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Continued learning opportunities are important for adaptation across the lifespan. Interrupted learning (e.g., “summer slide”) is a known, critical issue for childhood education. This perspective piece proposes that adulthood could be a period of prolonged interrupted learning with reduced learning opportunities, despite the known importance of lifelong learning. This idea goes beyond calls for healthy older adults to lead an active life to maintain cognitive abilities and to maintain basic functional skills by highlighting important lifespan circumstances that may hinder or facilitate adaptation in new and changing environments. We explore how research on interrupted learning in childhood could be applied to later adulthood and how changes in learning are viewed differently for children and adults. In addition, research on increasing abilities during childhood generally focuses on specific skills (e.g., reading, math), whereas cognitive aging research focuses on more general cognitive abilities related to attention and memory. Finally, given that interrupted learning occurs unevenly across different ages, abilities, and resources, more can be investigated in terms of who interrupted learning affects across the lifespan, and the neural underpinnings of interrupted learning. Acknowledging and addressing interrupted learning across the lifespan may promote long-term thriving and avoid preventable deficits and decline. 

Cognitive neuroimaging researchers' ability to infer accurate statistical conclusions from neuroimaging depends greatly on the quality of the data analyzed. This need for quality control is never more evident than when conducting neuroimaging studies with children and adolescents. Developmental neuroimaging requires patience, flexibility, adaptability, extra time, and effort. It also provides us a unique, non-invasive way to understand the development of cognitive processes, individual differences, and the changing relations between brain and behavior over the lifespan. In this discussion, we focus on collecting magnetic resonance imaging (MRI) data, as it is one of the more complex protocols used with children and youth. Through our extensive experience collecting MRI datasets with children and families, as well as a review of current best practices, we will cover three main topics to help neuroimaging researchers collect high-quality datasets. First, we review key recruitment and retention techniques, and note the importance for consistency and inclusion across groups. Second, we discuss ways to reduce scan anxiety for families and ways to increase scan success by describing the pre-screening process, use of a scanner simulator, and the need to focus on participant and family comfort. Finally, we outline several important design considerations in developmental neuroimaging such as asking a developmentally appropriate question, minimizing data loss, and the applicability of public datasets. Altogether, we hope this article serves as a useful tool for those wishing to enter or learn more about developmental cognitive neuroscience.