Abnormal dynamic functional connectivity is linked to recovery after acute ischemic stroke

Area of Science:

• Neuroscience
• Radiology
• Medical Imaging

Background:

• Acute ischemic stroke (AIS) significantly impacts brain function.
• Understanding dynamic functional connectivity (dFC) is crucial for assessing stroke severity and recovery.
• Resting-state functional MRI (rs-fMRI) offers insights into brain network alterations.

Purpose of the Study:

• To investigate whole-brain dFC patterns in AIS patients.
• To correlate dFC with short-term and long-term stroke severity.
• To explore the predictive capacity of dFC for stroke outcomes.

Main Methods:

• rs-fMRI data from 41 AIS patients were analyzed using a sliding window approach and k-means clustering.
• Dynamic connectivity configurations were identified and compared across stroke severity groups (NIHSS scores).
• Bayesian hierarchical models and correlation analyses assessed the relationship between dFC, clinical measures, and neurological recovery (ΔNIHSS).

Main Results:

• Three distinct dFC configurations were identified acutely post-stroke.
• Severely affected patients exhibited prolonged engagement with a specific dFC state characterized by isolated functional domains.
• dFC patterns predicted stroke severity and were significantly correlated with 90-day neurological recovery, particularly involving default mode network components.

Conclusions:

• Dynamic functional connectivity alterations are evident in acute ischemic stroke.
• Specific dFC states are associated with stroke severity and can predict outcomes.
• dFC, especially involving default mode network, is a significant correlate of early neurological recovery post-stroke.