The mechanism underlying memory impairment caused by white matter lesions of cerebral small vessel disease is still unclear. The disrupted synchronization of gamma oscillations in the prefrontal-hippocampal circuit is a potential key mechanism. Our study has demonstrated that white matter lesions lead to demyelination of the connection tracts between the prefrontal lobe and hippocampus, which is closely related to memory dysfunction. However, further studies are required to explore if these microstructural changes in white matter tracts influence memory function by affecting gamma oscillations. Thus, this project will use the previously established episodic memory task and event-related potential to determine the changes in gamma oscillations in the prefrontal-hippocampal circuit and the effects on memory encoding and retrieval. Combining multimodal imaging, we will explore the mediating role of white matter microstructure damage, and establish a machine learning prediction model for memory impairment. In addition, transcranial alternation current stimulation (tACS) will be used to investigate the mechanisms of memory improvement by regulating the prefrontal-hippocampal gamma oscillations. This project will clarify the neural oscillation mechanism underlying memory impairment caused by white matter lesions of cerebral small vessel disease, with the expectation of providing new predictive indicators and interventions.
Study Type
OBSERVATIONAL
Enrollment
150
Xuanwu Hospital Capital Medical University
Beijing, Beijing Municipality, China
RECRUITINGOverall cognitive function
Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MOCA) scale scores.
Time frame: baseline and one-year follow-up
Attention and executive functions
the scores are evaluated using the Clock Drawing Test (CDT), the Digit Span Test (DST), and the Trail Making Test (TMT).
Time frame: Baseline and follow up
Language function
Boston Naming Test (BNT)
Time frame: Baseline and one-year follow up
Memory function
Digit Span Test (DST) and the WHO-UCLA Auditory Verbal Learning Test (AVLT).
Time frame: Baseline and one-year follow up
Brain imaging data
Based on DTI data, the following metrics can be extracted: Fractional Anisotropy (FA) Mean Diffusivity (MD) Axial Diffusivity (AD) Radial Diffusivity (RD)
Time frame: baseline and one-year follow-up
Electroencephalogram (EEG) data.
Based on EEG data, time-frequency analysis and cross-frequency coupling analysis can be performed to extract the following metrics: Theta Band Neural Oscillation Energy Theta-Gamma Coupling Strength
Time frame: baseline and one-year follow-up
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