Recent evidence suggests that emotional well-being improves from early adulthood to old age. This study used experience-sampling to examine the developmental course of emotional experience in a representative sample of adults spanning early to very late adulthood. Participants (N = 184, Wave 1; N = 191, Wave 2; N = 178, Wave 3) reported their emotional states at five randomly selected times each day for a one week period. Using a measurement burst design, the one-week sampling procedure was repeated five and then ten years later. Cross-sectional and growth curve analyses indicate that aging is associated with more positive overall emotional well-being, with greater emotional stability and with more complexity (as evidenced by greater co-occurrence of positive and negative emotions). These findings remained robust after accounting for other variables that may be related to emotional experience (personality, verbal fluency, physical health, and demographic variables). Finally, emotional experience predicted mortality; controlling for age, sex, and ethnicity, individuals who experienced relatively more positive than negative emotions in everyday life were more likely to have survived over a 13 year period. Findings are discussed in the theoretical context of socioemotional selectivity theory.

Neuroscientists have long observed that brain activity is naturally variable from moment-to-moment, but neuroimaging research has largely ignored the potential importance of this phenomenon. An emerging research focus on within-person brain signal variability is providing novel insights, and offering highly predictive, complementary, and even orthogonal views of brain function in relation to human lifespan development, cognitive performance, and various clinical conditions. As a result, brain signal variability is evolving as a bona fide signal of interest, and should no longer be dismissed as meaningless noise when mapping the human brain.

Does risk taking change as a function of age? We conducted a systematic literature search and found 29 comparisons between younger and older adults on behavioral tasks thought to measure risk taking (N =4,093). The reports relied on various tasks differing in several respects, such as the amount of learning required or the choice framing (gains vs. losses). The results suggest that age-related differences vary considerably as a function of task characteristics, in particular the learning requirements of the task. In decisions from experience, age-related differences in risk taking were a function of decreased learning performance: older adults were more risk seeking compared to younger adults when learning led to risk-avoidant behavior, but were more risk averse when learning led to risk-seeking behavior. In decisions from description, younger adults and older adults showed similar risk-taking behavior for the majority of the tasks, and there were no clear age-related differences as a function of gain/loss framing. We discuss limitations and strengths of past research and provide suggestions for future work on age-related differences in risk taking.

Although global declines in structure have been documented in the aging human brain, little is known about the functional integrity of the striatum and prefrontal cortex in older adults during incentive processing. We used event-related functional magnetic resonance imaging to determine whether younger and older adults differed in both self-reported and neural responsiveness to anticipated monetary gains and losses. The present study provides evidence for intact striatal and insular activation during gain anticipation with age, but shows a relative reduction in activation during loss anticipation. These findings suggest that there is an asymmetry in the processing of gains and losses in older adults that may have implications for decision-making.Over the past several decades, scientists have made rapid progress toward determining the effects of aging on cognition. Both behavioral and neuroimaging studies show that there is a strong negative relationship between age and cognitive performance across many types of tasks 1,2 . However, a growing body of research also suggests that many affective abilities do not decline with age, and that in some cases they may improve. Accumulating behavioral evidence suggests that older adults perform relatively better on tasks that involve the processing of emotional stimuli 3 . Socioemotional selectivity theory postulates that age-related attempts to optimize emotional well-being 4 generate increased positive emotional experiences and/or decreased negative emotional experiences over the life span 5 . To date, however, very few neuroimaging studies have focused on changes in emotion with age 6,7 , with only one prior study examining changes in incentive processing over the life span 8 .Studies of brain structure and chemistry provide some evidence for age-related decline. These studies have specifically shown significant structural atrophy of the caudate, insula and prefrontal cortex, as well as global declines in dopamine receptors in the striatum and the

As the global population ages, older decision makers will be required to take greater responsibility for their own physical, psychological and financial well-being. With this in mind, researchers have begun to examine the effects of ageing on decision making and associated neural circuits. A new “affect, integration, motivation” (or AIM) framework may help clarify how affective and motivational circuits support decision making. Recent research has shed light on whether and how ageing influences these circuits, providing an interdisciplinary account of how ageing can alter decision making.

Recent years have seen a rejuvenation of interest in studies of motivation–cognition interactions arising from many different areas of psychology and neuroscience. The present issue of Cognitive, Affective, & Behavioral Neuroscience provides a sampling of some of the latest research from a number of these different areas. In this introductory article, we provide an overview of the current state of the field, in terms of key research developments and candidate neural mechanisms receiving focused investigation as potential sources of motivation–cognition interaction. However, our primary goal is conceptual: to highlight the distinct perspectives taken by different research areas, in terms of how motivation is defined, the relevant dimensions and dissociations that are emphasized, and the theoretical questions being targeted. Together, these distinctions present both challenges and opportunities for efforts aiming toward a more unified and cross-disciplinary approach. We identify a set of pressing research questions calling for this sort of cross-disciplinary approach, with the explicit goal of encouraging integrative and collaborative investigations directed toward them.

Can risk-taking propensity be thought of as a trait that captures individual differences across domains, measures, and time? Studying stability in risk-taking propensities across the lifespan can help to answer such questions by uncovering parallel, or divergent, trajectories across domains and measures. We contribute to this effort by using data from respondents aged 18 to 85 in the German Socio-Economic Panel Study (SOEP) and by examining (1) differential stability, (2) mean-level differences, and (3) individual-level changes in self-reported general (N = 44,076) and domain-specific (N =11,903) risk-taking propensities across adulthood. In addition, we investigate (4) the correspondence between cross-sectional trajectories of self-report and behavioral measures of social (trust game; N = 646) and nonsocial (monetary gamble; N = 433) risk taking. The results suggest that risk-taking propensity can be understood as a trait with moderate stability. Results show reliable mean-level differences across the lifespan, with risk-taking propensities typically decreasing with age, although significant variation emerges across domains and individuals. Interestingly, the mean-level trajectory for behavioral measures of social and nonsocial risk taking was similar to those obtained from self-reported risk, despite small correlations between task behavior and self-reports. Individual-level analyses suggest a link between changes in risk-taking propensities both across domains and in relation to changes in some of the Big Five personality traits. Overall, these results raise important questions concerning the role of common processes or events that shape the lifespan development of risk-taking across domains as well as other major personality facets.

As human life expectancy continues to rise, financial decisions of aging investors may have an increasing impact on the global economy. In this study, we examined age differences in financial decisions across the adult life span by combining functional neuroimaging with a dynamic financial investment task. During the task, older adults made more suboptimal choices than younger adults when choosing risky assets. This age-related effect was mediated by a neural measure of temporal variability in nucleus accumbens activity. These findings reveal a novel neural mechanism by which aging may disrupt rational financial choice.