Tai Chi (TC) practice has been shown to improve both cognitive and physical function in older adults. However, the neural mechanisms underlying the benefits of TC remain unclear. Our primary aims are to explore whether distinct age-related and TC-practice-related relationships can be identified with respect to either temporal or spatial (within/between-network connectivity) differences. This cross-sectional study examined recurrent neural network dynamics, employing an adaptive, data-driven thresholding approach to source-localized resting-state EEG data in order to identify meaningful connections across time-varying graphs, using both temporal and spatial features derived from a hidden Markov model (HMM). Mann–Whitney U tests assessed between-group differences in temporal and spatial features by age and TC practice using either healthy younger adult controls (YACs, n = 15), healthy older adult controls (OACs, n = 15), or Tai Chi older adult practitioners (TCOAs, n = 15). Our results showed that aging is associated with decreased within-network and between-network functional connectivity (FC) across most brain networks. Conversely, TC practice appears to mitigate these age-related declines, showing increased FC within and between networks in older adults who practice TC compared to non-practicing older adults. These findings suggest that TC practice may abate age-related declines in neural network efficiency and stability, highlighting its potential as a non-pharmacological intervention for promoting healthy brain aging. This study furthers the triple-network model, showing that a balancing and reorientation of attention might be engaged not only through higher-order and top-down mechanisms (i.e., FPN/DAN) but also via the coupling of bottom-up, sensory–motor (i.e., SMN/VIN) networks.

Tai Chi (TC) practice has demonstrated cognitive, motor, and emotional benefits for older adults which are thought to be underlied by neuroprotective mechanisms; however, the nature of such neuroprotective mechanisms remains insufficiently characterized and thus, poorly understood. The current study sought to characterize the compensatory and/or detrimental neural connectivity patterns associated with TC practice, using dynamic functional connectivity (FC) derived from resting-state, source-localized EEG data. We examined three participant groups: younger adults (YACs, n=15), older adult controls (OACs, n=15), and older adults practicing Tai Chi (TCOAs, n=15) from which aging effects (OACs vs YACs) and TC effects (OACs vs TCOAs) were quantified. Our analysis revealed TC practitioners demonstrated specific compensatory connectivity patterns, predominantly through preservation mechanisms that maintained youthful connectivity profiles and alternative mechanisms diverging beneficially from age-matched controls. Although numerical analyses of FC mechanisms suggested a predominantly detrimental connectivity pattern for certain FC subcategories, correlational analysis indicated that many of these connections provided cognitive, motor, and emotional regulation benefits, thereby clarifying their compensatory role. Notably, interactions within and between attention-related (ventral/dorsal) and frontoparietal networks emerged as pivotal compensatory neural networks, aligning with previous mind-body literature. These findings highlight TC’s potential to enhance neural resilience against age-related functional decline. Future research should employ simultaneous and temporally aligned neuroimaging, physiological, and behavioral assessments to validate and expand upon these results, as well as further elucidating the organizing principles by which reorganizational network changes exert their neuroprotective effects.