Topographic analysis of the development of individual activation patterns during performance monitoring in medial frontal cortex

Suzanne C. Perkins, Robert C. Welsh, Emily R. Stern, Stephan F. Taylor, Kate D. Fitzgerald

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Age-related improvements in human performance monitoring have been linked to maturation of medial frontal cortex (MFC) in healthy youth, however, imaging studies conflict regarding age-related changes in MFC activation patterns. Topographical analysis of single-subject activation enables measurement of variation in location of MFC activation by age, as well as other potentially influential factors (e.g., performance on task). In this study, 22 youth (ages 8-17 years) and 21 adults (ages 23-51 years) underwent functional magnetic resonance imaging during a performance monitoring task examining interference and errors. Single-subject factors (extent of MFC activation, age and accuracy) were entered into a three-level hierarchical linear model to test the influence of these characteristics on location of MFC activation. Activation shifted from a rostral/anterior to a more dorsal/posterior location with increasing age and accuracy during interference. Inclusion of age and accuracy accounted for almost all of the unexplained variance in location of interference-related activation within MFC. This pattern links improvement of performance-monitoring capacity to age-related increases in posterior MFC and decreases in anterior MFC activation. Taken together, these results show the maturation of performance monitoring capacity to depend on more focal engagement of posterior MFC substrate for cognitive control. AbbreviationsMFCmedial frontal cortexFCfrontal cortexMSITMultisource Interference TaskRTreaction timeLSlongitudinal splineRradius.

Original languageEnglish
Pages (from-to)137-148
Number of pages12
JournalDevelopmental Cognitive Neuroscience
Volume6
DOIs
StatePublished - 2013

Keywords

  • Cognitive control
  • Hierarchical linear modeling
  • Human development
  • Single subject activation
  • fMRI

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