Experience-dependent plasticity of large-scale brain networks in aging: How different training modalities shape neural connectivity

: Brain regions are organized into large-scale networks through dynamic functional connections that support sensorimotor and cognitive processes across the lifespan. Age-related disruptions of these functional systems are associated with cognitive and motor decline and increased risk of neurocognitive disorders. A growing body of evidence suggests that structured physical training can modulate resting-state functional connectivity within these networks, offering a potential neuroprotective strategy. However, the relative efficacy of different training modalities, and the mechanisms by which simultaneous cognitive loading during motor training may confer neuroplastic benefits, remain incompletely characterized. This narrative review critically integrates evidence on network-level changes following cardiorespiratory, resistance and balance training, cognitive stimulation, and combined motor-cognitive interventions (with exergames (i.e., interactive physical and/or motor-cognitive exercises to control traditional or extended reality videogames) and mind-body practices) in older adults. We critically appraise evidence strength across three methodological tiers: direct neuroimaging (i.e., rs-fMRI), indirect measures (i.e., EEG and fNIRS), and conceptual frameworks, and apply this hierarchy to critically evaluate the guided-plasticity facilitation framework, a working hypothesis proposing synergistic neuroplastic effects when motor and cognitive demands overlap, for which direct neuroimaging support in humans remains limited. Key methodological gaps are identified: scarcity of direct comparison trials, inadequate dose-matching, limited long-term data, and near-absence of dynamic functional connectivity analyses. We outline research priorities to advance a mechanistic, individualized understanding of experience-dependent brain network plasticity in aging and neurocognitive disorders and propose network-level biomarkers as a candidate direction for future personalized training prescriptions. We also outline a prospective precision-medicine framework for exercise prescription in neurocognitive disorders, noting that prospective validation studies are needed before network-level biomarkers can inform clinical decision-making.