Paradoxical network rigidity and peripheral decoupling: age-related breakdown of adaptive postural control
Year: 2026
Type: article
Study design: Observational Study
Abstract: Older adults face disproportionate fall risk during dual-task conditions, yet the neuromechanical basis remains elusive. We reveal a mechanistic paradox: aging reorganizes whole-body coordination through globally rigid, hyper-connected networks that paradoxically decouple the peripheral effectors critical for balance. Motion capture analysis (48 younger, 48 older adults; 21 markers) during stance on stable/unstable surfaces with and without cognitive load showed that younger adults dynamically reconfigure coordination architectures, with task-specific modulation of local clustering, global efficiency, and peripheral-to-center-of-mass coupling. Older adults instead exhibited chronically rigid networks—elevated local transitivity, global efficiency, and small-worldness, hallmarks of ostensibly superior organization—yet showed reduced inter-modular flexibility and, critically, weakened foot–ankle–shank-to-center-of-mass coupling during instability, precisely when distal control becomes essential. This rigidity persisted across mechanical and cognitive challenges and throughout sustained trials, independent of sway magnitude or fatigue, indicating chronic reorganization rather than transient compensation. Age-related motor decline thus reflects not component degradation but qualitative network rigidification: loss of context-sensitive reconfiguration capacity. These findings establish network flexibility metrics as mechanistic markers for fall risk and reframe intervention targets from component strengthening toward restoring organizational plasticity—the capacity to selectively assemble, dissolve, and reassemble coordination patterns as task demands evolve.
Source: npj Aging
Institution: University of Nebraska at Omaha
Language: English
Field: Health Professions
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,690
OpenAlex ID: W7208769486
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