Key considerations for child and adolescent MRI data collection.

Area of Science:

• Developmental cognitive neuroscience
• Neuroimaging research

Background:

• High-quality neuroimaging data is essential for accurate statistical conclusions in cognitive neuroscience.
• Developmental neuroimaging studies, particularly with children and adolescents, present unique challenges requiring specialized approaches.
• Magnetic Resonance Imaging (MRI) data collection with pediatric populations demands meticulous planning and execution.

Purpose of the Study:

• To provide neuroimaging researchers with practical strategies for collecting high-quality MRI data in children and adolescents.
• To address key challenges in developmental neuroimaging, including recruitment, data quality, and study design.
• To serve as a resource for researchers entering or seeking to enhance their expertise in developmental cognitive neuroscience.

Main Methods:

• Review of current best practices in developmental neuroimaging data collection.
• Discussion of recruitment and retention techniques for pediatric participants.
• Exploration of methods to reduce scan anxiety and increase scan success, including pre-screening and simulator use.
• Outline of design considerations such as developmentally appropriate questions and minimizing data loss.

Main Results:

• Effective recruitment and retention strategies are vital for consistent and inclusive pediatric neuroimaging datasets.
• Reducing scan anxiety through preparation (e.g., pre-screening, simulator) and ensuring participant comfort significantly increases scan success rates.
• Thoughtful study design, including age-appropriate questions and minimizing data loss, is critical for robust developmental findings.

Conclusions:

• Implementing specific techniques for recruitment, anxiety reduction, and study design can substantially improve the quality of MRI data collected from children and adolescents.
• Adherence to best practices in developmental neuroimaging is key to advancing our understanding of cognitive development and brain-behavior relationships across the lifespan.
• This article provides a valuable framework for researchers aiming to conduct rigorous and successful developmental cognitive neuroscience studies.