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Updated: Jan 3, 2026

A Pediatric Concussion Model in Mice: Closed Head Injury with Long-Term Disorders (CHILD)
Published on: February 7, 2025
Default mode network anatomy and function is linked to pediatric concussion recovery
Kartik K Iyer1, Andrew Zalesky2, Karen M Barlow1,3,4,5
1Child Health Research Centre, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia.
Insights
Brain structure and function changes in children with mild traumatic brain injury (mTBI) are linked to persistent post-concussion symptoms (PPCS), particularly sleep disturbances. These brain markers accurately predict recovery from PPCS.
Area of Science:
- Neuroscience
- Pediatric Neurology
- Radiology
Background:
- Mild traumatic brain injury (mTBI) can lead to persistent post-concussion symptoms (PPCS) in children.
- Understanding the relationship between brain changes and symptom recovery is crucial for effective treatment.
Purpose of the Study:
- To investigate if anatomical and functional brain features correlate with PPCS in children recovering from mTBI.
- To determine if these brain indices can predict individual recovery from PPCS.
Main Methods:
- 110 children with mTBI were assessed using MRI for gray matter volume and resting-state fMRI for functional connectivity.
- Sleep disturbance scores and neurocognition were measured longitudinally.
- Machine learning models analyzed the prognostic value of combined structural and functional brain data.
Main Results:
- Decreased gray matter volume and functional connectivity in the default mode network (posterior cingulate cortex, medial prefrontal cortex) were associated with increased sleep disturbance and fatigue.
- Reduced functional connectivity between these regions correlated with sleep problems.
- Combined brain indices accurately predicted clinical outcomes (AUC=0.86).
Conclusions:
- The structure-function profile of default mode network regions is critical for sleep disturbances post-mTBI.
- These findings offer valuable prognostic information for pediatric concussion recovery.
Objective:
To determine whether anatomical and functional brain features relate to key persistent post-concussion symptoms (PPCS) in children recovering from mild traumatic brain injuries (mTBI), and whether such brain indices can predict individual recovery from PPCS.
Methods:
One hundred and ten children with mixed recovery following mTBI were seen at the concussion clinic at Neurology department Alberta Children's Hospital. The primary outcome was the Post-Concussion Symptom Inventory (PCSI, parent proxy). Sleep disturbance scores (PCSI subdomain) and the Neurocognition Index (CNS Vital Signs) were also measured longitudinally. PPCS was assessed at 4 weeks postinjury and 8-10 weeks postinjury. Gray matter volumes were assessed using magnetic resonance imaging (MRI) and voxel-based morphometry at 4 weeks postinjury. Functional connectivity was estimated at the same timepoint using resting-state MRI. Two complementary machine learning methods were used to assess if the combination of gray matter and functional connectivity indices carried meaningful prognostic information.
Results:
Higher scores on a composite index of sleep disturbance, including fatigue, were associated with converging decreases in gray matter volume and local functional connectivity in two key nodes of the default mode network: the posterior cingulate cortex and the medial prefrontal cortex. Sleep-related disturbances also significantly correlated with reductions in functional connectivity between these brain regions. The combination of structural and functional brain indices associated to individual variations in the default mode network accurately predicted clinical outcomes at follow-up (area under the curve = 0.86).
Interpretation:
These results highlight that the function-structure profile of core default mode regions underpins sleep-related problems following mTBI and carries meaningful prognostic information for pediatric concussion recovery.
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