Functional connectivity in a triple-network saliency model is associated with real-life self-control

Area of Science:

• Neuroscience
• Cognitive Psychology
• Brain Imaging

Background:

• The neurocognitive mechanisms underlying real-life self-control are not fully understood.
• Previous research primarily focused on task-related brain activity, neglecting functional connectivity between large-scale brain networks.

Purpose of the Study:

• To investigate the association between functional connectivity of large-scale brain networks and real-life self-control.
• To test the hypothesis that cross-network interactions involving the salience network (SN), central executive network (CEN), and default mode network (DMN) predict self-control.

Main Methods:

• Utilized a saliency-based triple-network model of cognitive control.
• Collected task-free functional magnetic resonance imaging (fMRI) data from a large community sample (N=294).
• Employed ecological momentary assessment to measure daily self-control and calculated a SN-centered network interaction index (NII).

Main Results:

• Higher NII scores were significantly associated with increased real-life self-control.
• Demonstrated a link between intrinsic inter-network organization and everyday self-regulatory behavior.

Conclusions:

• The findings support the role of the salience network (SN) in mediating self-control by facilitating switching between the default mode network (DMN) and central executive network (CEN).
• Highlights the importance of functional connectivity and network interactions for understanding real-life self-control.