Motor- and Cognitive-Dominant Functional Network Adaptations Supporting Dual-Task Performance in Older Adults

Abstract Aging is associated with declines in both motor and cognitive functions, which are often examined using cognitive–motor dual-task paradigms. However, the functional brain network mechanisms supporting dual-task performance across these domains remain incompletely understood. We investigated 40 older adults (50–80 years) and 20 younger adults (20–40 years) who performed a motor single task (pedaling), a cognitive single task (Go/NoGo), and a combined cognitive–motor dual-task during functional magnetic resonance imaging (fMRI) using a custom-built MRI-compatible pedaling device. Behaviorally, older adults showed significant dual-task costs in motor performance, whereas cognitive performance was relatively preserved. At the neural level, task-based functional connectivity revealed distinct patterns of age-related network reorganization. Cognitive-dominant networks showed relatively selective connectivity increases within frontal executive and motor-planning regions, consistent with compensatory recruitment supporting preserved cognitive dual-task performance. In contrast, motor-dominant networks exhibited broader reorganization, characterized by strengthened frontoparietal control circuits but weakened cerebello-parietal and sensorimotor pathways, pointing to reduced automaticity and increased reliance on central cognitive control. Multivariate brain–behavior analyses further revealed age-related differences in latent connectivity–behavior relationships. Motor-dominant networks in older adults showed greater dispersion and stronger coupling with behavioral variability, whereas cognitive-network patterns remained largely stable and overlapping across age groups. Motor response time variability, particularly under dual-task conditions, emerged as the strongest behavioral contributor to this latent brain–behavior dimension and was associated to connectivity in frontoparietal control and motor-planning regions. Together, these findings demonstrate that aging involves an asymmetric reorganization of large-scale networks, in which motor systems become increasingly dependent on cognitive control while cognitive systems remain comparatively resilient. This network-level account identifies motor variability and cognitive–motor interdependence as sensitive markers of aging-related brain changes, with implication for understanding why cognitive–motor abilities remain stable in some individuals while declining in others.