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

• Published in: Brain and behavior Vol. 12; no. 7; pp. e2646 - n/a
• Main Authors: Briggs, Robert G., Young, Isabella M., Dadario, Nicholas B., Fonseka, R. Dineth, Hormovas, Jorge, Allan, Parker, Larsen, Micah L., Lin, Yueh‐Hsin, Tanglay, Onur, Maxwell, B. David, Conner, Andrew K., Stafford, Jordan F., Glenn, Chad A., Teo, Charles, Sughrue, Michael E.
• Format: Journal Article
• Language: English
• Published: Los Angeles John Wiley & Sons, Inc 01.07.2022; John Wiley and Sons Inc; Wiley
• Subjects: anatomy; Brain research; Medical imaging; Meta-analysis; Network switching; Neural networks; Neuroimaging; Original; parcellation; salience network; tractography; Canada; Montreal Quebec Canada
• ISSN: 2162-3279; 2162-3279
• DOI: 10.1002/brb3.2646

Background The salience network (SN) is a transitory mediator between active and passive states of mind. Multiple cortical areas, including the opercular, insular, and cingulate cortices have been linked in this processing, though knowledge of network connectivity has been devoid of structural specificity. Objective The current study sought to create an anatomically specific connectivity model of the neural substrates involved in the salience network. Methods A literature search of PubMed and BrainMap Sleuth was conducted for resting‐state and task‐based fMRI studies relevant to the salience network according to PRISMA guidelines. Publicly available meta‐analytic software was utilized to extract relevant fMRI data for the creation of an activation likelihood estimation (ALE) map and relevant parcellations from the human connectome project overlapping with the ALE data were identified for inclusion in our SN model. DSI‐based fiber tractography was then performed on publicaly available data from healthy subjects to determine the structural connections between cortical parcellations comprising the network. Results Nine cortical regions were found to comprise the salience network: areas AVI (anterior ventral insula), MI (middle insula), FOP4 (frontal operculum 4), FOP5 (frontal operculum 5), a24pr (anterior 24 prime), a32pr (anterior 32 prime), p32pr (posterior 32 prime), and SCEF (supplementary and cingulate eye field), and 46. The frontal aslant tract was found to connect the opercular‐insular cluster to the middle cingulate clusters of the network, while mostly short U‐fibers connected adjacent nodes of the network. Conclusion Here we provide an anatomically specific connectivity model of the neural substrates involved in the salience network. These results may serve as an empiric basis for clinical translation in this region and for future study which seeks to expand our understanding of how specific neural substrates are involved in salience processing and guide subsequent human behavior. This study provides a detailed model of the salience network (SN) based on its structural and functional connectivity within an anatomically specific parcellation scheme. A coordinate‐based meta‐analysis of the literature and subsequent tractographic analysis on identified regions demonstrate that the SN comprises three clusters of interconnected cortical regions that are extensively connected with both frontal aslant tract fibers and short local association fibers, generally forming a large cingulate and insular‐opercular system. These results may serve as an empirical basis for clinical translation in this region and for future studies that seek to expand our understanding of how specific neural substrates are involved in salience processing and guide subsequent human behavior.