Functional and structural connectome-based predictive modelling of balance in elderly adults
Xinyu Liu1,2,3, Selin Scherrer4, Sven Egger4
1Laboratory for Functional and Metabolic Imaging (LIFMET), Ecole Polytechnique Fédérale de Lausanne, EPFL AVP CP CIBM Station 6, 1015, Lausanne, Switzerland. xinyuliu1999@hotmail.com.
Scientific Reports
|March 18, 2026
Summary
Brain connections predict balance in older adults. Both structural and functional brain networks are key to maintaining stability, with structural connections showing greater predictive power and reliability for balance control.
Area of Science:
- Neuroscience
- Gerontology
- Biomedical Engineering
Background:
- Balance control is crucial for older adults' quality of life, but its neural basis is not fully understood.
- Previous neuroimaging studies often analyzed brain regions or single connectome types (structural or functional) in isolation.
- Understanding the neural correlates of balance is essential for developing targeted interventions.
Purpose of the Study:
- To identify brain connections predictive of individual balance abilities in older adults using connectome-based predictive modeling (CPM).
- To investigate the predictive power and reliability of both structural and functional connectomes for balance control.
- To explore the complementary roles of different brain networks in maintaining balance.
Main Methods:
- Utilized connectome-based predictive modeling (CPM) on structural and functional connectomes from 54 older adults.
- Employed repeated-measurement data for test-retest reliability and strength performance data for specificity validation.
- Analyzed mean sway area on an unstable device as the primary measure of balance performance.
Main Results:
- Both structural and functional connectomes successfully predicted balance performance.
- Motor-subcortical, medial-frontal, and fronto-parietal networks consistently predicted balance across both connectome types.
- Structural connectomes demonstrated superior prediction performance and test-retest reliability compared to functional connectomes.
- Connections with visual networks uniquely contributed to prediction in the structural connectome.
Conclusions:
- Structural and functional brain connectomes are significant predictors of motor control in challenging conditions for the elderly.
- Interdependency and complementary roles of structural and functional connectomes are highlighted in balance control.
- Structural connectome analysis offers robust insights into the neural underpinnings of balance in older adults.
