Development of Network Topology and Functional Connectivity of the Prefrontal Cortex. (6th December 2019)

• Record Type: Journal Article
• Authors: Lopez, Katherine C; Kandala, Sridhar; Marek, Scott; Barch, Deanna M
• Is Part Of: Cerebral cortex. Volume 30:Number 4(2020)
• Page Start: 2489
• Page End: 2505
• Publication Date: 2019-12-06
• Subjects: graph theory -- hubs -- large-scale networks; Cerebral cortex -- Periodicals; Brain -- Periodicals; 612.825
• DOI: 10.1093/cercor/bhz255
• Languages: English
• ISSNs: 1047-3211

Abstract

Abstract: The prefrontal cortex (PFC) comprises distinct regions and networks that vary in their trajectories across development. Further understanding these diverging trajectories may elucidate the neural mechanisms by which distinct PFC regions contribute to cognitive maturity. In particular, it remains unclear whether PFC regions of distinct network affiliations differ in topology and their relationship to cognition. We examined 615 individuals (8–21 years) to characterize age-related effects in participation coefficient of 28 PFC regions of distinct networks, evaluating connectivity profiles of each region to understand patterns influencing topological maturity. Findings revealed that PFC regions of attention, frontoparietal, and default mode networks (DMN) displayed varying rates of decline in participation coefficient with age, characterized by stronger connectivity with each PFC's respective network; suggesting that PFC regions largely aid network segregation. Conversely, PFC regions of the cinguloopercular/salience network increased in participation coefficient with age, marked by stronger between-network connections, suggesting that some PFC regions feature a distinctive ability to facilitate network integration. PFC topology of the DMN, in particular, predicted improvements in global cognition, including motor speed and higher order abilities. Together, these findings elucidate systematic differences in topology across PFC regions of different network affiliation, representing important neural signatures of typical brain development.