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Physical Activity Is Linked to Greater Moment-To-Moment Variability in Spontaneous Brain Activity in Older Adults.

Burzynska AZ, Wong CN, Voss MW, Cooke GE, Gothe NP, Fanning J, McAuley E, Kramer AF - PLoS ONE (2015)

Bottom Line: We found that older adults who engaged more in LI-PA and MV-PA had greater SDBOLD in brain regions that play a role in integrating segregated functional domains in the brain and benefit from greater CRF or PA, such as precuneus, hippocampus, medial and lateral prefrontal, and temporal cortices.Our results suggest that engaging in higher intensity PA may have protective effects on neural processing in aging.We conclude that SDBOLD is a promising correlate of functional brain health in aging.

View Article: PubMed Central - PubMed

Affiliation: The Beckman Institute for Advanced Science and Technology at the University of Illinois, Urbana, IL, United States of America.

ABSTRACT
Higher cardiorespiratory fitness (CRF) and physical activity (PA) in old age are associated with greater brain structural and functional integrity, and higher cognitive functioning. However, it is not known how different aspects of lifestyle such as sedentariness, light PA (LI-PA), or moderate-to-vigorous physical activity (MV-PA) relate to neural activity in aging. In addition, it is not known whether the effects of PA on brain function differ or overlap with those of CRF. Here, we objectively measured CRF as oxygen consumption during a maximal exercise test and measured PA with an accelerometer worn for 7 days in 100 healthy but low active older adults (aged 60-80 years). We modeled the relationships between CRF, PA, and brain functional integrity using multivariate partial least squares analysis. As an index of functional brain integrity we used spontaneous moment-to-moment variability in the blood oxygenation level-dependent signal (SDBOLD), known to be associated with better cognitive functioning in aging. We found that older adults who engaged more in LI-PA and MV-PA had greater SDBOLD in brain regions that play a role in integrating segregated functional domains in the brain and benefit from greater CRF or PA, such as precuneus, hippocampus, medial and lateral prefrontal, and temporal cortices. Our results suggest that engaging in higher intensity PA may have protective effects on neural processing in aging. Finally, we demonstrated that older adults with greater overall WM microstructure were those showing more LI-PA and MV-PA and greater SDBOLD. We conclude that SDBOLD is a promising correlate of functional brain health in aging. Future analyses will evaluate whether SDBOLD is modifiable with interventions aimed to increase PA and CRF in older adults.

No MeSH data available.


Multivariate relationships between CRF, PA, and SDBOLD (the CRF/PA—SDBOLD model).A: PLS spatial pattern of the CRF/PA—SDBOLD model. Red-yellow regions indicate greater SDBOLD with greater LI-PA and MV-PA. Significant regions: bootstrap ratio ≥3.00. Abbreviations as in Table 2. B: Correlation magnitudes (Pearson r) between CRF, sedentary time, LI-PA, MV-PA, and SDBOLD during rest (permuted p<0.001, error bars represent bootstrapped 95% confidence intervals). CRF and sedentary time did not contribute to the LV as their error bars cross zero.
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pone.0134819.g001: Multivariate relationships between CRF, PA, and SDBOLD (the CRF/PA—SDBOLD model).A: PLS spatial pattern of the CRF/PA—SDBOLD model. Red-yellow regions indicate greater SDBOLD with greater LI-PA and MV-PA. Significant regions: bootstrap ratio ≥3.00. Abbreviations as in Table 2. B: Correlation magnitudes (Pearson r) between CRF, sedentary time, LI-PA, MV-PA, and SDBOLD during rest (permuted p<0.001, error bars represent bootstrapped 95% confidence intervals). CRF and sedentary time did not contribute to the LV as their error bars cross zero.

Mentions: To identify multivariate patterns of relations between CRF, the three PA measures, and SDBOLD in the entire GM we performed behavioral PLS analysis. We refer to it as the CRF/PA—SDBOLD model. The behavioral PLS analysis yields orthogonal latent variables (LVs) that optimally represent relations of SDBOLD in GM voxels with CRF and number of hours spent on PA at three intensities. The analysis yielded one significant LV (permuted p = 0.040, 52.63% cross-block covariance explained by this LV), suggesting that more LI-PA and MV-PA was related to greater SDBOLD in multiple GM regions (Fig 1A and 1B). CRF and sedentary time did not significantly contribute to the model. Peak voxels’ location and bootstrap ratios for the CRF/PA—SDBOLD model are reported in Table 2.


Physical Activity Is Linked to Greater Moment-To-Moment Variability in Spontaneous Brain Activity in Older Adults.

Burzynska AZ, Wong CN, Voss MW, Cooke GE, Gothe NP, Fanning J, McAuley E, Kramer AF - PLoS ONE (2015)

Multivariate relationships between CRF, PA, and SDBOLD (the CRF/PA—SDBOLD model).A: PLS spatial pattern of the CRF/PA—SDBOLD model. Red-yellow regions indicate greater SDBOLD with greater LI-PA and MV-PA. Significant regions: bootstrap ratio ≥3.00. Abbreviations as in Table 2. B: Correlation magnitudes (Pearson r) between CRF, sedentary time, LI-PA, MV-PA, and SDBOLD during rest (permuted p<0.001, error bars represent bootstrapped 95% confidence intervals). CRF and sedentary time did not contribute to the LV as their error bars cross zero.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4526228&req=5

pone.0134819.g001: Multivariate relationships between CRF, PA, and SDBOLD (the CRF/PA—SDBOLD model).A: PLS spatial pattern of the CRF/PA—SDBOLD model. Red-yellow regions indicate greater SDBOLD with greater LI-PA and MV-PA. Significant regions: bootstrap ratio ≥3.00. Abbreviations as in Table 2. B: Correlation magnitudes (Pearson r) between CRF, sedentary time, LI-PA, MV-PA, and SDBOLD during rest (permuted p<0.001, error bars represent bootstrapped 95% confidence intervals). CRF and sedentary time did not contribute to the LV as their error bars cross zero.
Mentions: To identify multivariate patterns of relations between CRF, the three PA measures, and SDBOLD in the entire GM we performed behavioral PLS analysis. We refer to it as the CRF/PA—SDBOLD model. The behavioral PLS analysis yields orthogonal latent variables (LVs) that optimally represent relations of SDBOLD in GM voxels with CRF and number of hours spent on PA at three intensities. The analysis yielded one significant LV (permuted p = 0.040, 52.63% cross-block covariance explained by this LV), suggesting that more LI-PA and MV-PA was related to greater SDBOLD in multiple GM regions (Fig 1A and 1B). CRF and sedentary time did not significantly contribute to the model. Peak voxels’ location and bootstrap ratios for the CRF/PA—SDBOLD model are reported in Table 2.

Bottom Line: We found that older adults who engaged more in LI-PA and MV-PA had greater SDBOLD in brain regions that play a role in integrating segregated functional domains in the brain and benefit from greater CRF or PA, such as precuneus, hippocampus, medial and lateral prefrontal, and temporal cortices.Our results suggest that engaging in higher intensity PA may have protective effects on neural processing in aging.We conclude that SDBOLD is a promising correlate of functional brain health in aging.

View Article: PubMed Central - PubMed

Affiliation: The Beckman Institute for Advanced Science and Technology at the University of Illinois, Urbana, IL, United States of America.

ABSTRACT
Higher cardiorespiratory fitness (CRF) and physical activity (PA) in old age are associated with greater brain structural and functional integrity, and higher cognitive functioning. However, it is not known how different aspects of lifestyle such as sedentariness, light PA (LI-PA), or moderate-to-vigorous physical activity (MV-PA) relate to neural activity in aging. In addition, it is not known whether the effects of PA on brain function differ or overlap with those of CRF. Here, we objectively measured CRF as oxygen consumption during a maximal exercise test and measured PA with an accelerometer worn for 7 days in 100 healthy but low active older adults (aged 60-80 years). We modeled the relationships between CRF, PA, and brain functional integrity using multivariate partial least squares analysis. As an index of functional brain integrity we used spontaneous moment-to-moment variability in the blood oxygenation level-dependent signal (SDBOLD), known to be associated with better cognitive functioning in aging. We found that older adults who engaged more in LI-PA and MV-PA had greater SDBOLD in brain regions that play a role in integrating segregated functional domains in the brain and benefit from greater CRF or PA, such as precuneus, hippocampus, medial and lateral prefrontal, and temporal cortices. Our results suggest that engaging in higher intensity PA may have protective effects on neural processing in aging. Finally, we demonstrated that older adults with greater overall WM microstructure were those showing more LI-PA and MV-PA and greater SDBOLD. We conclude that SDBOLD is a promising correlate of functional brain health in aging. Future analyses will evaluate whether SDBOLD is modifiable with interventions aimed to increase PA and CRF in older adults.

No MeSH data available.