clustering coefficient in the right inferior parietal gyrus was associated with a larger allocentric navigation error. White matter hyperintensities (WMH) did not affect the correlation between network properties and SN accuracy. This study demonstrated that structural connectivity network abnormalities, especially in the frontal and parietal gyri, are associated with a lower SN accuracy, independently of WMH, providing a new insight into the brain mechanisms associated with SN impairment in MCI.

Keywords: clustering coefficient; graph theory; mild cognitive impairment; network topology; spatial navigation.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Graphs show differences in the nodal network topological properties between the patients with MCI and normal controls. (A) The location of the node with significantly altered nodal network topological properties in MCI patients, compared with normal controls. (B–E) The nodal clustering coefficients in the left MFG (p = 0.020), right REC (p = 0.023), right SPG (p = 0.034), and right IPL (p = 0.009) were significantly different between the patients with MCI and normal controls. (F) The nodal shortest path length in the left PCL (p = 0.045) was significantly different between the patients with MCI and normal controls. NC, normal controls; MCI, mild cognitive impairment; L, left; R, right; Cp, local clustering coefficient; Lp, local shortest path length; MFG, middle frontal gyrus; REC, rectus; SPG, superior parietal gyrus; IPL, inferior parietal gyrus; PCL, paracentral lobule.

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