Cognition in the Berlin Aging Study (BASE): The First 10 Years

This paper summarizes and expands research on cognitive aging from the Berlin Aging Study (BASE), a longitudinal, multidisciplinary, and population-based investigation of old and very old individuals. First, we describe previously reported research on five key themes: (a) experimental and mortality-associated components of longitudinal selectivity; (b) comparisons between cross-sectional and cross-sectional/longitudinal convergence age gradients; (c) old-age dedifferentiation of inter-individual differences; (d) possible reasons for the age-based increase in the link between intellectual and sensory domains; and (e) limits to cognitive plasticity in very old age. Second, we make use of multilevel modeling to determine the magnitude and direction of retest effects. Retest effects are classified as either flat (step function from the first to the second measurement occasion) or growing (linear increase after the first measurement occasion). Five of the eight longitudinally administered cognitive tests are found to display significant retest effects of either or both types. Retest adjustment increased the linear negative and decreased the quadratic negative component of cross-sectional/longitudinal convergence gradients in measures of intellectual abilities.     

Out of sight,out of mind? Relations between visual acuity and cognition

Prior research has established significant relations between measures of sensory ability and cognitive function in adults of different ages, and several explanations for this relation have been proposed. One explanation is that sensory abilities restrict cognitive processing, a second is that cognitive abilities influence assessments of sensory ability, and a third is that both sensory function and cognition are affected by a common, potentially age-based, third factor. These explanations were investigated using mediation and moderation analyses, with near visual acuity as the sensory measure and scores on visual speed tests and auditory memory tests as the cognitive measures. Measures of visual acuity, speed, and memory were obtained from three moderately large samples, two cross-sectional (N?=?380, N?=?4,779) and one longitudinal (N?=?2,258), with participants ranging from 18 to 90 years of age. The visual acuity and cognitive measures had different age trajectories, and the visual acuity–cognition relations were similar in each 5-year age band. The results suggest that the age-related differences and changes in near visual acuity are unlikely to contribute to the age-related differences and changes in speed and memory measures.     

认知年老化与执行衰退假说

在认知年老化领域,执行衰退假说是近年来新兴的一种理论。执行衰退假说在理论上具有很强的吸引力,但在实证研究中却存在很多困难,如执行功能的可分离性问题,执行功能测量的信度和效度问题,以及执行功能与加工速度的关系问题。目前,该领域研究的焦点是：在行为学水平上,控制一般性因素（加工速度）后,执行功能是否仍对认知年老化起重要的中介作用;在神经水平上,执行（额叶）功能随龄的变化情况,以及在认知年老化过程中,额叶在大脑功能重组中扮演的角色。最终实现对认知年老化的理解,需要将认知功能与大脑结构联系起来;既看到广泛存在的共同的基本机制,又不能忽略不同认知结构的选择性变化。     

Cerebral White Matter Integrity and Cognitive Aging: Contributions from Diffusion Tensor Imaging

The integrity of cerebral white matter is critical for efficient cognitive functioning, but little is known regarding the role of white matter integrity in age-related differences in cognition. Diffusion tensor imaging (DTI) measures the directional displacement of molecular water and as a result can characterize the properties of white matter that combine to restrict diffusivity in a spatially coherent manner. This review considers DTI studies of aging and their implications for understanding adult age differences in cognitive performance. Decline in white matter integrity contributes to a disconnection among distributed neural systems, with a consistent effect on perceptual speed and executive functioning. The relation between white matter integrity and cognition varies across brain regions, with some evidence suggesting that age-related effects exhibit an anterior–posterior gradient. With continued improvements in spatial resolution and integration with functional brain imaging, DTI holds considerable promise, both for theories of cognitive aging and for translational application.     

What Can We Learn From Longitudinal Studies of Adult Development?

This article distinguishes between normal and pathological aging, provides an interdisciplinary context, and then considers a sample case of cognitive aging. Developmental influences on cognition include the physiological infrastructure, genetic predispositions, and environmental influences. Different types of longitudinal studies are distinguished, and contrasting findings of cross-sectional and longitudinal studies are examined in the sample case of the Seattle Longitudinal Study. Also considered is the longitudinal context for intervention studies and the role of longitudinal family studies in assessing rate of aging and generational differences in rates of aging. Finally, attention is given to the role of longitudinal studies in the early detection of risk for dementia in advanced age.     

What Can We Learn From Longitudinal Studies of Adult Development?

This article distinguishes between normal and pathological aging, provides an interdisciplinary context, and then considers a sample case of cognitive aging. Developmental influences on cognition include the physiological infrastructure, genetic predispositions, and environmental influences. Different types of longitudinal studies are distinguished, and contrasting findings of cross-sectional and longitudinal are examined in the sample case of the Seattle Longitudinal Study. Also considered is the longitudinal context for intervention studies and the role of longitudinal family studies in assessing rate of aging and generational differences in rates of aging. Finally, attention is given to the role of longitudinal studies in the early detection of risk for dementia in advanced age.     

Neuroanatomical substrates of age-related cognitive decline

There are many reports of relations between age and cognitive variables and of relations between age and variables representing different aspects of brain structure and a few reports of relations between brain structure variables and cognitive variables. These findings have sometimes led to inferences that the age-related brain changes cause the age-related cognitive changes. Although this conclusion may well be true, it is widely recognized that simple correlations are not sufficient to warrant causal conclusions, and other types of correlational information, such as mediation and correlations between longitudinal brain changes and longitudinal cognitive changes, also have limitations with respect to causal inferences. These issues are discussed, and the existing results on relations of regional volume, white matter hyperintensities, and diffusion tensor imaging measures of white matter integrity to age and to measures of cognitive functioning are reviewed. It is concluded that at the current time the evidence that these aspects of brain structure are neuroanatomical substrates of age-related cognitive decline is weak. The final section contains several suggestions concerning measurement and methodology that may lead to stronger conclusions in the future.     

The Neuropsychology of HIV/AIDS in Older Adults

Highly active antiretroviral therapy is allowing increasing numbers of adults to age with HIV. The neuropsychological effects of aging with HIV are reviewed through three types of studies. First, the separate effects of HIV and aging on cognition are examined in studies that compare younger adults with HIV with neurologically normal older adults. Second, studies examine the impact of aging within samples of adults with HIV only. Third, providing the most critical evidence, are studies that assess cognition in younger and older adults with HIV relative to younger and older adults without HIV. In general research findings are inconclusive. Large individual differences among older adults with HIV as well as co-factors (APOE4 and detectable viral load) may account for inconsistent findings in the literature. A subgroup of older adults with HIV may be at greater risk for cognitive impairment, especially in attention functioning.     

Cross-sectional and longitudinal relationships among age, cognition, and processing speed

Cross-sectional and longitudinal age effects on cognitive function were examined in 302 older adults followed longitudinally. Processing speed was related to cognitive performance at cross-section, and change in speed predicted within-person longitudinal cognitive decline. Statistical control of processing speed greatly reduced cross-sectional age effects but did not attenuate longitudinal aging effects. This difference in processing speed's ability to account for cross-sectional and longitudinal age effects is discussed in the context of theories of cognitive aging and methodological and statistical issues pertaining to the cross-sectional and longitudinal study of cognitive aging.     

All data collection and analysis methods have limitations: reply to Rabbitt (2011) and Raz and Lindenberger (2011)

The commentaries on my article contain a number of points with which I disagree but also several with which I agree. For example, I continue to believe that the existence of many cases in which between-person variability does not increase with age indicates that greater variance with increased age is not inevitable among healthy individuals up to about 80 years of age. I also do not believe that problems of causal inferences from correlational information are more severe in the cognitive neuroscience of aging than in other research areas; I contend instead that neglect of these problems has led to confusion about neurobiological underpinnings of cognitive aging. I agree that researchers need to be cautious in extrapolating from cross-sectional to longitudinal relations, but I also note that even longitudinal data are limited with respect to their ability to support causal inferences.     

Category norms as a function of culture and age: comparisons of item responses to 105 categories by american and chinese adults

Understanding how aging influences cognition across different cultures has been hindered by a lack of standardized, cross-referenced verbal stimuli. This study introduces a database of such item-level stimuli for both younger and older adults, in China and the United States, and makes 3 distinct contributions. First, the authors specify which item categories generalize across age and/or cultural groups, rigorously quantifying differences among them. Second, they introduce novel, powerful methods to measure between-group differences in freely generated ranked data, the rank-ordered logit model and Hellinger Affinity. Finally, a broad archive of tested, cross-linguistic stimuli is now freely available to researchers: data, similarity measures, and all stimulus materials for 105 categories and 4 culture-by-age groups, comprising over 10,000 fully translated unique item responses.     

Age-related differences in acquisition of perceptual-motor skills: working memory as a mediator

Aging is associated with reduced performance on information processing speed, memory, and executive functions tasks. Although older adults are also less apt in acquiring new perceptual-motor skills, it is unclear whether and how skill acquisition difficulties are associated with age-related general cognitive differences. We addressed this question by examining structural relations among measures of cognitive resources (working memory) and indices of perceptual-motor skill acquisition (pursuit rotor and mirror tracing) in 96 healthy adults aged 19-80 years of age. Three competing structural models were tested: a single (common) factor model, a dual correlated factors model, and a hierarchical dual-factor model. The third model provided the best fit to the data, indicating age differences in simple perceptual-motor skill are partially mediated by more complex abilities.     

How shared are age-related influences on cognitive and noncognitive variables?

Several theories have suggested that age-related declines in cognitive processing are due to a pervasive unitary mechanism, such as a decline in processing speed. Structural equation model tests have shown some support for such common factor explanations. These results, however, may not be as conclusive as previously claimed. A further analysis of 4 cross-sectional data sets described in Salthouse, Hambrick, and McGuthry (1998) and Salthouse and Czaja (2000) found that although the best fitting model included a common factor in 3 of the data sets, additional direct age paths were significant, indicating the presence of specific age effects. For the remaining data set, a factor-specific model fit at least as well as the best fitting common factor model. Three simulated data sets with known structure were then tested with a sequence of structural equation models. Common factor models could not always be falsified--even when they were false. In contrast, factor-specific models were more easily falsified when the true model included a unitary common factor. These results suggest that it is premature to conclude that all age-related cognitive declines are due to a single mechanism. Common factor models may be particularly difficult to falsify with current analytic procedures.     

Proactive interference in working memory is related to adult age and cognitive factors: cross-sectional and longitudinal evidence from the Betula study

ABSTRACT

In working memory (WM), successful maintenance of information is affected by interference. Older adults may be especially susceptible to the effects of interference, which may cause age-related cognitive impairments. A relative score of IC was derived from cross-sectional (n = 869) and longitudinal (n = 443) data to investigate (1) if IC is reduced in normal aging, (2) if individual differences in IC related to individual performance in other cognitive domains, and (3) if 5-year change in IC is related to change in general cognition. Older age was associated with reduced IC, but no decline in IC occurred over 5 years. Also, the ability to control interference in WM was related to performance in episodic memory, verbal fluency, and block design. We also found that IC mediates the relationship between age and cognition, suggesting that age-related cognitive decline is linked to IC. Finally, we demonstrate that change in IC was related to decline in episodic memory.     

Age-Related Differences in Acquisition of Perceptual-Motor Skills: Working Memory as a Mediator

ABSTRACT

Aging is associated with reduced performance on information processing speed, memory, and executive functions tasks. Although older adults are also less apt in acquiring new perceptual-motor skills, it is unclear whether and how skill acquisition difficulties are associated with age-related general cognitive differences. We addressed this question by examining structural relations among measures of cognitive resources (working memory) and indices of perceptual-motor skill acquisition (pursuit rotor and mirror tracing) in 96 healthy adults aged 19–80 years of age. Three competing structural models were tested: a single (common) factor model, a dual correlated factors model, and a hierarchical dual-factor model. The third model provided the best fit to the data, indicating age differences in simple perceptual-motor skill are partially mediated by more complex abilities.     

On the confounds among retest gains and age-cohort differences in the estimation of within-person change in longitudinal studies: a simulation study

Although longitudinal designs are the only way in which age changes can be directly observed, a recurrent criticism involves to what extent retest effects may downwardly bias estimates of true age-related cognitive change. Considerable attention has been given to the problem of retest effects within mixed effects models that include separate parameters for longitudinal change over time (usually specified as a function of age) and for the impact of retest (specified as a function of number of exposures). Because time (i.e., intervals between assessment) and number of exposures are highly correlated (and are perfectly correlated in equal interval designs) in most longitudinal studies, the separation of effects of within-person change from effects of retest gains is only possible given certain assumptions (e.g., age convergence). To the extent that cross-sectional and longitudinal effects of age differ, obtained estimates of aging and retest may not be informative. The current simulation study investigated the recovery of within-person change (i.e., aging) and retest effects from repeated cognitive testing as a function of number of waves, age range at baseline, and size and direction of age-cohort differences on the intercept and age slope in age-based models of change. Significant bias and Type I error rates in the estimated effects of retest were observed when these convergence assumptions were not met. These simulation results suggest that retest effects may not be distinguishable from effects of aging-related change and age-cohort differences in typical long-term traditional longitudinal designs.     

Latent variable analyses of age trends of cognition in the Health and Retirement Study, 1992-2004

The present study was conducted to better describe age trends in cognition among older adults in the longitudinal Health and Retirement Study (HRS) from 1992 to 2004 (N = 17,000). The authors used contemporary latent variable models to organize this information in terms of both cross-sectional and longitudinal inferences about age and cognition. Common factor analysis results yielded evidence for at least 2 common factors, labeled Episodic Memory and Mental Status, largely separable from vocabulary. Latent path models with these common factors were based on demographic characteristics. Multilevel models of factorial invariance over age indicated that at least 2 common factors were needed. Latent curve models of episodic memory were based on age at testing and showed substantial age differences and age changes, including impacts due to retesting as well as several time-invariant and time-varying predictors.     

Modeling Intraindividual Cognitive Change in Aging Adults: Results from the Einstein Aging Studies

This paper reviews research from the longitudinal Einstein Aging Studies (EAS) that has focused on modeling intraindividual cognitive change in aging adults. We describe how to separate models of intraindividual change at the within-person level from models of individual differences in change at the between-person level. We illustrate this distinction by analyzing new data from the EAS to test the speed hypothesis at the intraindividual level of analyses. The present findings replicate those of Sliwinski and Buschke (1999) by showing that within-person changes in speed predict within-person changes in cognition, but that speed does not substantially attenuate estimates of within-person cognitive decline. We conclude that correct measurement and explanatory modeling of intraindividual change should be the primary focus of longitudinal aging research, and that the more common practice of modeling individual differences in change should be a secondary focus.     

Plasticity of brain and cognition in older adults

Aging is typically related to changes in brain and cognition, but the aging process is heterogeneous and differs between individuals. Recent research has started investigating the influence of cognitive and physical training on cognitive performance, functional brain activity, and brain structure in old age. The functional relevance of neural changes and the interactions among these changes following interventions is still a matter of debate. Here we selectively review research on structural and functional brain correlates of training-induced performance changes in healthy older adults and present exemplary longitudinal intervention studies sorted by the type of training applied (i.e., strategy-based training, process-specific training, and physical exercise). Although many training studies have been conducted recently, within each task domain, the number of studies that used comparable methods and techniques to assess behavioral and neural changes is limited. We suggest that future studies should include a multimodal approach to enhance the understanding of the relation between different levels of brain changes in aging and those changes that result from training. Investigating inter-individual differences in intervention-induced behavioral and neuronal changes would provide more information about who would benefit from a specific intervention and why. In addition, a more systematic examination of the time course of training-related structural and functional changes would improve the current level of knowledge about how learning is implemented in the brain and facilitate our understanding of contradictory results.