Effective Connectivity of Default Mode Network Subsystems in Parkinson's Disease with Mild Cognitive Impairment Based on Spectral Dynamic Causal Modeling.

OBJECTIVE

The objective of this study is to compare the differences in effective connectivity within the default mode network (DMN) subsystems between patients with Parkinson's disease with mild cognitive impairment (PD-MCI) and patients with Parkinson's disease with normal cognition (PD-CN). The mechanisms underlying DMN dysfunction in PD-MCI patients and its association with clinical cognitive function in PD-MCI are aimed to be investigated.

METHODS

The spectral dynamic causal model (spDCM) was employed to analyze the effective connectivity of functional magnetic resonance imaging (fMRI) data in the resting state for the DMN subsystems, which include the medial prefrontal cortex (MPFC), posterior cingulate cortex (PCC), left and right angular gyrus (LAG, RAG) in 23 PD-MCI and 22 PD-CN patients, respectively. The effective connectivity values of DMN subsystems in the two groups were statistically analyzed using a two-sample t-test. The Spearman correlation analysis was used to test the correlation between the effective connectivity values of the subsystems with significant differences between the two groups and the clinical cognitive function (as measured by Montreal Cognitive Assessment Scale (MoCA) score).

RESULTS

Statistical analysis revealed significant differences in the effective connections of MPFC-LAG and LAG-PCC between the two patient groups (MPFC-LAG: t = -2.993, p < 0.05; LAG-PCC: t = 2.174, p < 0.05).

CONCLUSIONS

The study findings suggest that abnormal strength and direction of effective connections between DMN subsystems are found in PD-MCI patients.