Abnormal static and dynamic functional connectivity of resting-state fMRI in multiple system atrophy

Area of Science:

• Neuroscience
• Medical Imaging
• Network Science

Background:

• Multiple System Atrophy (MSA) is a neurodegenerative disease with complex pathophysiology.
• Understanding alterations in functional brain networks is crucial for diagnosing and managing MSA.
• Current research often focuses on static brain connectivity, potentially missing dynamic changes.

Purpose of the Study:

• To investigate topological alterations in functional brain networks of MSA patients compared to healthy controls (HC).
• To propose and validate a novel joint analysis method for static and dynamic functional connectivity (FC).
• To explore the diagnostic potential of brain network features in MSA.

Main Methods:

• Utilized resting-state functional magnetic resonance imaging (rs-fMRI) data from 24 MSA patients and 20 HCs.
• Constructed static and dynamic brain networks and calculated graph theory attributes (e.g., LE, WD, BC).
• Performed statistical comparisons, correlation analysis with UMSARS scores, and Receiver Operating Characteristic (ROC) analysis.

Main Results:

• Both static and dynamic analyses revealed decreased local efficiency (LE) and weighted degree (WD) in the cerebellum.
• Static FC showed increased betweenness centrality (BC) in the prefrontal cortex and cerebellum.
• Dynamic FC analysis identified decreased BC, clustering coefficients, and LE in cortical and cerebellar regions; dynamic features showed higher diagnostic accuracy.

Conclusions:

• The study provides evidence for disrupted dynamic disconnection syndrome in MSA.
• Both static and dynamic functional connectivity alterations are present in MSA.
• Dynamic FC features demonstrate significant potential for MSA diagnosis and disease progression monitoring using rs-fMRI.