scholarly journals Two Separate, Large Cohorts Reveal Modifiers of Age-Related Change in Visual Reaction Time Performance

2020 ◽  
Author(s):  
Joshua S Talboom ◽  
Matt D De Both ◽  
Marcus A Naymic ◽  
Annie M Schmidt ◽  
Candace R Lewis ◽  
...  
Keyword(s):  
Reaction Time ◽  
Processing Speed ◽  
Brain Aging ◽  
Memory Task ◽  
Uk Biobank ◽  
Visual Reaction Time ◽  
Cohort Differences ◽  
Age Related ◽  
Visual Reaction ◽  
The Uk

To help identify factors influencing age-related cognitive decline and disease, a web-based simple visual reaction time (RT and svRT respectively, index of processing speed) and paired-associate learning (PAL, indexing of verbal episodic memory) task were implemented. Test results were combined with 22 survey questions. An analysis of RT and svTR data from the MindCrowd (n=75,666) cohort revealed education and reported stroke as potential modifiers of age-associated processing speed and memory decline. As a complement, we evaluated complex, recognition, reaction time (cvrRT) in the UK Biobank cohort and compared the results to a subset of the MindCrowd cohort, creating UKBb MindCrowd (n=39,795), mirroring the UK Biobank's (n=158,247) age range (40-70y). Many estimates from an identical linear model, used for both cohorts, were similar despite noted cohort differences (e.g., USA vs. the UK). Results from the UK Biobank that differed from UKBb MindCrowd included a first-degree family history Alzheimer's disease (FHAD) associated with slower cvrRTs and that sex and education affected age-related cvrRT slowing. While results from UKBb MindCrowd suggested that education and smoking status were related to opposite effects on age-related svRT slowing. MindCrowd's collected RT and PAL findings have begun to pull back the curtain on the intricate network connecting processing speed, memory, and cognition to healthy and pathological brain aging.

scholarly journals Two separate, large cohorts reveal potential modifiers of age-associated variation in visual reaction time performance

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
J. S. Talboom ◽  
M. D. De Both ◽  
M. A. Naymik ◽  
A. M. Schmidt ◽  
C. R. Lewis ◽  
...  
Keyword(s):  
Reaction Time ◽  
Visual Recognition ◽  
Uk Biobank ◽  
Associate Learning ◽  
Cross Sectional ◽  
Age Related ◽  
Visual Reaction ◽  
History Of ◽  
Potential Factors ◽  
The Uk

AbstractTo identify potential factors influencing age-related cognitive decline and disease, we created MindCrowd. MindCrowd is a cross-sectional web-based assessment of simple visual (sv) reaction time (RT) and paired-associate learning (PAL). svRT and PAL results were combined with 22 survey questions. Analysis of svRT revealed education and stroke as potential modifiers of changes in processing speed and memory from younger to older ages (ntotal = 75,666, nwomen = 47,700, nmen = 27,966; ages 18–85 years old, mean (M)Age = 46.54, standard deviation (SD)Age = 18.40). To complement this work, we evaluated complex visual recognition reaction time (cvrRT) in the UK Biobank (ntotal = 158,249 nwomen = 89,333 nmen = 68,916; ages 40–70 years old, MAge = 55.81, SDAge = 7.72). Similarities between the UK Biobank and MindCrowd were assessed using a subset of MindCrowd (UKBb MindCrowd) selected to mirror the UK Biobank demographics (ntotal = 39,795, nwomen = 29,640, nmen = 10,155; ages 40–70 years old, MAge = 56.59, SDAge = 8.16). An identical linear model (LM) was used to assess both cohorts. Analyses revealed similarities between MindCrowd and the UK Biobank across most results. Divergent findings from the UK Biobank included (1) a first-degree family history of Alzheimer’s disease (FHAD) was associated with longer cvrRT. (2) Men with the least education were associated with longer cvrRTs comparable to women across all educational attainment levels. Divergent findings from UKBb MindCrowd included more education being associated with shorter svRTs and a history of smoking with longer svRTs from younger to older ages.

scholarly journals Exogenous sex hormone effects on brain microstructure in women: a diffusion MRI study in the UK Biobank

2020 ◽  
Author(s):  
Leila Nabulsi ◽  
Katherine E. Lawrence ◽  
Vigneshwaran Santhalingam ◽  
Zvart Abaryan ◽  
Christina P. Boyle ◽  
...  
Keyword(s):  
White Matter ◽  
Volume Fraction ◽  
Brain Aging ◽  
Sex Hormone ◽  
Uk Biobank ◽  
Fractional Polynomial ◽  
Age Related ◽  
Hormone Exposure ◽  
The Uk ◽  
Quadratic Models

ABSTRACTThis study used advanced diffusion-weighted MRI (dMRI) to examine the association between exogenous sex-hormone exposure and the brain’s white matter aging trajectories in a large population-based sample of women. To investigate the effect of pre- and post-menopausal sex hormones on brain aging, cross-sectional brain dMRI data from the UK Biobank was analyzed using 3 diffusion models: conventional diffusion tensor imaging (DTI), the tensor distribution function (TDF), and neurite orientation dispersion and density imaging (NODDI). Mean skeletonized diffusivity measures were extracted and averaged across the whole brain, including fractional anisotropy, isotropic volume fraction, intracellular volume fraction and orientation dispersion index. We used general linear models and fractional polynomial regressions to characterize age-related trajectories in white matter measures following hormone therapy (HT) and oral contraceptive (OC) use in women (HT analysis: N=8,301; OC analysis: N=8,913). Sex hormone treatment (HT and OC) was statistically associated with the aging trends in white matter measures. Estrogen therapy alone appeared to exert a neuroprotective effect on age-related white matter processes, compared to HT containing both estrogen and progestin therapy – which was associated with accelerated aging-related processes in women. These results support the hypothesis that exogenous sex hormone exposure may impact white matter aging; white matter metrics may also be sensitive to sex hormone levels in women. Furthermore, we discuss the necessity to test alternative models for lifespan trajectories beyond popular linear and quadratic models, especially when dealing with large samples. Fractional polynomial models may provide a more adaptive alternative to linear or quadratic models.

scholarly journals Effects of High vs. Low Glycemic Index of Post-Exercise Meals on Sleep and Exercise Performance: A Randomized, Double-Blind, Counterbalanced Polysomnographic Study

Nutrients ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1795 ◽  
Author(s):  
Angelos Vlahoyiannis ◽  
George Aphamis ◽  
Eleni Andreou ◽  
George Samoutis ◽  
Giorgos Sakkas ◽  
...  
Keyword(s):  
Reaction Time ◽  
Glycemic Index ◽  
Exercise Performance ◽  
Sleep Onset ◽  
Interval Training ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Visual Reaction Time ◽  
Post Exercise ◽  
Visual Reaction

The aim of the current study was to investigate the effect of the glycemic index of post-exercise meals on sleep quality and quantity, and assess whether those changes could affect the next day’s exercise performance. Following a baseline/familiarization phase, 10 recreationally trained male volunteers (23.2 ± 1.8 years) underwent two double-blinded, randomized, counterbalanced crossover trials. In both trials, participants performed sprint interval training (SIT) in the evening. Post-exercise, participants consumed a meal with a high (HGI) or low (LGI) glycemic index. Sleep parameters were assessed by a full night polysomnography (PSG). The following morning, exercise performance was evaluated by the countermovement jump (CMJ) test, a visual reaction time (VRT) test and a 5-km cycling time trial (TT). Total sleep time (TST) and sleep efficiency were greater in the HGI trial compared to the LGI trial (p < 0.05), while sleep onset latency was shortened by four-fold (p < 0.05) and VRT decreased by 8.9% (p < 0.05) in the HGI trial compared to the LGI trial. The performance in both 5-km TT and CMJ did not differ between trials. A moderate to strong correlation was found between the difference in TST and the VRT between the two trials (p < 0.05). In conclusion, this is the first study to show that a high glycemic index meal, following a single spring interval training session, can improve both sleep duration and sleep efficiency, while reducing in parallel sleep onset latency. Those improvements in sleep did not affect jumping ability and aerobic endurance performance. In contrast, the visual reaction time performance increased proportionally to sleep improvements.

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