The study of aging and cognitive skill learning is concerned with age-related changes and differences in how we gather, store, and use information and abilities. As life expectancy continues to rise, resulting in greater numbers and proportions of older individuals in the population, understanding the development and retention of skills across the lifespan is increasingly important. Older adults’ task performance in cognitive skill learning is often equal to that of young adults, albeit not as efficient, where older adults often require more time to complete training. Investigations of age differences in fundamental cognitive processes of attention, memory, or executive functioning generally reveal declines in older adults. These are related to a slowing of cognitive processing. Slowing in cognitive processing results in longer time necessary to complete tasks which can interfere with the fidelity of older adults’ cognitive processes in time-limited scenarios. Despite this, older adults maintain comparable rates of learning with young adults, albeit with some reduced efficiency in more complex tasks. The effectiveness of older adults’ learning is also impacted by a lesser tendency to recognize and adopt efficient learning strategies, as well as less flexibility in strategy use relative to younger adults. In learning tasks that involve a transition from using a complex initial strategy to relying on memory retrieval, older adults show a volitional avoidance of memory that is related to lower memory confidence and an impoverished mental model of the task. Declines in learning are not entirely problematic from a functional perspective, however, as older adults can often rely upon their extensive knowledge to compensate for certain deficiencies, particularly in everyday tasks. Indeed, domains where older adults have maintained expertise are somewhat insulated from other age-related declines.
Jack Kuhns and Dayna R. Touron
Gianluca Susi, Jaisalmer de Frutos-Lucas, Guiomar Niso, Su Miao Ye-Chen, Luis Antón Toro, Brenda Nadia Chino Vilca, and Fernando Maestú
Oscillatory activity present in brain signals reflects the underlying time-varying electrical discharges within and between ensembles of neurons. Among the variety of non-invasive techniques available for measuring of the brain’s oscillatory activity, magnetoencephalography (MEG) presents a remarkable combination of spatial and temporal resolution, and can be used in resting-state or task-based studies, depending on the goals of the experiment. Two important kinds of analysis can be carried out with the MEG signal: spectral a. and functional connectivity (FC) a. While the former provides information on the distribution of the frequency content within distinct brain areas, FC tells us about the dependence or interaction between the signals stemming from two (or among many) different brain areas. The large frequency range combined with the good resolution offered by MEG makes MEG-based spectral and FC analyses able to highlight distinct patterns of neurophysiological alterations during the aging process in both healthy and pathological conditions. Since disruption in spectral content and functional interactions between brain areas could be accounted for by early neuropathological changes, MEG could represent a useful tool to unveil neurobiological mechanisms related to the cognitive decline observed during aging, particularly suitable for the detection of functional alterations, and then for the discovery of potential biomarkers in case of pathology. The aging process is characterized by alterations in the spectral content across the brain. At the network level, FC studies reveal that older adults experience a series of changes that make them more vulnerable to cognitive interferences. While special attention has been dedicated to the study of pathological conditions (in particular, mild cognitive impairment and Alzheimer’s disease), the lack of studies addressing the features of FC in healthy aging is noteworthy. This area of research calls for future attention because it is able to set the baseline from which to draw comparisons with different pathological conditions.
Jessica R. Andrews-Hanna, Matthew D. Grilli, and Muireann Irish
The brain’s default network (DN) has received considerable interest in the context of so-called “normal” and pathological aging. Findings have generally been couched in support of a pessimistic view of brain aging, marked by substantial loss of structural brain integrity accompanied by a host of impairments in brain and cognitive function. A critical look at the literature, however, reveals that the standard loss of integrity, loss of function (LILF) view in normal aging may not necessarily hold with respect to the DN and the internally guided functions it supports. Many internally guided processes subserved by the DN are preserved or enhanced in cognitively healthy older adults. Moreover, differences in motivational, contextual, and physiological factors between young and older adults likely influence the extant neuroimaging and cognitive findings. Accordingly, normal aging can be viewed as a series of possibly adaptive cognitive and DN-related alterations that bolster cognitive function and promote socioemotional well-being and stability in a stage of life noted for change. On the other hand, the available evidence reveals strong support for the LILF view of the DN in neurodegenerative disorders, whereby syndromes such as Alzheimer’s disease (AD) and semantic dementia (SD), characterized by progressive atrophy to distinct DN subsystems, display distinct aberrations in autobiographical and semantic cognition. Taken together, these findings call for more naturalistic, age-appropriate, and longitudinal paradigms when investigating neurocognitive changes in aging and to adequately assess and control for differences in non-neural factors that may obscure “true” effects of normal and pathological aging. A shift in the framework with which age-related alterations in internally guided cognition are interpreted may shed important light on the neurocognitive mechanisms differentiating healthy and pathological aging, leading to a more complete picture of the aging brain in all its complexity.
Anthony Randal McIntosh
Brain organization can be measured across multiple spatial and temporal scales where each scale affects the other in the emergent functions that are known as cognition. As a complex adaptive system, the interplay of these scales in the brain represents the information that ultimately supports what one thinks and does. The dynamics of these multiscale operations can be quantified with measures of complexity, which are sensitive to the balance between information that is coded in local cell populations and that is captured in the network interactions between populations. This local versus global balance has its foundation in the structural connectivity of the brain, which is then realized through the dynamics of cell populations and their ensuing interactions with other populations. Considering brain function and cognition in this way enables a different perspective on the changes in cognitive function in aging. Changes in brain signal complexity from childhood to adulthood were assessed in two independent studies. Both showed that maturation is accompanied by an overall increase in signal complexity, which also correlated with more stable and accurate cognitive performance. There was some suggestion that the maximal change occurs in medial posterior cortical areas, which have been considered “network hubs” of the brain. In extending to the study of healthy aging, a scale-dependent change in brain complexity was observed across three independent studies. Healthy aging brings a shift in local and global balance, where more information is coded in local dynamics and less in global interactions. This balance is associated with better cognitive performance and, interestingly, in a more active lifestyle. It also seems that the lack of this shift in local and global balance is predictive of worse cognitive performance and potentially predictive of additional decline indicative of dementia.
Simon J. Haines, Jill Talley Shelton, Julie D. Henry, Gill Terrett, Thomas Vorwerk, and Peter G. Rendell
Tasks that involve remembering to carry out future intentions (such as remembering to attend an appointment), and the cognitive processes that enable the completion of such tasks (such as planning), are referred to as prospective memory (PM). PM is important for promoting quality of life across many domains. For instance, failures in remembering to meet social commitments are linked to social isolation, whereas failures in remembering to fulfill occupational goals are linked to poorer vocational outcomes. Declines in PM functioning are of particular concern for older adults because of the strong links between PM and functional capacity. The relationship between age and PM appears to be complex, dependent on many factors. While some aspects of PM appear to hold up relatively well in late adulthood, others appear to show consistent age-related decline. Variability in age differences appears to partially reflect the fact that there are diverse types of PM tasks, which impose demands on a range of cognitive processes that are differentially affected by aging. Specifically, the level and type of environmental support associated with different PM task types appears to be a meaningful determinant of age-related effects. Given the worldwide changing age demographics, the interest in age-related effects on PM will likely intensify, and a primary focus will be how to optimize and maintain PM capacity for this population. This is already reflected in the increasing research on interventions focused on enhancing PM capacity in late adulthood, and points to important future directions in this area of study.
Michael J. Valenzuela
Cognitive reserve refers to the many ways that neural, cognitive, and psychosocial processes can adapt and change in response to brain aging, damage, or disease, with the overarching effect of preserving cognitive function. Cognitive reserve therefore helps to explain why cognitive abilities in late life vary as dramatically as they do, and why some individuals are brittle to degenerative pathology and others exceptionally resilient. Historically, the term has evolved and at times suffered from vague, circular, and even competing notions. Fortunately, a recent broad consensus process has developed working definitions that resolve many of these issues, and here the evidence is presented in the form of a suggested Framework: Contributors to cognitive reserve, which include environmental exposures that demand new learning and intellectual challenge, genetic factors that remain largely unknown, and putative G × E interactions; mechanisms of cognitive reserve that can be studied at the biological, cognitive, or psychosocial level, with a common theme of plasticity, flexibility, and compensability; and the clinical outcome of (enriched) cognitive reserve that can be summarized as a compression of cognitive morbidity, a relative protection from incident dementia but increased rate of progression and mortality after diagnosis. Cognitive reserve therefore has great potential to address the global challenge of aging societies, yet for this potential to be realized a renewed scientific, clinical, and societal focus will be required.
Susan Krauss Whitbourne
Research methods in lifespan development include single-factor designs that either follow a single cohort of individuals over time or compare age groups at a single time point. The two basic types of studies involving the manipulation of the single factors of age, cohort, and time of measurement are longitudinal and cross-sectional. Each of these has advantages and disadvantages, but both are characterized by limitations because they cannot definitively separate the joint influences of age, cohort, and type of measurement. The third group of designs involves manipulation of two or more levels of each factor to permit inferences to be drawn that separate personal from social aging. The theoretical problems involved in both the single-factor and sequential designs combine with practical issues to present lifespan developmental researchers with a number of choices in approaching the variables of interest. The theoretical problems include the inevitable linking of personal with social aging, particularly evident in single-factor designs, and the fact that selective attrition leads to the differential availability of increasingly select older samples. Practical problems include the need to assign participants to appropriate age intervals and such clerical issues as the need to track participants in follow-up investigations. Researchers must also be aware of methodological issues related to task equivalence across individuals of different ages and the need to covary for potential confounds that could lead to differences across groups of participants due to such factors as education and health status. The increasing recognition of the need to address these issues is leading to a body of literature that reflects the growing sophistication of the field along with the more widespread availability of sophisticated analytic methods. As these improvements continue to raise the level of scholarship in the field, there will be a greater understanding of both ontogenetic change as well as the influence of context on development from childhood through later life.
David J. Madden and Zachary A. Monge
Age-related decline occurs in several aspects of fluid, speed-dependent cognition, particularly those related to attention. Empirical research on visual attention has determined that attention-related effects occur across a range of information processing components, including the sensory registration of features, selection of information from working memory, controlling motor responses, and coordinating multiple perceptual and cognitive tasks. Thus, attention is a multifaceted construct that is relevant at virtually all stages of object identification. A fundamental theme of attentional functioning is the interaction between the bottom-up salience of visual features and top-down allocation of processing based on the observer’s goals. An underlying age-related slowing is prominent throughout visual processing stages, which in turn contributes to age-related decline in some aspects of attention, such as the inhibition of irrelevant information and the coordination of multiple tasks. However, some age-related preservation of attentional functioning is also evident, particularly the top-down allocation of attention. Neuroimaging research has identified networks of frontal and parietal brain regions relevant for top-down and bottom-up attentional processing. Disconnection among these networks contributes to an age-related decline in attention, but preservation and perhaps even increased patterns of functional brain activation and connectivity also contribute to preserved attentional functioning.
Benjamin Boller and Sylvie Belleville
Individuals with mild cognitive impairment (MCI) experience cognitive difficulties and many find themselves in a transitional stage between aging and dementia, making this population a suitable target for cognitive intervention. In MCI, not all cognitive functions are impaired and preserved functions can thus be recruited to compensate for the impact of cognitive impairment. Improving cognition may have a tremendous impact on quality of life and help delay the loss of autonomy that comes with dementia. Several studies have reported evidence of cognitive benefits following cognitive intervention in individuals with MCI. Studies that relied on training memory and attentional control have provided the most consistent evidence for cognitive gains. A few studies have investigated the neurophysiological processes by which these training effects occur. More research is needed to draw clear conclusions on the type of brain processes that are engaged in cognitive training and there are insufficient findings regarding transfer to activities of daily life. Results from recent studies using new technologies such as virtual reality provide encouraging evidence of transfer effects to real-life situations.
Daniel L. Schacter, Aleea L. Devitt, and Donna Rose Addis
Episodic future thinking refers to the ability to imagine or simulate experiences that might occur in an individual’s personal future. It has been known for decades that cognitive aging is associated with declines in episodic memory, and recent research has documented correlated age-related declines in episodic future thinking. Previous research has considered both cognitive and neural mechanisms that are responsible for age-related changes in episodic future thinking, as well as effects of aging on the functions served by episodic future thinking. Studies concerned with mechanism indicate that multiple cognitive mechanisms contribute to changes in episodic future thinking during aging, including episodic memory retrieval, narrative style, and executive processes. Recent studies using an episodic specificity induction—brief training in recollecting episodic details of a recent experience—have proven useful in separating the contributions of episodic retrieval from other non-episodic processes during future thinking tasks in both old and young adults. Neuroimaging studies provide preliminary evidence of a role for age-related changes in default and executive brain networks in episodic future thinking and autobiographical planning. Studies concerned with function have examined age-related effects on the link between episodic future thinking and a variety of processes, including everyday problem-solving, prospective memory, prosocial intentions, and intertemporal choice/delay discounting. The general finding in these studies is for age-related reductions, consistent with the work on mechanisms that consistently reveals reduced episodic detail in older adults when they imagine future events. However, several studies have revealed that episodic simulation nonetheless confers some benefits for tasks tapping adaptive functions in older adults, such as problem-solving, prospective memory, and prosocial intentions, even though age-related deficits on these tasks are not eliminated or reduced by episodic future thinking.