Network dynamics in post-stroke cognitive impairment: insights from effective connectivity analysis.

Area of Science:

• Neuroscience
• Cognitive Science
• Medical Imaging

Background:

• Post-stroke cognitive impairment (PSCI) is a significant challenge affecting quality of life.
• Understanding the neural mechanisms of PSCI is crucial for developing effective interventions.

Purpose of the Study:

• To investigate changes in effective connectivity (EC) within and between large-scale brain networks in patients with PSCI.
• To correlate altered EC with cognitive performance and lesion location.

Main Methods:

• Utilized spectral dynamic causal modeling (spDCM) on resting-state fMRI data from 41 PSCI patients and 41 healthy controls.
• Compared EC in default mode, executive control, dorsal attention, and salience networks.
• Correlated EC changes with cognitive test scores and performed subgroup analysis based on lesion location.

Main Results:

• PSCI patients exhibited significantly increased EC from the posterior cingulate cortex (PCC) to the left and right dorsolateral prefrontal cortex (L_DLPFC, R_DLPFC), and from the right insula to R_DLPFC.
• Increased EC was negatively correlated with cognitive scores.
• Subgroup analysis revealed enhanced executive control in PSCI patients with left anterior circulation lesions.

Conclusions:

• Findings suggest increased inter-network EC, particularly within the triple network model, contributes to PSCI pathophysiology.
• The PCC and R_DLPFC are implicated in the neural mechanisms underlying PSCI.
• This study highlights the importance of network-level analysis for understanding PSCI and developing targeted therapies.