Resting-State Functional Connectivity and Scholastic Performance in Preadolescent Children: A Data-Driven Multivoxel Pattern Analysis (MVPA)

Daniel R. Westfall, Sheeba A. Anteraper, Laura Chaddock-Heyman, Eric S. Drollette, Lauren B. Raine, Susan Whitfield-Gabrieli, Arthur F. Kramer, Charles H. Hillman

Research output: Contribution to journalArticlepeer-review

Abstract

Scholastic performance is the key metric by which schools measure student’s academic success, and it is important to understand the neural-correlates associated with greater scholastic performance. This study examines resting-state functional connectivity (RsFc) associated with scholastic performance (reading and mathematics) in preadolescent children (7–9 years) using an unbiased whole-brain connectome-wide multi-voxel pattern analysis (MVPA). MVPA revealed four clusters associated with reading composite score, these clusters were then used for whole-brain seed-based RsFc analysis. However, no such clusters were found for mathematics composite score. Post hoc analysis found robust associations between reading and RsFc dynamics with areas involved with the somatomotor, dorsal attention, ventral attention, limbic, frontoparietal, and default mode networks. These findings indicate that reading ability may be associated with a wide range of RsFc networks. Of particular interest, anticorrelations were observed between the default mode network and the somatomotor, dorsal attention, ventral attention, and frontoparietal networks. Previous research has demonstrated the importance of anticorrelations between the default mode network and frontoparietal network associated with cognition. These results extend the current literature exploring the role of network connectivity in scholastic performance of children.
Original languageEnglish (US)
JournalJournal of Clinical Medicine
Volume9
Issue number10
DOIs
StatePublished - Oct 2 2020

Keywords

  • academic achievement
  • functional MRI
  • resting-state networks
  • reading

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