Interindividual Differences in Mid-Adolescents in Error Monitoring and Post-Error Adjustment

Abstract

A number of studies have concluded that cognitive control is not fully established until late adolescence. The precise differences in brain function between adults and adolescents with respect to cognitive control, however, remain unclear. To address this issue, we conducted a study in which 185 adolescents (mean age (SD) 14.6 (0.3) years) and 28 adults (mean age (SD) 25.2 (6.3) years) performed a single task that included both a stimulus-response (S-R) interference component and a task-switching component. Behavioural responses (i.e. reaction time, RT; error rate, ER) and brain activity during correct, error and post-error trials, detected by functional magnetic resonance imaging (fMRI), were measured. Behaviourally, RT and ER were significantly higher in incongruent than in congruent trials and in switch than in repeat trials. The two groups did not differ in RT during correct trials, but adolescents had a significantly higher ER than adults. In line with similar RTs, brain responses during correct trials did not differ between groups, indicating that adolescents and adults engage the same cognitive control network to successfully overcome S-R interference or task switches. Interestingly, adolescents with stronger brain activation in the bilateral insulae during error trials and in fronto-parietal regions of the cognitive control network during post-error trials did have lower ERs. This indicates that those mid-adolescents who commit fewer errors are better at monitoring their performance, and after detecting errors are more capable of flexibly allocating further cognitive control resources. Although we did not detect a convincing neural correlate of the observed behavioural differences between adolescents and adults, the revealed interindividual differences in adolescents might at least in part be due to brain development.

The typical development of posterior medial frontal cortex function and connectivity during task control demands in youth 8–19 years old

“…Seemingly conflicting reports of increasing (Adleman et al, 2002; Fitzgerald et al, 2010; Rubia et al, 2006, 2007), decreasing (Durston et al, 2002; Tamm et al, 2002) or unchanging (Casey et al, 1997; Konrad et al, 2005; Marsh et al, 2006; Rodehack et al, 2014) pMFC response to task demands across prior studies may result from the use of different fMRI probes. For example, probes of cognitive interference compared to response inhibition engage overlapping (Chambers et al, 2009; Simmonds et al, 2008;Wager et al, 2005), yet distinct (Bari and Robbins, 2013;Van Velzen et al, 2014) elements of task control and it is possible that distinguishable neural networks with unique maturational trajectories may underlie the development of these task control sub-process.…”

“…Other studies treated age continuously, enabling the detection of more subtle age-related variations. Yet, while several such studies have tested for simple linear effects of age (Adleman et al, 2002; Casey et al, 1997; Durston et al, 2002; Fitzgerald et al, 2010; Konrad et al, 2005; Rodehack et al, 2014; Rubia et al, 2006, 2007; Tamm et al, 2002; but see Marsh et al, 2006), none have reported non-linear (e.g., quadratic or U-shaped) effects of age on brain activation in response to task control demands. Given recent evidence suggesting that developmental change in cortical thickness (including in pMFC) follows a non-linear trajectory (Lenroot and Giedd, 2006), it is possible that a non-linear fit may characterize developmental changes in pMFC engagement by task control.…”

Low‐level alcohol consumption during adolescence and its impact on cognitive control development

“…Details of baseline data and a list of the entire exclusion criteria can be found elsewhere (Rodehacke et al . ). Subjects participated in the study after giving written informed consent for each acquisition.…”

“…In line with a previous publication concerning this task (Rodehacke et al . ), we predict that over time (1) RT and (2) errors decrease, whereas (3) brain responses in core cognitive control areas (ACC, dlPFC, pre‐SMA and PPC) increase.…”

Effects of an opioid (proenkephalin) polymorphism on neural response to errors in health and cocaine use disorder

“…In health, the neural correlates of error-related processing typically encompass a network of regions of the medial prefrontal cortex (PFC) including the anterior cingulate cortex (ACC) [3–5]. Despite this common neural signature, error-related processing is also modulated by individual differences [6–9]. That is, certain individuals or groups may differ in the frequency with which they commit errors, and/or in the reactivity they show upon committing such errors.…”