ArticleBrain communications2025
Dynamic reconfiguration of brain functional networks in world class gymnasts: a resting-state functional MRI study.
Article in Brain communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review and coordinate-based meta-analysis of resting-state fMRI in athletes from open and closed skills sports.Scientific reports · 2025Pooled it
- The Effect of AoA-L2 on Functional Network Dynamics in Bilinguals.Brain topography · 2026Article
- Toward a dual-pathway model of neuroplastic adaptation in sport: neural efficiency and neural optimization.Frontiers in neuroscience · 2026Article
- Dynamic Brain Activation and Connectivity in Elite Golfers During Distinct Golf Swing Phases: An fMRI Study.Brain sciences · 2025Article
- Functional reorganization of brain networks from childhood to adolescence: A multi-level approach.International journal of clinical and health psychology : IJCHPArticle
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Long-term intensive training has enabled world class gymnasts to attain exceptional skill levels, inducing notable neuroplastic changes in their brains. Previous studies have identified optimized brain modularity related to long-term intensive training based on resting-state functional MRI, which is associated with higher efficiency in motor and cognitive functions. However, most studies assumed that functional topological networks remain static during the scans, neglecting the inherent dynamic changes over time. This study applied a multilayer network model to identify the effect of long-term intensive training on dynamic functional network properties in gymnasts. The imaging data were collected from 13 gymnasts and 14 age- and gender-matched non-athlete controls. We first construct dynamic functional connectivity matrices for each subject to capture the temporal information underlying these brain signals. Then, we applied a multilayer community detection approach to analyse how brain regions form modules and how this modularity changes over time. Graph theoretical parameters, including flexibility, promiscuity, cohesion and disjointedness, were estimated to characterize the dynamic properties of functional networks across global, network, and nodal levels in the gymnasts. The gymnasts showed significantly lower flexibility, cohesion and disjointedness at the global level than the controls. Then, we observed lower flexibility and cohesion in the auditory, dorsal attention, sensorimotor, subcortical, cingulo-opercular and default mode networks in the gymnasts than in the controls. Furthermore, these gymnasts showed decreased flexibility and cohesion in several regions associated with motor function. Together, we found brain functional neuroplasticity related to long-term intensive training, primarily characterized by decreased flexibility of brain dynamics in the gymnasts, which provided new insights into brain reorganization in motor skill learning.
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