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.
Highlights
There is growing evidence that the human brain is a largescale complex network (Seeley et al, 2009; Betzel et al, 2012)
The specific areas of discrepant network properties of mild cognitive impairment (MCI) patients and normal cognition patients (NC) are listed in Table 3 and Figure 1, including the left middle frontal gyrus, right rectus, right superior parietal gyrus, right inferior parietal gyrus, and left paracentral lobule
We found a lower egocentric navigation accuracy in MCI patients compared to NCs
Summary
There is growing evidence that the human brain is a largescale complex network (Seeley et al, 2009; Betzel et al, 2012). The global efficiency of a network (Eg) is measured by how information is exchanged over the network, meaning that how efficient the communication is between one brain region to another, and the local efficiency (Eloc) reflects the average efficiency of each local cluster of the network. The white matter structural networks in the healthy human brain usually exhibit a small-world character, which can optimally balance information segregation and integration, resulting in efficient organization that reduces the cost of maintaining many connections and allows for efficient information movement (Gong et al, 2009). Patients with Alzheimer’s disease (AD) dementia and mild cognitive impairment (MCI) showed abnormal properties of cortical networks and loss of small-world characteristics in previous studies that reported either local or global structural connectivity disruptions in these patients (Shu et al, 2012)
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