Analysis of brain dynamics changes in patients with cerebral small vessel disease-related cognitive impairment based on electroencephalogram microstates.

OBJECTIVE

Cognitive dysfunction is one of the main clinical features in patients with cerebral small vessel disease (CSVD). Over time, cognitive decline related to CSVD might evolve into dementia. This study aims to explore the changes in brain functional networks of CSVD patients with cognitive impairment through microstate analysis of resting-state electroencephalogram, and to investigate the association between these changes and cognitive dysfunction.

METHODS

A cohort of 42 CSVD patients from the Department of Neurology at the Third People's Hospital of Mianyang City was recruited between September 2023 and March 2024, constituting the CSVD group. Concurrently, 40 individuals who underwent health checkups served as the control group (HC group). Both groups underwent neuropsychological assessments and 19-channel video EEG recordings. EEG data were analyzed using the MICROSTATELAB 1.0 toolbox to identify microstates. Four microstate prototypes (Ms) were derived, and their temporal characteristics were compared across groups. Moreover, correlations between these characteristics and neuropsychological scale scores were examined.

RESULTS

1. Neuropsychological assessments indicated that the CSVD group scored significantly lower than the HC group in general cognitive level, memory, visuospatial ability, executive function, and language function (p < 0.05). 2. In resting-state EEG microstate analysis, the CSVD group exhibited significantly lower appearance rates for MsA, MsB, MsC, and MsD compared to the HC group (p = 0.014, p = 0.047, p = 0.014, p = 0.02). Durations of MsB, MsC, and MsD were prolonged in the CSVD group (p = 0.014, p = 0.037, p = 0.036). Furthermore, the MsC to MsA transition rate was significantly reduced in the CSVD group (p = 0.036). 3. Correlation analysis within the CSVD group revealed several significant relationships. The MsD to MsC transition rate was negatively correlated with the AD8 score (p = 0.049, r =  - 0.309). The MsD occurrence rate was negatively correlated with the FAQ score (p = 0.039, r =  - 0.324). The MsA to MsC transition rate was positively correlated with the FAQ score (p = 0.038, r = 0.326). The MsD occurrence rate was positively correlated with MMSE (p = 0.027, r = 0.345). The MsA to MsB transition rate was negatively correlated with MMSE (p = 0.041, r =  - 0.321). The MsB duration was negatively correlated with DST scores (p = 0.027, r =  - 0.345). The MsD occurrence was positively correlated with BNT scores (p = 0.031, r = 0.338). MsA coverage, MsA to MsB transition rate, and MsB to MsA transition rate were negatively correlated with Stroop C scores [(p = 0.019, r =  - 0.364), (p = 0.01, r =  - 0.399), (p = 0.022, r =  - 0.358)]. The MsC to MsD transition rate and MsD to MsC transition rate were positively correlated with the Stroop C score [(p = 0.014, r = 0.381), (p = 0.01, r = 0.397)].

CONCLUSION

The CSVD group demonstrated increased stability in brain functional networks but reduced inter-network interaction capabilities. Network activities related to MsA and MsB were enhanced, while those related to MsC were diminished. Abnormal changes in microstates were correlated with cognitive deficits in CSVD patients, suggesting that microstate alterations could serve as potential biomarkers for CSVD-related cognitive impairment.