Effective Connectivity within the Default Mode Network: Dynamic Causal Modeling of Resting-State fMRI Data

Area of Science:

• Neuroscience
• Cognitive Neuroscience
• Brain Imaging

Background:

• The Default Mode Network (DMN) is crucial for internal cognitive processes during rest.
• Current methods often measure BOLD signal associations, limiting causal inference of DMN interactions.
• Existing studies on DMN effective connectivity yield inconsistent results.

Purpose of the Study:

• To identify stable causal connectivity patterns among key Default Mode Network regions.
• To investigate the driving role of specific DMN regions in resting-state brain function.

Main Methods:

• Utilized resting-state fMRI data from 30 healthy subjects.
• Applied spectral dynamic causal modeling (DCM) to analyze effective connectivity.
• Modeled endogenous brain fluctuations using Discrete Cosine Set (0.0078-0.1 Hz).

Main Results:

• The optimal group-level model showed significant, symmetrical connections from bilateral IPC to mPFC and PCC (p < 0.05).
• mPFC-PCC connections were bidirectional and weaker than those from the IPC.
• Connections originating from the LIPC/RIPC to other DMN regions were consistently stronger.

Conclusions:

• The bilateral intraparietal cortex (IPC) exerts a significant driving influence within the DMN.
• Findings provide new insights into the causal relationships and resting-state dynamics of the DMN.
• Results support and extend previous research on DMN effective connectivity.