Network-based statistics reveals an enhanced subnetwork in prefrontal cortex in mild cognitive impairment: a functional near-infrared spectroscopy study

基于网络统计的研究表明,轻度认知障碍患者的前额叶皮层子网络增强:一项功能性近红外光谱研究

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Abstract

BACKGROUND: Mild cognitive impairment (MCI) is generally considered to have a high risk of progression to Alzheimer's disease. Our study aimed to investigate the abnormal functional connectivity (FC) in prefrontal cortex (PFC) in patients with MCI and explore the relationship between the observed changes and cognitive function. METHODS: Sixty-seven patients with MCI and 71 healthy individuals were recruited for this study. All participants underwent the Montreal Cognitive Assessment (MoCA) and functional near-infrared spectroscopy (fNIRS) examinations. RESULTS: Compared with healthy controls (HC), the patients with MCI exhibited significantly lower MoCA scores (p < 0.001). Through FC analysis, an enhanced subnetwork was observed in the right prefrontal cortex of the MCI group, covering four pairs of channel connections: CH12-CH15, CH12-CH16, CH13-CH15, and CH13-CH16. Moreover, the FC values of these four channel pairs and the education duration were significantly correlated with MoCA scores. Subsequently, a multiple linear regression model was performed to observe the independent factors of cognition decline, serving the education duration and the average FC values of subnetwork as independent variables and the MoCA scores as the dependent variable. The regression model showed a total of 25.7% explanation power (adjusted R(2) = 0.257, F = 24.723, p < 0.001). CONCLUSION: Our study suggested that the enhanced subnetwork within the right PFC may be involved in the pathophysiology of MCI and serve as a potential target for the treatment of MCI.

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