Investigating the functional heterogeneity of the default mode network using coordinate-based meta-analytic modeling

Area of Science:

• Neuroscience
• Cognitive Neuroscience
• Brain Imaging

Background:

• The default mode network (DMN) is known for intrinsic resting-state activity and task-related decreases.
• However, DMN regions also show task-related increases, often masked by traditional analysis methods.
• Understanding the full functional repertoire of the DMN is crucial for comprehending brain function.

Purpose of the Study:

• To identify core regions of the DMN and investigate their functional heterogeneity.
• To develop a DMN connectivity model based on task-related increases in activity.
• To reveal specialized subnetworks within the DMN and their associated behavioral domains.

Main Methods:

• Utilized activation likelihood estimation (ALE) for meta-analysis of neuroimaging results.
• Generated meta-analytic coactivation maps for individual DMN regions.
• Analyzed behavioral domain metadata from the BrainMap database to assess functional properties.

Main Results:

• Identified core DMN regions and their functional heterogeneity through meta-analysis.
• Developed a DMN connectivity model illustrating task-related interaction patterns.
• Discovered distinct subnetworks (cliques) within the DMN with specialized functions, including affective, perceptual, and reduced motor processing.

Conclusions:

• The default mode network exhibits significant functional specialization across different subnetworks.
• Task-related increases in DMN activity reveal a more complex functional organization than previously understood.
• This research provides a novel framework for understanding DMN connectivity and its role in diverse cognitive and behavioral processes.