Integrating Three Characteristics of Executive Function in Non-Demented Aging: Trajectories, Classification, and Biomarker Predictors

Rhythmic musical activities may strengthen connectivity between brain networks associated with aging-related deficits in timing and executive functions

Brain aging and common conditions of aging (e.g., hypertension) affect networks important in organizing information, processing speed and action programming (i.e., executive functions). Declines in these networks may affect timing and could have an impact on the ability to perceive and perform musical rhythms. There is evidence that participation in rhythmic musical activities may help to maintain and even improve executive functioning (near transfer), perhaps due to similarities in brain regions underlying timing, musical rhythm perception and production, and executive functioning. Rhythmic musical activities may present as a novel and fun activity for older adults to stimulate interacting brain regions that deteriorate with aging. However, relatively little is known about neurobehavioral interactions between aging, timing, rhythm perception and production, and executive functioning. In this review, we account for these brain-behavior interactions to suggest that deeper knowledge of overlapping brain regions associated with timing, rhythm, and cognition may assist in designing more targeted preventive and rehabilitative interventions to reduce age-related cognitive decline and improve quality of life in populations with neurodegenerative disease. Further research is needed to elucidate the functional relationships between brain regions associated with aging, timing, rhythm perception and production, and executive functioning to direct design of targeted interventions.

Machine learning analyses identify multi-modal frailty factors that selectively discriminate four cohorts in the Alzheimer's disease spectrum: a COMPASS-ND study

BACKGROUND

Frailty indicators can operate in dynamic amalgamations of disease conditions, clinical symptoms, biomarkers, medical signals, cognitive characteristics, and even health beliefs and practices. This study is the first to evaluate which, among these multiple frailty-related indicators, are important and differential predictors of clinical cohorts that represent progression along an Alzheimer's disease (AD) spectrum. We applied machine-learning technology to such indicators in order to identify the leading predictors of three AD spectrum cohorts; viz., subjective cognitive impairment (SCI), mild cognitive impairment (MCI), and AD. The common benchmark was a cohort of cognitively unimpaired (CU) older adults.

METHODS

The four cohorts were from the cross-sectional Comprehensive Assessment of Neurodegeneration and Dementia dataset. We used random forest analysis (Python 3.7) to simultaneously test the relative importance of 83 multi-modal frailty indicators in discriminating the cohorts. We performed an explainable artificial intelligence method (Tree Shapley Additive exPlanation values) for deep interpretation of prediction effects.

RESULTS

We observed strong concurrent prediction results, with clusters varying across cohorts. The SCI model demonstrated excellent prediction accuracy (AUC = 0.89). Three leading predictors were poorer quality of life ([QoL]; memory), abnormal lymphocyte count, and abnormal neutrophil count. The MCI model demonstrated a similarly high AUC (0.88). Five leading predictors were poorer QoL (memory, leisure), male sex, abnormal lymphocyte count, and poorer self-rated eyesight. The AD model demonstrated outstanding prediction accuracy (AUC = 0.98). Ten leading predictors were poorer QoL (memory), reduced olfaction, male sex, increased dependence in activities of daily living (n = 6), and poorer visual contrast.

CONCLUSIONS

Both convergent and cohort-specific frailty factors discriminated the AD spectrum cohorts. Convergence was observed as all cohorts were marked by lower quality of life (memory), supporting recent research and clinical attention to subjective experiences of memory aging and their potentially broad ramifications. Diversity was displayed in that, of the 14 leading predictors extracted across models, 11 were selectively sensitive to one cohort. A morbidity intensity trend was indicated by an increasing number and diversity of predictors corresponding to clinical severity, especially in AD. Knowledge of differential deficit predictors across AD clinical cohorts may promote precision interventions.

Utility of the Comprehensive Trail Making Test in the Assessment of Mild Cognitive Impairment in Older Patients

INTRODUCTION

The purpose of this study is to determine the usefulness of the CTMT (Comprehensive Trail Making Test) in diagnosing mild cognitive impairment in older patients. The test is used to assess executive functions, of which impairment is already observed in the early stages of the neurodegenerative process.

MATERIALS AND METHODS

The study includes 98 patients of a geriatric ward assigned to 2 groups of 49 patients each: patients diagnosed with a mild cognitive impairment and patients without a cognitive impairment, constituting the control group (group K). A set of screening tests was used in the initial study: the MMSE (Mini-Mental State Examination), MoCA (Montreal Cognitive Assessment), and CDT (Clock Drawing Test), GDS (Geriatric Depression Scale). The second study included the performance of the CTMT; the performance indicator was the time of performance.

RESULTS

Statistically significant differences are obtained between patients with mild cognitive impairments and those in cognitive normality in the performance of the CTMT test (p < 0.01). Patients with MCIs took longer to complete all trails of the test. To identify cognitive impairment, cutoff points were proposed for the CTMT total score and the other test trails. The CTMT overall score and CTMT 5 scored the highest AUCs (CTMT overall score = 0.77, CTMT Trail 5 = 0.80).

CONCLUSIONS

The Comprehensive Trail Making Test may be useful in diagnosing mild cognitive impairment as a complementary screening tool.

Mentation Tracks Severity but not Oxygenation in Obstructive Sleep Apnea

There is a rough consensus, after decades of research, that obstructive sleep apnea (OSA) is associated with mild cognitive impairments, especially in areas of executive functioning (EF), attention/working memory (A/WM), episodic memory (EM), and speed of speed of information processing (SIP). However, there is less consensus as to whether apnea severity matters for these impairments, which sleep variables matter most to which cognitive domains, whether common OSA comorbidities contribute to these determinations, or whether the apparent associations are really artifacts of these comorbidities. In this study, 40 participants with OSA submitted to polysomnography and to neuropsychological assessment with an expanded Halstead-Reitan Test Battery. Aggregates of tests to cover the four cognitive domains mentioned above were linearly regressed on the apnea-hypopnea index (AHI), the nadir of oxygen saturation (NOS), and hypertension and diabetes mellitus (scored present or absent). The AHI predicted both EF (p = .015; sr2 = .13) and A/WM (p = .023; sr2 = 11) in the primary analyses, and EM (p = .027; sr2 = .10) in the secondary analyses. Thus, AHI may affect EF, A/WM and perhaps EM beyond NOS and beyond two of OSA's most common comorbidities. Implications of these findings are discussed here.

Recurrent but not single report of fear of falling predicts cognitive decline in community-residing older adults

OBJECTIVES

Literature regarding the association of fear of falling (FOF), a common concern in aging, and cognition is scarce. Moreover, whether frequency of FOF endorsement influences age-related cognitive decline has not been reported. Here we determined whether FOF status (no FOF, single-report FOF, recurrent FOF), predicted decline in global cognitive function (GCF), memory, and attention/executive functions.

METHODS

Participants were community-residing older adults (n = 421; mean age = 76.29 ± 6.48; %female = 56.06). FOF was assessed bimonthly through yes/no responses to "do you have a fear of falling?" during the first year of the study. Recurrent status required two or more FOF endorsements. GCF was assessed using Repeatable Battery for the Assessment of Neuropsychological Status (RBANS); composite scores were used to assess memory as well as attention/executive functions. Cognitive measures were administered annually for up to six years.

RESULTS

Stratification of the cohort by FOF status showed that 81 participants reported recurrent FOF, 60 participants endorsed FOF once and 280 participants reported no FOF. Linear mixed effects models revealed that compared to no FOF, recurrent FOF was associated with worse declines in GCF (estimate=-0.03, p=.006), memory (estimate=-0.04, p=.012) and attention/executive functions (estimate=-0.04, p=.006). Comparisons between single-report FOF and no FOF, however, were not significant.

CONCLUSIONS

These findings demonstrate that recurrent but not single-report FOF is a risk factor for cognitive decline in community-residing older adults.

Data-driven approaches to executive function performance and structure in aging: Integrating person-centered analyses and machine learning risk prediction

Objective: Executive function (EF) performance and structure in nondemented aging are frequently examined with variable-centered approaches. Person-centered analytics can contribute unique information about classes of persons by simultaneously considering EF performance and structure. The risk predictors of these classes can then be determined by machine learning technology. Using data from the Victoria Longitudinal Study we examined two goals: (a) detect different underlying subgroups (or classes) of EF performance and structure and (b) test multiple risk predictors for best discrimination of these detected subgroups. Method: We used a classification sample (n = 778; M_age = 71.42) for the first goal and a prediction subsample (n = 570; M_age = 70.10) for the second goal. Eight neuropsychological measures represented three EF dimensions (inhibition, updating, shifting). Fifteen predictors represented five domains (genetic, functional, lifestyle, mobility, demographic). Results: First, we observed two distinct classes: (a) lower EF performance and unidimensional structure (Class 1) and (b) higher EF performance and multidimensional structure (Class 2). Second, Class 2 was predicted by younger age, more novel cognitive activity, more education, lower body mass index, lower pulse pressure, female sex, faster balance, and more physical activity. Conclusions: Data-driven modeling approaches tested the possibility of an EF aging class that displayed both preserved EF performance levels and sustained multidimensional structure. The two observed classes differed in both performance level (lower, higher) and structure (unidimensional, multidimensional). Machine learning prediction analyses showed that the higher performing and multidimensional class was associated with multiple brain health-related protective factors. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Effects of Chinese Mind-Body Exercises on Executive Function in Middle-Aged and Older Adults: A Systematic Review and Meta-Analysis

Chinese mind-body exercises (CMBEs) are positively associated with executive function (EF), but their effects on EF, from synthesized evidence using systematic and meta-analytic reviews, have not been conducted. Therefore, the present systematic review with meta-analysis attempted to determine whether CMBEs affect EF and its sub-domains, as well as how exercise, sample, and study characteristics moderate the causal relationship between CMBEs and EF in middle-aged and older adults. Seven electronic databases were searched for relevant studies published from the inception of each database through June 2020 (PubMed, Web of Science, Embase, Cochrane Controlled Trials Register, Wanfang, China National Knowledge Infrastructure, and Weipu). Randomized controlled trials with at least one outcome measure of CMBEs on EF in adults of mean age ≥ 50 years with intact cognition or mild cognitive impairment (MCI) and with or without chronic diseases were included. A total of 29 studies (N = 2,934) ultimately were included in this study. The results indicated that CMBEs improved overall EF (Standardized Mean Differences = 0.28, 95% CI 0.12, 0.44), as well as its sub-domains of working memory and shifting. The beneficial effects of CMBEs on EF occurred regardless of type (Tai Chi, Qigong), frequency of group classes (≤2 time, 3-4 time, ≥5 times), session time (≤45 min, 46-60 min), total training time (≥150 to ≤300 min, >300 min), and length of the CMBEs (4-12 week, 13-26 week, and >26 week), in addition to that more frequent participation in both group classes and home practice sessions (≥5 times per week) resulted in more beneficial effects. The positive effects of CMBEs on EF were also demonstrated, regardless of participants mean age (50-65 years old, >65 years old), sex (only female, both), and cognitive statuses (normal, MCI, not mentioned), health status (with chronic disease, without chronic disease), as well as training mode (group class, group class plus home practice) and study language (English, Chinese). This review thus suggests that CMBEs can be used as an effective method with small to moderate and positive effects in enhancing EF, and that more frequent group classes and home practice sessions may increase these effects. However, certain limitations, including strictly design studies, limited ES (effect size) samples for specific variables, and possible biased publications, required paying particular attention to, for further exploring the effects of CMBEs on EF.