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Updated: Oct 12, 2025
Studying Brain Function in Children Using Magnetoencephalography
Published on: April 8, 2019
Developmental Factors That Predict Head Movement During Resting-State Functional Magnetic Resonance Imaging in
Chelsea A Johnson1, Emily O Garnett2, Ho Ming Chow3
1Department of Communicative Sciences and Disorders, Michigan State University, East Lansing, MI, United States.
Insights
Childhood temperament, sex, and age influence head movement during brain MRI scans. Higher effortful control in boys reduces movement, aiding data collection for neurodevelopmental studies.
Area of Science:
- Neuroimaging
- Developmental Psychology
- Pediatric Neurology
Background:
- Early childhood is crucial for neurocognitive development and identifying neurodevelopmental disorders.
- Magnetic resonance imaging (MRI) is vital for studying brain development but challenging in young children due to movement.
- Predicting factors for successful MRI acquisition is essential for reliable data in pediatric neuroimaging.
Purpose of the Study:
- To investigate predictors of head movement during resting-state functional MRI (rs-fMRI) in preschool-aged children.
- To examine the influence of age, sex, stuttering status, and childhood temperament on movement during MRI scans.
- To determine if temperament factors can improve predictions of MRI data quality in children.
Main Methods:
- Analyzed rs-fMRI data from 76 children aged 3-7 years, including 42 children who stutter (CWS).
- Assessed movement extent during scans using MRI data.
- Measured age, sex, stuttering status, and childhood temperament via the Child Behavioral Questionnaire.
Main Results:
- Age, sex, and temperament factors significantly predicted head movement during rs-fMRI.
- Children who stutter did not differ from controls in temperament or movement.
- Effortful control and negative affectivity in boys were significant predictors of movement, with age becoming non-significant when temperament was included.
Conclusions:
- Childhood temperament, particularly effortful control, is a key factor in predicting successful MRI data acquisition in young children.
- Incorporating temperament assessments alongside age and sex can enhance the prediction of usable rs-fMRI data quality.
- Findings suggest strategies to minimize movement and improve neuroimaging research in pediatric populations.
Abstract:
Early childhood marks a period of dynamic neurocognitive development. Preschool-age coincides with the onset of many childhood disorders and is a developmental period that is frequently studied to determine markers of neurodevelopmental disorders. Magnetic resonance imaging (MRI) is often used to explore typical brain development and the neural bases of neurodevelopmental disorders. However, acquiring high-quality MRI data in young children is challenging. The enclosed space and loud sounds can trigger unease and cause excessive head movement. A better understanding of potential factors that predict successful MRI acquisition would increase chances of collecting useable data in children with and without neurodevelopmental disorders. We investigated whether age, sex, stuttering status, and childhood temperament as measured using the Child Behavioral Questionnaire, could predict movement extent during resting-state functional MRI (rs-fMRI) in 76 children aged 3-7 years, including 42 children who stutter (CWS). We found that age, sex, and temperament factors could predict motion during rs-fMRI scans. The CWS were not found to differ significantly from controls in temperament or head movement during scanning. Sex and age were significant predictors of movement. However, age was no longer a significant predictor when temperament, specifically effortful control, was considered. Controlling for age, boys with higher effortful control scores moved less during rs-fMRI procedures. Additionally, boys who showed higher negative affectivity showed a trend for greater movement. Considering temperament factors in addition to age and sex may help predict the success of acquiring useable rs-fMRI (and likely general brain MRI) data in young children in MR neuroimaging.
