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A decrease in brain volume (ie, brain atrophy) is a marker of cognitive health in older adults. Insufficient weekly accumulation of moderate and vigorous physical activity (MVPA) has been associated with lower brain volume. As this association has been established for a small number of brain areas and structures and atrophy rates seem to be nonuniform between them, more comprehensive analyses are warranted. We compared the volume of 71 brain areas and structures in 45 older adults who met and did not meet objectively measured MVPA recommendations. In addition, we used multiple regression models to determine whether cardiorespiratory fitness (VO2PEAK), MVPA, and health-related risk factors could affect the atrophy of brain areas and structures. An accelerometer (GT9-X ActiGraph) was worn for 7 days. Participants were then classified into 2 groups: <150 minutes MVPA (<150′MVPA; n  = 20) and ≥150 minutes MVPA (≥150′MVPA; n  = 25) per week. Older adults who accumulated ≥150′MVPA per week had significantly higher absolute and relative (% of intracranial volume) volumes of 39 and 9 brain areas and structures, respectively, than those who accumulated <150′MVPA per week. Higher VO2PEAK seems to be a key predictor of the atrophy of brain areas and structures. In conclusion, meeting weekly physical activity recommendations seems to have a widespread effect on preserving the volume of more than 30 brain areas and structures in older adults. VO2PEAK seems to be the most frequent and important predictor of brain volume preservation. [ABSTRACT FROM AUTHOR]

Background: Deficits in the cerebellar locomotor region (CLR) have been associated with loss of gait automaticity in individuals with freezing of gait in Parkinson's disease (freezers); however, exercise interventions that restore gait automaticity in freezers are lacking. We evaluated the effects of the adapted resistance training with instability ([ARTI] complex exercises) compared with traditional motor rehabilitation (without complex exercises) on gait automaticity and attentional set‐shifting. We also verified associations between gait automaticity change and CLR activation change previously published. Methods: Freezers were randomized either to the experimental group (ARTI, n = 17) or to the active control group (traditional motor rehabilitation, n = 15). Both training groups performed exercises 3 times a week for 12 weeks. Gait automaticity (dual‐task and dual‐task cost [DTC] on gait speed and stride length), single‐task gait speed and stride length, attentional set‐shifting (time between Trail Making Test parts B and A), and CLR activation during a functional magnetic resonance imaging protocol of simulated step initiation task were evaluated before and after interventions. Results: Both training groups improved gait parameters in single task (P < 0.05), but ARTI was more effective than traditional motor rehabilitation in improving DTC on gait speed, DTC on stride length, dual‐task stride length, and CLR activation (P < 0.05). Changes in CLR activation were associated with changes in DTC on stride length (r = 0.68, P = 0.002) following ARTI. Only ARTI improved attentional set‐shifting at posttraining (P < 0.05). Conclusions: ARTI restores gait automaticity and improves attentional set‐shifting in freezers attributed to the usage of exercises with high motor complexity. © 2020 International Parkinson and Movement Disorder Society [ABSTRACT FROM AUTHOR]

Background: Individuals with Parkinson's disease (PD) who report freezing of gait (FOG) have poorer sleep quality than those without FOG. Cognitive, anxiety, and mobility disability are components of the FOG phenotype, however, no study has investigated if poor sleep quality is associated with all three components that underlie FOG in PD.Research Question: Are there associations among sleep quality and all three components of the FOG phenotype?Methods: Forty and 39 individuals with and without FOG (PD + FOG and PD-FOG), respectively, and 31 age-matched healthy controls (HC) participated in this study. Self-reported FOG (new-FOG questionnaire-NFOGQ), sleep quality (Pittsburgh Sleep Quality Index-PSQI), cognitive function (Montreal Cognitive Assessment-MoCA), anxiety (subscale from Hospital Anxiety and Depression Scale-HADS-A), and mobility (timed-up-and-go test-TUG) were assessed.Results and Significance: PSQI scores were correlated with the scores of NFOGQ, MoCA, HADS-A, and TUG time in PD + FOG (P ≤ 0.0038). The multiple regression analysis identified the PSQI scores as the only predictor of the variance of the NFOGQ scores (R2 = 0.46, P < .0001). The variance in the PSQI scores were explained (69 %) by MoCA scores, NFOGQ scores, TUG time, and HADS-A scores (P ≤ 0.05). Although PD + FOG had a higher disease severity compared to PD-FOG (P < 0.001), disease severity did not enter in the regression model to explain PSQI scores and NFOGQ scores. We also observed associations of PSQI scores with the MoCA scores and TUG time for HC (P ≤ 0.0038), whereas there was no association between PSQI scores and any variable in PD-FOG (P > 0.05). Finally, PD + FOG presented worse scores of PSQI, MoCA, HADS-A, and TUG time than PD-FOG and HC (P < 0.05). Thus, poor sleep quality is associated with FOG and all three components that underlie FOG, regardless of the disease severity. Therefore, treatments useful to decrease FOG should be targeted to ameliorate sleep quality, cognition, anxiety, and mobility. [ABSTRACT FROM AUTHOR]