Parcellation-based tractographic modeling of the salience network through meta-analysis

Area of Science:

• Neuroscience
• Cognitive Neuroscience
• Neuroimaging

Background:

• The salience network (SN) integrates active and passive cognitive states.
• Previous research identified cortical areas in the SN but lacked structural specificity in connectivity.
• Understanding SN's precise neural architecture is crucial for cognitive function.

Purpose of the Study:

• To develop an anatomically specific connectivity model of the neural substrates within the salience network.
• To elucidate the structural connections between key cortical regions of the SN.
• To provide a foundation for clinical translation and further research into salience processing.

Main Methods:

• Conducted a PRISMA-guided literature search of fMRI studies on the salience network.
• Utilized meta-analytic software to create an activation likelihood estimation (ALE) map.
• Employed DSI-based fiber tractography on Human Connectome Project data to map structural connections.

Main Results:

• Identified nine core cortical regions forming the salience network.
• The frontal aslant tract connects the opercular-insular and middle cingulate clusters.
• Short U-fibers predominantly connect adjacent network nodes.

Conclusions:

• Anatomically specific connectivity model of the salience network is presented.
• Findings offer an empirical basis for clinical applications and future research.
• This model enhances understanding of neural substrates in salience processing and behavior guidance.