Age changes in processing speed as a leading indicator of cognitive aging.

Bivariate dual change score models were applied to longitudinal data from the Swedish Adoption/Twin Study of Aging to compare the dynamic predictions of 2-component theories of intelligence and the processing speed theory of cognitive aging. Data from up to 5 measurement occasions covering a 16-year period were available from 806 participants ranging in age from 50 to 88 years at the first measurement wave. Factors were generated to tap 4 general cognitive domains: verbal ability, spatial ability, memory, and processing speed. Model fitting indicated no dynamic relationship between verbal and spatial factors, providing no support for the hypothesis that age changes in fluid abilities drive age changes in crystallized abilities. The results suggest that, as predicted by the processing speed theory of cognitive aging, processing speed is a leading indicator of age changes in memory and spatial ability, but not verbal ability. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Are processing speed tasks biomarkers of cognitive aging?

We examined the association between 5 processing speed measures and general cognitive ability in a large (>900) sample of relatively healthy men and women at age 70. The processing speed tests were the Wechsler Digit Symbol-Coding and Symbol Search, simple reaction time, 4-choice reaction time, and inspection time. To inquire whether the processing speed tasks might be biomarkers of cognitive aging, we examined the attenuations in their associations with general cognitive ability after adjusting for cognitive ability measured almost 60 years earlier. With the exception of inspection time, the attenuations were substantial. Inspection time was the only processing speed measure—all of which were measured at age 70—whose correlation with cognitive ability at age 70 was significantly greater than the correlation with cognitive ability at age 11. In old age, individual differences in most commonly used measures of processing speed are largely dependent on childhood cognitive ability. For all processing speed tasks, a little variance is left that appears to be related to aging differences. Inspection time, the marker that was least dependent on childhood intelligence, should be considered further as one biomarker of cognitive aging. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Aging, cognitive resources, and declarative learning.

A battery of cognitive tasks designed to assess information-processing speed, working memory capability, and declarative learning was administered to a cross-sectional sample of 477 adults ranging in age from 17 to 86 years. Results showed significant age-related decrements in all three constructs. A variety of structural equation models was fit to the results. The preferred model on empirical and conceptual grounds was one that showed (a) working memory capability as the most important mediator of age effects in declarative learning; (b) working memory capability as the mediator for the effects of general processing speed on declarative learning; and (c) differentiation among verbal, numeric, and spatial processing speed and between verbal and spatial working memory capability. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Performance variability is related to change in cognition: Evidence from the Victoria Longitudinal Study.

Performance variability across repeated task administrations may be an important indicator of age-related cognitive functioning. In the present investigation, the authors examined whether age differences and change in inconsistency were related to 6-year (3 occasion) cognitive change. Inconsistency scores were computed from 4 reaction time tasks performed by 446 older adults (54-89 years). Replicating previous cross-sectional results, greater inconsistency was observed for older participants even after controlling for differences in response speed. New longitudinal results demonstrated (a) associations between inconsistency at baseline measurement and 6-year change in cognitive performance; (b) longitudinal change in inconsistency; and (c) intraindividual covariation between 6-year change in inconsistency and 6-year change in level of cognitive function. These findings support the view that performance variability serves as a marker of cognitive aging. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Genetic variance in processing speed drives variation in aging of spatial and memory abilities.

Previous analyses have identified a genetic contribution to the correlation between declines with age in processing speed and higher cognitive abilities. The goal of the current analysis was to apply the biometric dual change score model to consider the possibility of temporal dynamics underlying the genetic covariance between aging trajectories for processing speed and cognitive abilities. Longitudinal twin data from the Swedish Adoption/Twin Study of Aging, including up to 5 measurement occasions covering a 16-year period, were available from 806 participants ranging in age from 50 to 88 years at the 1st measurement wave. Factors were generated to tap 4 cognitive domains: verbal ability, spatial ability, memory, and processing speed. Model-fitting indicated that genetic variance for processing speed was a leading indicator of variation in age changes for spatial and memory ability, providing additional support for processing speed theories of cognitive aging. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Latent Change Models of Adult Cognition: Are Changes in Processing Speed and Working Memory Associated With Changes in Episodic Memory?

The authors used 6-year longitudinal data from the Victoria Longitudinal Study (VLS) to investigate individual differences in amount of episodic memory change. Latent change models revealed reliable individual differences in cognitive change. Changes in episodic memory were significantly correlated with changes in other cognitive variables, including speed and working memory. A structural equation model for the latent change scores showed that changes in speed and working memory predicted changes in episodic memory, as expected by processing resource theory. However, these effects were best modeled as being mediated by changes in induction and fact retrieval. Dissociations were detected between cross-sectional ability correlations and longitudinal changes. Shuffling the tasks used to define the Working Memory latent variable altered patterns of change correlations. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Can longitudinal changes in processing speed explain longitudinal age changes in fluid intelligence?

The processing-speed theory of cognitive aging contends that age-related declines in intellectual function reflect the consequences of age-related slowing of processing speed. Cross-sectional data support this assumption. The association between 4-year changes in processing speed and 4-year changes in fluid intelligence was examined with a sample of 417 older adults. Changes in processing speed correlated .53 with changes in fluid intelligence. The difference in the explanatory power of processing speed regarding age-related differences and age-related changes is discussed with reference to other longitudinal studies and methodological considerations. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Contribution of age, genes, and environment to the relationship between perceptual speed and cognitive ability.

The aim of this study was to examine genetic influences on cognitive ability in adulthood in the context of the relationship between perceptual speed and cognitive aging. Quantitative genetic analysis of data from the Swedish Adoption Twin Study of Aging allowed for estimation of the contribution of age, genetic, and environmental effects to the variance in a latent cognitive factor and to the covariance between the cognitive factor and perceptual speed. The sample included 292 pairs of monozygotic and dizygotic twins, both reared together and reared apart, ranging in age from 40 to 84 years. Analysis of components of total variance in the cognitive factor indicated that 90% of the age-related variance in the cognitive factor was shared with perceptual speed and 70% of the genetic variance in the cognitive factor was shared with perceptual speed. The correlation between the speed and cognitive factors was primarily genetically mediated. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Only time will tell: Cross-sectional studies offer no solution to the age–brain–cognition triangle: Comment on Salthouse (2011).

Salthouse (2011) critically reviewed cross-sectional and longitudinal relations among adult age, brain structure, and cognition (ABC) and identified problems in interpretation of the extant literature. His review, however, missed several important points. First, there is enough disparity among the measures of brain structure and cognitive performance to question the uniformity of B and C vertices of the ABC triangle. Second, age differences and age changes in brain and cognition are often nonlinear. Third, variances and correlations among measures of brain and cognition frequently vary with age. Fourth, cross-sectional comparisons among competing models of ABC associations cannot disambiguate competing hypotheses about the structure and the range of directed and reciprocal relations between changes in brain and behavior. We offer the following conclusions, based on these observations. First, individual differences among younger adults are not useful for understanding the aging of brain and behavior. Second, only multivariate longitudinal studies, age-comparative experimental interventions, and a combination of the two will deliver us from the predicaments of the ABC triangle described by Salthouse. Mediation models of cross-sectional data represent age-related differences in target variables but fail to approximate time-dependent relations; thus, they do not elucidate the dimensions and dynamics of cognitive aging. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Neuroanatomical and cognitive mediators of age-related differences in episodic memory.

Aging is associated with declines in episodic memory. In this study, the authors used a path analysis framework to explore the mediating role of differences in brain structure, executive functions, and processing speed in age-related differences in episodic memory. Measures of regional brain volume (prefrontal gray and white matter, caudate, hippocampus, visual cortex), executive functions (working memory, inhibitory control, task switching, temporal processing), processing speed, and episodic memory were obtained in a sample of young and older adults. As expected, age was linked to reduction in regional brain volumes and cognitive performance. Moreover, neural and cognitive factors completely mediated age differences in episodic memory. Whereas hippocampal shrinkage directly affected episodic memory, prefrontal volumetric reductions influenced episodic memory via limitations in working memory and inhibitory control. Age-related slowing predicted reduced efficiency in temporal processing, working memory, and inhibitory control. Lastly, poorer temporal processing directly affected episodic memory. No direct effects of age on episodic memory remained once these factors were taken into account. These analyses highlight the value of a multivariate approach with the understanding of complex relationships in cognitive and brain aging. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Hearing loss and cognition in the Baltimore Longitudinal Study of Aging.

Objective: To determine the relationship between hearing loss and cognitive function as assessed with a standardized neurocognitive battery. We hypothesized a priori that greater hearing loss is associated with lower cognitive test scores on tests of memory and executive function. Method: A cross-sectional cohort of 347 participants ≥55 years in the Baltimore Longitudinal Study of Aging without mild cognitive impairment or dementia had audiometric and cognitive testing performed in 1990–1994. Hearing loss was defined by an average of hearing thresholds at 0.5, 1, 2, and 4 kHz in the better-hearing ear. Cognitive testing consisted of a standardized neurocognitive battery incorporating tests of mental status, memory, executive function, processing speed, and verbal function. Regression models were used to examine the association between hearing loss and cognition while adjusting for confounders. Results: Greater hearing loss was significantly associated with lower scores on measures of mental status (Mini-Mental State Exam), memory (Free Recall), and executive function (Stroop Mixed, Trail Making B). These results were robust to analyses accounting for potential confounders, nonlinear effects of age, and exclusion of individuals with severe hearing loss. The reduction in cognitive performance associated with a 25 dB hearing loss was equivalent to the reduction associated with an age difference of 6.8 years. Conclusion: Hearing loss is independently associated with lower scores on tests of memory and executive function. Further research examining the longitudinal association of hearing loss with cognitive functioning is needed to confirm these cross-sectional findings. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

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. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Cortical gray matter atrophy in healthy aging cannot be explained by undetected incipient cognitive disorders: A comment on Burgmans et al. (2009).

Burgmans, van Boxtel, Vuurman, et al. (2009) published an interesting study titled “The Prevalence of Cortical Gray Matter Atrophy May Be Overestimated in the Healthy Aging Brain” on how subclinical cognitive disorders may affect correlations between age and cortical volume. Correlations between cortical gray matter volume and age were found in 30 elderly with cognitive decline after 6 years, but not in 28 elderly without cognitive decline. This study is important, and demonstrates that preclinical cognitive disorders may affect cortical brain volumes before being detectable by neuropsychological tests. However, we are not convinced by the conclusions: “… gray matter atrophy… is to a lesser extent associated with the healthy aging process, but more likely with brain processes underlying significant cognitive decline” (p. 547) and “… cortical gray matter atrophy in the aging brain may be overestimated in a large number of studies on healthy aging” (p. 547). We analyzed the cross-sectional MR data (n = 1,037) as well as longitudinal data from a sample of very well-screened elderly followed by cognitive testing for 2 years. In the cross-sectional data, the correlations between age and brain volumes were generally not much reduced when the upper age limit was lowered. This would not be expected if age-related incipient cognitive disorders caused the correlations given that the incidence of cognitive decline increased with age. Longitudinally, 1-year atrophy was identified in all tested regions. It is likely that cortical brain atrophy is manifested in cognitively normal elderly without subclinical cognitive disorders. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Smarter in middle age, faster in old age: A cross-lagged panel analysis of reaction time and cognitive ability over 13 years in the West of Scotland Twenty-07 Study.

Participants in the West of Scotland Twenty-07 Study performed reaction time tasks and took the Alice Heim 4 Part 1 test (AH4) of intelligence twice, 13 years apart. Cross-lagged associations between speed of processing and AH4 were examined using latent variables in structural equation modeling. The stability coefficients of the latent traits of processing speed and of AH4 score across 13 years were .49 and .89, respectively. There was a significant association (?.21) between AH4 score at age 56 and speed of processing at age 69 but not vice versa. The results fail to support the theory that processing speed is a foundation for successful cognitive aging but support a hypothesis that suggests that higher general intelligence might be associated with lifestyle and other factors that preserve processing speed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Free testosterone levels, attentional control, and processing speed performance in aging men.

Psychometric measures of processing speed are strong predictors of cognitive functioning with aging; however, the neurobiological mechanisms underlying this association remain unclear. Recently, the authors reported a negative association between calculated free testosterone levels (cEFT) and processing speed in men aged between 50 and 70 years (Martin, Wittert, Burns, & McPherson, 2008). Ex-Gaussian decomposition of reaction time (RT) distributions allows for the robust estimation of skew in the distribution, which may reflect poorer attentional control. In a reanalysis of data from this previous study, the authors examined the associations between age, cEFT levels, and ex-Gaussian parameters derived from four RT tasks as predictors of cognitive functioning performance in 96 middle-to-older aged men. Results indicated that cEFT levels were significantly associated with increased skew in the RT distribution (i.e., the exponential portion) but not with the estimates derived from the Gaussian portion of the curve. Further, path analysis across the entire data set showed that this association was a strong predictor of processing speed performance. Taken together these results suggest that cEFT levels moderate cognitive functioning performance in males via attentional control processes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

How do health and biological age influence chronological age and sex differences in cognitive aging: Moderating, mediating, or both?

Much research on cognitive competence in normal older adults has documented age and sex differences. The authors used new cross-sectional data from the Victoria Longitudinal Study (VLS) (n = 386; age 61 to 95 years) to examine how health and biological age influence age and sex differences in cognitive aging. The authors found evidence for both moderating and mediating influences. Age differences were moderated by health status, such that the negative effects of age were most pronounced among participants of relatively better health. Sex differences were moderated by health and were more pronounced among participants reporting comparatively poorer health. Although health mediated a notable amount of age-related cognitive variation, BioAge mediated considerably more variance, even after statistical control for differences in health. A complex pattern emerged for the mediation of sex differences: Although BioAge accounted for sex-related variation in cognitive performance, health operated to suppress these differences. Overall, both health and BioAge predicted cognitive variation independently of chronological age. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Aging, vascular risk, and cognition: Blood glucose, pulse pressure, and cognitive performance in healthy adults.

Advanced age is associated with decline in many areas of cognition as well as increased frequency of vascular disease. Well-described risk factors for vascular disease, such as diabetes and arterial hypertension, have been linked to cognitive deficits beyond those associated with aging. To examine whether vascular health indices such as fasting blood glucose levels and arterial pulse pressure can predict subtle deficits in age-sensitive abilities, the authors studied 104 healthy adults (ages 18 to 78) without diagnoses of diabetes or hypertension. Whereas results revealed a classic pattern of age-related differences in cognition, preprandial blood glucose level and pulse pressure independently and differentially affected cognitive performance. High-normal blood glucose levels were associated with decreased delayed associative memory, reduced accuracy of working memory processing among women, and slower working memory processing among men. Elevated pulse pressure was associated with slower perceptual–motor processing. Results suggest that blood glucose levels and pulse pressure may be sensitive indicators of cognitive status in healthy adults; however, longitudinal research is needed to determine whether such relatively mild elevations in this select group predict age-related cognitive declines. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Processing speed and memory mediate age-related differences in decision making.

Decision making under risk changes with age. Increases in risk aversion with age have been most commonly characterized, although older adults may be risk seeking in some decision contexts. An important, and unanswered, question is whether these changes in decision making reflect a direct effect of aging or, alternatively, an indirect effect caused by age-related changes in specific cognitive processes. In the current study, older adults (M = 71 years) and younger adults (M = 24 years) completed a battery of tests of cognitive capacities and decision-making preferences. The results indicated systematic effects of age upon decision quality—with both increased risk seeking and increased risk aversion observed in different tasks—consistent with prior studies. Path analyses, however, revealed that age-related effects were mediated by individual differences in processing speed and memory. When those variables were included in the model, age was no longer a significant predictor of decision quality. The authors conclude that the reduction in decision quality and associated changes in risk preferences commonly ascribed to aging are instead mediated by age-related changes in underlying cognitive capacities. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Stress-related cognitive interference predicts cognitive function in old age.

Both subjective distress and cognitive interference have been proposed as mechanisms underlying the negative effects of stress on cognition. Studies of aging have shown that distress is associated with lower cognitive performance, but none have examined the effects of cognitive interference. One hundred eleven older adults (Mage=80) completed measures of working memory, processing speed, and episodic memory as well as self-report measures of subjective distress and cognitive interference. Cognitive interference was strongly associated with poorer performance on all 3 cognitive constructs, whereas distress was only modestly associated with lower working memory. The results suggest that cognitive process related to stress is an important predictor of cognitive function in advanced age. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Interrelationships among biological markers of aging, health, activity, acculturation, and cognitive performance in late adulthood.

In this study a structural equation model of predictors of age differences in cognitive performance in late adulthood was developed. Biological markers of aging (vision, hearing, vibration sense, forced expiratory volume, and grip strength) were used as indicators of a latent variable called BioAge. A sample of 180 community-dwelling women aged 60 to 90 years was assessed. Results showed that BioAge explained all of the age-related variance in cognitive test performance. Physical health and physical activity had direct effects on BioAge. Measures of acculturation explained non-age-related variance in cognitive test performance. Some variables used as biomarkers also explained individual differences in measures of crystallized intelligence and perceptual speed. It is concluded that the association between biomarkers and cognition in old age is due to more than a common statistical association with age. (PsycINFO Database Record (c) 2010 APA, all rights reserved)