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Clarifying the longitudinal factor structure, temporal stability, and construct validity of Go/No-Go task-related neural activation across adolescence and young adulthood

  • K. J. Paige
  • , C. R. Colder
  • , L. M. Cope
  • , J. E. Hardee
  • , M. M. Heitzeg
  • , M. E. Soules
  • , A. S. Weigard
  • SUNY Buffalo
  • University of Michigan, Ann Arbor

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

This study aimed to clarify the psychometric properties and development of Go/No-Go (GNG) task-related neural activation across critical periods of neurobiological maturation by examining its longitudinal stability, factor structure, developmental change, and associations with a computational index of task-general cognitive control. A longitudinal sample (N=289) of adolescents from the Michigan Longitudinal Study was assessed at four time-points (mean number of timepoints per participant=2.05; standard deviation=0.89) spanning early adolescence (ages 10−13) to young adulthood (22−25). Results suggested that regional neural activations from the “successful inhibition” (SI>GO) and “failed inhibition” (FI>GO; error-monitoring) contrasts are each described well by a single general factor. Neural activity across both contrasts showed developmental increases throughout adolescence that plateau in young adulthood. Neural activity metrics evidenced low temporal stability across this period of marked developmental change, and the SI>GO factor showed no relations with a behavioral index of cognitive control. The FI>GO factor displayed stronger criterion validity in the form of significant, positive associations with behaviorally measured cognitive control. Findings emphasize the utility of well-validated psychometric methods and longitudinal data for clarifying the measurement properties of functional neuroimaging metrics and improving measurement practices in developmental cognitive neuroscience.

Original languageEnglish
Article number101390
JournalDevelopmental Cognitive Neuroscience
Volume67
DOIs
StatePublished - Jun 2024

Keywords

  • Cognitive control
  • Computational psychiatry
  • Diffusion decision model
  • Error-monitoring systems
  • Inhibitory control

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