Key points are not available for this paper at this time.
Abstract Cognitive training often aims to improve cognitive skills, but outcomes have been variable in terms of their success. One factor that has been found to predict training outcomes is the degree of modularity of functional brain networks, defined as the extent to which brain regions are more strongly connected to regions within the same functional subnetwork than to regions outside of the subnetwork. Specifically, more modular organization of functional brain networks at baseline has been associated with greater benefits from cognitive training in adults. During childhood, cognitive development is marked by a slow progression towards network integration and segregation, which together contribute to increasing modularity. Thus, network modularity might also be an important predictor of training outcomes in children. To investigate whether individual differences in network modularity predict training outcomes in children, we examined 84 children aged 8 to 11 years who completed nine weeks of either high-intensity task-switching training or high-intensity single-task training. Prior to training, children showed lower network modularity than adults, in line with previously reported developmental changes in network configuration. With training, performance improved, especially in the high-intensity task-switching group. More modular organization of functional brain networks before training was associated with faster improvements in task-switching performance, especially at the beginning of training. These results suggest that more modular functional networks might allow for faster adaptation to training demands in children and thus faster improvements with training. Graphical abstract Highlights – Intensive training improved task-switching performance in children. – Children showed less modular network organization than adults. – More modular networks before training were associated with faster training gains. – Children with more modular networks adapted more quickly to training demands.
Schwarze et al. (2026) studied this question.