Perceptual decision-making in children: Age-related differences and EEG correlates

Abstract

Children make faster and more accurate decisions about perceptual information as they get older, but it is unclear how different aspects of the decision-making process change with age. Here, we used hierarchical Bayesian diffusion models to decompose performance in a perceptual task into separate processing components, testing age-related differences in model parameters and links to neural data. We collected behavioural and EEG data from 96 six- to twelve-year-olds and 20 adults completing a motion discrimination task. We used a component decomposition technique to identify two response-locked EEG components with ramping activity preceding the response in children and adults: one with activity that was maximal over centro-parietal electrodes and one that was maximal over occipital electrodes. Younger children had lower drift rates (reduced sensitivity), wider boundary separation (increased response caution) and longer non-decision times than older children and adults. Yet model comparisons suggested that the best model of children’s data included age effects only on drift rate and boundary separation (not non-decision time). Next we extracted the slope of ramping activity in our EEG components and covaried these with drift rate. The slopes of both EEG components related positively to drift rate, but the best model with EEG covariates included only the centro-parietal component. By decomposing performance into distinct components and relating them to neural markers, diffusion models have the potential to identify the reasons why children with developmental conditions perform differently to typically developing children - and to uncover processing differences inapparent in the response time and accuracy data alone.

Cognitive pediatric tele-assessment: a scoping review

“…A special consideration when working with pediatric populations is the fact that children are more variable in terms of attentional capacity, motivation, stamina, and engagement than adults (Hodge et al, 2019;Salinas et al, 2020;Manning et al, 2021;Ruffini et al, 2022), and therefore more susceptible to "Zoom" or virtual fatigue (Bailenson, 2021), and eyestrain over lengthy assessments (Jaffar and Zehra Ali, 2021). These factors not only can reduce assessment performance but can also hamper the possibility of establishing a standardized testing protocol suitable for a larger range of pediatric samples.…”