Topography Impacts Topology: Anatomically Central Areas Exhibit a "high-Level Connector" Profile in the Human Cortex

Jiahe Zhang, Lianne H. Scholtens, Yongbin Wei, Martijn P. Van Den Heuvel, Lorena Chanes, Lisa Feldman Barrett*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Degree centrality is a widely used measure in complex networks. Within the brain, degree relates to other topological features, with high-degree nodes (i.e., hubs) exhibiting high betweenness centrality, participation coefficient, and within-module z-score. However, increasing evidence from neuroanatomical and predictive processing literature suggests that topological properties of a brain network may also be impacted by topography, that is, anatomical (spatial) distribution. More specifically, cortical limbic areas (agranular and dysgranular cortices), which occupy an anatomically central position, have been proposed to be topologically central and well suited to initiate predictions in the cerebral cortex. We estimated anatomical centrality and showed that it positively correlated with betweenness centrality, participation coefficient, and communicability, analogously to degree. In contrast to degree, however, anatomical centrality negatively correlated with within-module z-score. Our data suggest that degree centrality and anatomical centrality reflect distinct contributions to cortical organization. Whereas degree would be more related to the amount of information integration performed by an area, anatomical centrality would be more related to an area's position in the predictive hierarchy. Highly anatomically central areas may function as "high-level connectors," integrating already highly integrated information across modules. These results are consistent with a high-level, domain-general limbic workspace, integrated by highly anatomically central cortical areas.

Original languageEnglish
Pages (from-to)1357-1365
Number of pages9
JournalCerebral Cortex
Volume30
Issue number3
DOIs
Publication statusPublished - 14 Mar 2020

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