398 research outputs found

    Age Differences in Striatal Delay Sensitivity during Intertemporal Choice in Healthy Adults

    Get PDF
    Intertemporal choices are a ubiquitous class of decisions that involve selecting between outcomes available at different times in the future. We investigated the neural systems supporting intertemporal decisions in healthy younger and older adults. Using functional neuroimaging, we find that aging is associated with a shift in the brain areas that respond to delayed rewards. Although we replicate findings that brain regions associated with the mesolimbic dopamine system respond preferentially to immediate rewards, we find a separate region in the ventral striatum with very modest time dependence in older adults. Activation in this striatal region was relatively insensitive to delay in older but not younger adults. Since the dopamine system is believed to support associative learning about future rewards over time, our observed transfer of function may be due to greater experience with delayed rewards as people age. Identifying differences in the neural systems underlying these decisions may contribute to a more comprehensive model of age-related change in intertemporal choice

    Age differences in risky choice: A meta-analysis

    No full text
    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

    Gain and Loss Learning Differentially Contribute to Life Financial Outcomes

    Get PDF
    Emerging findings imply that distinct neurobehavioral systems process gains and losses. This study investigated whether individual differences in gain learning and loss learning might contribute to different life financial outcomes (i.e., assets versus debt). In a community sample of healthy adults (n = 75), rapid learners had smaller debt-to-asset ratios overall. More specific analyses, however, revealed that those who learned rapidly about gains had more assets, while those who learned rapidly about losses had less debt. These distinct associations remained strong even after controlling for potential cognitive (e.g., intelligence, memory, and risk preferences) and socioeconomic (e.g., age, sex, ethnicity, income, education) confounds. Self-reported measures of assets and debt were additionally validated with credit report data in a subset of subjects. These findings support the notion that different gain and loss learning systems may exert a cumulative influence on distinct life financial outcomes

    Role of CEO Age in Determining Executive-employee Pay Gap in Chinese Listed Manufacturing Companies: A Perspective of Risk Aversion

    Full text link
    The paper investigates the effect of CEO age on executive-employee pay gap (EEPG), a newly focused dimension of executive compensation arrangements by the literature, by choosing the panel data consisting of 3495 firm-years in Chinese listed manufacturing companies during 2010-2014 as the research sample. Empirical analysis based on multiple regression analysis adopting the method of OLS by applying SPSS19.0 makes a new finding, i.e., there is a positive relationship between CEO age and EEPG, which holds robust with the change of the measures. Further investigation on the determination mechanism of CEO age on EEPG show that older CEOs intend to set relatively lower EEPG out of their risk aversion needs

    Age and Adaptation: Stronger Decision Updating about Real World Risks in Older Age

    Get PDF
    In later life, people are faced with a multitude of risky decisions that concern their health, finance, and personal security. Older adults often exercise caution in situations that involve risk. In this research, we asked whether older adults are also more responsive to warnings about potential risk. An answer to this question could reveal a factor underlying increased cautiousness in older age. In Study 1, participants decided whether they would engage in risky activities (e.g., using an ATM machine in the street) in four realistic scenarios about which participants could be expected to have relevant knowledge or experience. They then made posterior decisions after listening to audio extracts of real reports relevant to each activity. In Study 2, we explored the role that emotions play in decision updating. As in Study 1, participants made prior and posterior decisions, with the exception that for each scenario the reports were presented in their original audio format (high emotive) or in a written transcript format (low emotive). Following each posterior decision, participants indicated their emotional valence and arousal responses to the reports. In both studies, older adults engaged in fewer risky activities than younger adults, indicative of increased cautiousness in older age, and exhibited stronger decision updating in response to the reports. Older adults also showed stronger emotional responses to the reports, even though emotional responses did not differ for audio and written transcript formats. Finally, age differences in emotional responses to the reports accounted for age differences in decision updating

    Age Differences in Risk: Perceptions, Intentions and Domains

    Full text link
    Although it is commonly assumed that older people are more cautious and risk averse than their younger counterparts, the research on age differences in risk taking is mixed. While some research has found that older adults are less risk seeking, other research has found the opposite or no differences. One explanation is that age differences vary across risk domains. In two studies, we surveyed three adult age groups ranging in age from 18 to 83 on their risk perceptions and intentions of risky behaviors across several domains. Our studies showed that compared with young adults, older adults tend to see more risk in behaviors in health and ethical domains but less risk in behaviors from the social domain. A similar pattern occurred for participants' intentions of engaging in the risky behaviors. Older adults rated risky behaviors from health and ethical domains as less enjoyable and less likely to produce gains than young adults, whereas they rated risky behaviors from the social domain as more enjoyable, less unpleasant, and less likely to produce losses than young adults. These results suggest that age differences in risk preferences may vary across domains and may result from differing motivations. Copyright © 2015 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/113748/1/bdm1848.pd

    A neurocomputational account of how inflammation enhances sensitivity to punishments versus rewards

    Get PDF
    BACKGROUND: Inflammation rapidly impairs mood and cognition and, when severe, can appear indistinguishable from major depression. These sickness responses are characterized by an acute reorientation of motivational state; pleasurable activities are avoided, and sensitivity to negative stimuli is enhanced. However, it remains unclear how these rapid shifts in behavior are mediated within the brain. METHODS: Here, we combined computational modeling of choice behavior, experimentally induced inflammation, and functional brain imaging (functional magnetic resonance imaging) to describe these mechanisms. Using a double-blind, randomized crossover study design, 24 healthy volunteers completed a probabilistic instrumental learning task on two separate occasions, one 3 hours after typhoid vaccination and one 3 hours after saline (placebo) injection. Participants learned to select high probability reward (win £1) and avoid high probability punishment (lose £1) stimuli. An action-value learning algorithm was fit to the observed behavior, then used within functional magnetic resonance imaging analyses to identify neural coding of prediction error signals driving motivational learning. RESULTS: Inflammation acutely biased behavior, enhancing punishment compared with reward sensitivity, through distinct actions on neural representations of reward and punishment prediction errors within the ventral striatum and anterior insula. Consequently, choice options leading to potential rewards were less behaviorally attractive, and those leading to punishments were more aversive. CONCLUSIONS: Our findings demonstrate the neural mediation of a rapid, state-dependent reorientation of reward versus punishment sensitivity during inflammation. This mechanism may aid the adaptive reallocation of metabolic resources during acute sickness but might also account for
    corecore