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A Developmental Perspective on Executive Function
This review article examines theoretical and methodological issues in the construction of a developmental perspective on executive function (EF) in childhood and adolescence. Unlike most reviews of EF, which focus on preschoolers, this review focuses on studies that include large age ranges. It outlines the development of the foundational components of EF— inhibition, working memory, and shifting. Cognitive and neurophysiological assessments show that although EF emerges during the first few years of life, it continues to strengthen significantly throughout childhood and adolescence. The components vary somewhat in their developmental trajectories. The article relates the findings to long-standing issues of development (e.g., developmental sequences, trajectories, and processes) and suggests research needed for constructing a developmental framework encompassing early childhood through adolescence.
Journal Article
Measuring sleep quality in older adults: a comparison using subjective and objective methods
Sleep quality decreases with aging and thus sleep complaints are prevalent in older adults, particularly for those with cognitive impairment and dementia. For older adults, emerging evidence suggests poor sleep quality increases risk of developing cognitive impairment and dementia. Given the aging population-and the impending economic burden associated with increasing numbers of dementia patients-there is pressing need to improve sleep quality among older adults. As such, research efforts have increased focus on investigating the association between age-related sleep changes and cognitive decline in older adults. Sleep quality is a complex construct to evaluate empirically, and yet the Pittsburg Sleep Quality Index (PSQI) is commonly used in studies as their only measure of sleep quality. Furthermore, the PSQI may not be the best sleep quality measure for older adults, due to its reliance on the cognitive capacity to reflect on the past month. Further study is needed to determine the PSQI's validity among older adults. Thus, the current study examined sleep quality for 78 community dwelling adults 55+ to determine the PSQI's predictive validity for objective sleep quality (as measured by actigraphy). We compared two subjective measures of sleep quality-the PSQI and Consensus Sleep Diary (CSD)-with actigraphy (MotionWatch 8©; camntech). Our results suggest perceived sleep quality is quite different from objective reality, at least for adults 55+. Importantly, we show this difference is unrelated to age, gender, education, or cognitive status (assessed using standard screens). Previous studies have shown the PSQI to be a valuable tool for assessing subjective sleep quality; however, our findings indicate for older adults the PSQI should not be used as a substitute for actigraphy, or vice versa. Hence, we conclude best practice is to include both subjective and objective measures when examining sleep quality in older adults (i.e., the PSQI, CSD, and actigraphy).
Journal Article
Predictors of the rate of cognitive decline in older adults using machine learning
The longitudinal rates of cognitive decline among aging populations are heterogeneous. Few studies have investigated the possibility of implementing prognostic models to predict cognitive changes with the combination of categorical and continuous data from multiple domains.
Implement a multivariate robust model to predict longitudinal cognitive changes over 12 years among older adults and to identify the most significant predictors of cognitive changes using machine learning techniques.
In total, data of 2733 participants aged 50-85 years from the English Longitudinal Study of Ageing are included. Two categories of cognitive changes were determined including minor cognitive decliners (2361 participants, 86.4%) and major cognitive decliners (372 participants, 13.6%) over 12 years from wave 2 (2004-2005) to wave 8 (2016-2017). Machine learning methods were used to implement the predictive models and to identify the predictors of cognitive decline using 43 baseline features from seven domains including sociodemographic, social engagement, health, physical functioning, psychological, health-related behaviors, and baseline cognitive tests.
The model predicted future major cognitive decliners from those with the minor cognitive decline with a relatively high performance. The overall AUC, sensitivity, and specificity of prediction were 72.84%, 78.23%, and 67.41%, respectively. Furthermore, the top 7 ranked features with an important role in predicting major vs minor cognitive decliners included age, employment status, socioeconomic status, self-rated memory changes, immediate word recall, the feeling of loneliness, and vigorous physical activity. In contrast, the five least important baseline features consisted of smoking, instrumental activities of daily living, eye disease, life satisfaction, and cardiovascular disease.
The present study indicated the possibility of identifying individuals at high risk of future major cognitive decline as well as potential risk/protective factors of cognitive decline among older adults. The findings could assist in improving the effective interventions to delay cognitive decline among aging populations.
Journal Article
The diagnostic performance of neurofilament light chain in CSF and blood for Alzheimer's disease, frontotemporal dementia, and amyotrophic lateral sclerosis: A systematic review and meta-analysis
A systematic review and meta-analysis was performed regarding the diagnostic performance of neurofilament light chain (NfL) in CSF and blood.
A database search was conducted for NfL biomarker studies in the context of Alzheimer's disease (AD), frontotemporal dementia (FTD), and amyotrophic lateral sclerosis (ALS) compared with controls (i.e., cognitively unimpaired, mild cognitive impairment, or disease mimics).
In groups with a sufficient number of studies, the performance of NfL in blood and CSF was similar. Compared with disease mimics, we observed that CSF NfL had strong discriminatory power for ALS, modest discriminatory power for FTD, and no discriminatory power for AD. NfL provided the greatest separation between ALS and cognitively unimpaired controls in both the blood and CSF, followed by FTD (CSF and blood), then AD (blood and CSF).
Comparable performance of CSF and blood NfL in many groups demonstrates the promise of NfL as a noninvasive biomarker of neurodegeneration; however, its utility in clinically meaningful scenarios requires greater scrutiny. Toward clinical implementation, a more comprehensive understanding of NfL concentrations in disease subtypes with overlapping phenotypes and at defined stages of disease, and the development of a harmonization program, are warranted.
Journal Article
Long-Term Effects of Resistance Exercise Training on Cognition and Brain Volume in Older Women: Results from a Randomized Controlled Trial
Aerobic exercise training has been shown to attenuate cognitive decline and reduce brain atrophy with advancing age. The extent to which resistance exercise training improves cognition and prevents brain atrophy is less known, and few studies include long-term follow-up cognitive and neuroimaging assessments. We report data from a randomized controlled trial of 155 older women, who engaged in 52 weeks of resistance training (either once- or twice-weekly) or balance-and-toning (twice-weekly). Executive functioning and memory were assessed at baseline, 1-year follow-up (i.e., immediately post-intervention), and 2-year follow-up. A subset underwent structural magnetic resonance imaging scans at those time points. At 2-year follow-up, both frequencies of resistance training promoted executive function compared to balance-and-toning (standardized difference [d]=.31–.48). Additionally, twice-weekly resistance training promoted memory (d=.45), reduced cortical white matter atrophy (d=.45), and increased peak muscle power (d=.27) at 2-year follow-up relative to balance-and-toning. These effects were independent of one another. These findings suggest resistance training may have a long-term impact on cognition and white matter volume in older women. (JINS, 2015, 21, 745–756)
Journal Article