A Three-Year Longitudinal Functional Magnetic Resonance Imaging Study of Performance Monitoring and Test-Retest Reliability from Childhood to Early Adulthood

Abstract

Previous cross-sectional functional magnetic resonance imaging studies have shown that performance monitoring functions continue to develop well into adolescence, associated with increased activation in brain regions important for cognitive control (prefrontal cortex, anterior cingulate cortex, and parietal cortex). To date, however, the development of performance monitoring has not yet been studied longitudinally, which leaves open the question whether changes can be detected within individuals over time. In the present study, human boys and girls, between ages 8 and 27 years, performed a child-friendly rule-switch task in the scanner on two occasions ϳ3.5 years apart. Change versus stability was examined using two methods: (1) repeated-measures analyses and (2) test-retest reliabilities of blood oxygenation level-dependent responses. Results showed that with increasing age, participants performed better on the task. The changes in neural activation associated with the processing of performance feedback were, however, more reliably correlated with changes in performance than with age. Test-retest reliability was at least fair to good for adults and adolescents, but poor to fair for the youngest age group. Substantially more variability was observed in the pattern and magnitude of children compared with adults, which may be interpreted as proxy for developmental change. Together, the results show that (1) change within individuals is variable, and more so for children than for adolescents and adults, and (2) performance is a better predictor for change in neural activation over time. These findings set the stage for studying developmental change in the perspective of multiple predictors, rather than solely by divisions based on age groups.

Behavioral and neural stability of attention bias to threat in healthy adolescents

“…Koolschijn et al, 2011; Ordaz et al, 2013). In the current study, post-hoc analyses were conducted to examine whether there was adequate reliability in the younger children.…”

“…Moreover, behavioral data in youth link attention bias to anxiety vulnerability (Pérez-Edgar et al, 2011; Shechner et al, 2012; White et al, in press), which creates a further need. Finally, in the few fMRI reliability studies conducted in children and adolescents, reliability estimates appear to be significantly lower in youth than adults (Koolschijn et al, 2011; Ordaz et al, 2013). Thus, understanding the reliability of neural activation associated with this behavioral vulnerability factor in child and adolescent populations is important.…”

“…However, to date, no study examines test-retest reliability of task-based fronto-amygdala connectivity. Moreover, across various other task-based indices of activation, divergent reliability estimates emerge in youth (e.g., Koolschijn, Schel, Rooij, Rombouts, & Crone, 2011) and adults (e.g Sauder et al, 2013). For example, intraclass correlation coefficients (ICCs) for PFC activation vary widely across children and adolescents (e.g., ICCs: 0.07 – 0.62, Koolschijn et al, 2011; ICCs: 0.15 – 0.43, Ordaz, Foran, Velanova, & Luna, 2013; ICCs: 0.17 – 0.56, van den Bulk et al, 2013) and adults (e.g., ICCs: 0.37 – 0.66, Koolschijn et al, 2011; ICCs: 0.15 – 0.55, Plichta et al, 2012) with few estimates falling in the “good” (ICCs of 0.6 – 0.74) or “excellent” (ICCs > 0.75) range (Cicchetti, 2001).…”

Progress toward openness, transparency, and reproducibility in cognitive neuroscience

“…Researchers continue to take seriously the effort to systematically measure the factors that influence test/ retest reliability of responses across time and tasks, and these sorts of studies are increasingly common [83][84][85][86][87][88] . Other research programs focus on addressing questions about the long-term within-subject stability of responses [89][90] , and how the accurate assessment of within-participant differences might address questions about individual differences 93 .…”

Activation in Context: Differential Conclusions Drawn from Cross-Sectional and Longitudinal Analyses of Adolescents’ Cognitive Control-Related Neural Activity

“…In an attempt to reduce noise caused by differences in age among individuals sampled, we recruited a sample of 8 th graders who were all 14-years-old at the first wave, and followed them for one year. This is appears to be a period of developmental change for adolescents in terms of structural brain development (Shaw et al, 2008), performance on cognitive control tasks (Luna, 2009), and performance-related neural activation during cognitive control (Koolschijn et al, 2011; Crone and Elzinga, 2015). In light of these changes, brain-behavior relationships may alter substantially as adolescents go through this transition.…”