Bayesian network analysis revealed the connectivity difference of the default mode network from the resting-state to...

Area of Science:

• Neuroscience
• Cognitive Neuroscience
• Brain Imaging

Background:

• Functional magnetic resonance imaging (fMRI) studies identified the default mode network (DMN).
• The DMN shows co-activation during rest and co-deactivation during attention-demanding tasks.
• Understanding DMN's dynamic connectivity is crucial for cognitive function research.

Purpose of the Study:

• To construct a directed effective connectivity model of the DMN using Bayesian network (BN) analysis.
• To compare the DMN's organizational architecture and interregional directed connections between resting-state and task-state.
• To investigate how DMN structure and function adapt to different cognitive demands.

Main Methods:

• Bayesian network (BN) analysis was employed to model DMN effective connectivity.
• Directed connections within the DMN were analyzed under both resting-state and task-state conditions.
• Comparison of network architecture and connection strength across different brain states.

Main Results:

• The DMN consistently organized into two interacting subsystems in both resting and task states.
• Significant changes were observed in directed connections between DMN regions from resting-state to task-state.
• The intrinsic structure of the DMN remained relatively stable across conditions.

Conclusions:

• The default mode network (DMN) exhibits a stable underlying structure irrespective of cognitive state.
• Information processing mechanisms within the DMN are state-dependent, showing dynamic changes in connectivity.
• BN analysis provides insights into the directed functional architecture of the DMN during different cognitive demands.