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The corticocortical vestibular network (CVN) plays an important role in maintaining balance and stability. In order to clarify the specific relationship between the CVN and the balance ability of patients with mild cognitive impairment (MCI), we recruited 30 MCI patients in the community. According to age and sex, they were 1:1 matched to 30 older adults with normal cognitive function. We evaluated balance ability and performed MRI scanning in the two groups of participants. We analyzed functional connectivity within the CVN based on the region of interest. Then, we performed a Pearson correlation analysis between the functional connection and the Berg Balance Scale scores. The research results show that compared with the control group, there were three pairs of functional connections (hMST_R–Premotor_R, PFcm_R–SMA_L, and hMST_L–VIP_R) that were significantly decreased in the CVNs of the MCI group (p < 0.05). Further correlation analysis showed that there was a significant positive correlation between hMST_R–Premotor_R functional connectivity and BBS score (r = 0.364, p = 0.004). The decline in balance ability and increase in fall risk in patients with MCI may be closely related to the change in the internal connection mode of the corticocortical vestibular network. [ABSTRACT FROM AUTHOR]

Mild cognitive impairment (MCI) is one of the important comorbidities of type 2 diabetes mellitus (T2DM). It is critical to find appropriate methods for early diagnosis and objective assessment of mild cognitive impairment patients with type 2 diabetes (T2DM-MCI). Our study aimed to investigate potential early alterations in phase lag index (PLI) and determine whether it can distinguish between T2DM-MCI and normal controls with T2DM (T2DM-NC). EEG was recorded in 30 T2DM-MCI patients and 30 T2DM-NC patients. The phase lag index was computed and used in a logistic regression model to discriminate between groups. The correlation between the phase lag index and Montreal Cognitive Assessment (MoCA) score was assessed. The α-band phase lag index was significantly decreased in the T2DM-MCI group compared with the T2DM-NC group and showed a moderate degree of classification accuracy. The MoCA score was positively correlated with the α-band phase lag index (r = 0.4812, moderate association, p = 0.015). This work shows that the functional connectivity analysis of EEG may offer an effective way to track the cortical dysfunction linked to the cognitive deterioration of T2DM patients, and the α-band phase lag index may have a role in guiding the diagnosis of T2DM-MCI. [ABSTRACT FROM AUTHOR]