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Get Moving! Increases in Physical Activity Are Associated With Increasing Functional Connectivity Trajectories in Typically Aging Adults
Background: Physical activity closely relates to cognition and brain structure as we age. However, the neural mechanisms underlying this relationship in humans remain less clear. Functional connectivity (FC), measured by task-free functional MRI (tf-fMRI) is a dynamic marker of network activity and...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7198911/ https://www.ncbi.nlm.nih.gov/pubmed/32410981 http://dx.doi.org/10.3389/fnagi.2020.00104 |
Sumario: | Background: Physical activity closely relates to cognition and brain structure as we age. However, the neural mechanisms underlying this relationship in humans remain less clear. Functional connectivity (FC), measured by task-free functional MRI (tf-fMRI) is a dynamic marker of network activity and may be a sensitive indicator of the brain’s response to exercise over time. We aimed to test the longitudinal relationship between physical activity and FC trajectories in functionally normal older adults. Methods: Two hundred and twelve functionally normal, longitudinally-followed older adults completed the Physical Activity Scale for the Elderly (PASE) and tf-fMRI scans at each visit [mean = 1.5 visits (range:1–3)]. We studied FC of the default mode network (DMN), frontal-parietal (FP), subcortical networks (SubCort), and frontal-subcortical inter-network connectivity (FS), given that previous studies implicate these regions in age-related changes. Linear mixed-effects models examined the relationship between within-person changes in PASE and FC (in SD units), covarying for age, sex, education and systemic cardiovascular risk factors (heart rate, BMI and systolic blood pressure). We additionally examined models covarying for DTI fractional anisotropy (FA) and mean diffusivity (MD) of tracts underlying networks of interest, as a marker of cerebrovascular disease. Furthermore, we examined the longitudinal relationship between PASE and neuropsychological trajectories. Results: In our first model, within-subject increases in physical activity tracked with increasing SubCort (β = 0.33, p = 0.007) and FS inter-network (β = 0.27, p = 0.03) synchrony, while between-subject parameters did not reach significance (β = −0.042 to −0.07, ps > 0.37). No significant longitudinal associations were observed between PASE and DMN (β = −0.02 p = 0.89) or FP networks (β = 0.15, p = 0.23). Adjusting for markers of cerebrovascular health (FA/MD) did not change estimated effects (SubCort: β = 0.31, p = 0.01, FS inter-network: β = 0.28, p = 0.03). Associations between changes in physical activity and neuropsychological trajectories were small (β = −0.14 to 0.002) and did not reach statistical significance (p-values >0.42). Conclusions: Our findings suggest that changes in exercise over time are specifically associated with frontal-subcortical processes in older adults. This relationship appears to be independent of cardio- or cerebrovascular disease, possibly driven by a more direct neural response to exercise. |
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