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The structure of executive function (EF) has been the focus of much debate for decades. What is more, the complexity and diversity provided by the developmental period only adds to this contention. The development of executive function plays an integral part in the expression of children's behavioral, cognitive, social, and emotional capabilities. Understanding how these processes are constructed during development allows for effective measurement of EF in this population. This meta-analysis aims to contribute to a better understanding of the structure of executive function in children. A coordinate-based meta-analysis was conducted (using BrainMap GingerALE 2.3), which incorporated studies administering functional magnetic resonance imaging (fMRI) during inhibition, switching, and working memory updating tasks in typical children (aged 6–18 years). The neural activation common across all executive tasks was compared to that shared by tasks pertaining only to inhibition, switching or updating, which are commonly considered to be fundamental executive processes. Results support the existence of partially separable but partially overlapping inhibition, switching, and updating executive processes at a neural level, in children over 6 years. Further, the shared neural activation across all tasks (associated with a proposed “unitary” component of executive function) overlapped to different degrees with the activation associated with each individual executive process. These findings provide evidence to support the suggestion that one of the most influential structural models of executive functioning in adults can also be applied to children of this age. However, the findings also call for careful consideration and measurement of both specific executive processes, and unitary executive function in this population. Furthermore, a need is highlighted for a new systematic developmental model, which captures the integrative nature of executive function in children.

Informing the Structure of Executive Function in Children: A Meta-Analysis of Functional Neuroimaging Data