‘Neuroeconomics’ can be broadly defined as the research of how the brain interacts with the environment to make decisions that are functional given individual and contextual constraints. Deciphering such brain-environment transactions requires mechanistic understandings of the neurobiological processes that implement value-dependent decision making. To this end, a common empirical approach is to investigate neural mechanisms of reward-based decision making. Flexible updating of choices and associated expected outcomes in ways that are adaptive for a given task (or a given set of (...) tasks) at hand relies on dynamic neurochemical tuning of the brain’s functional circuitries involved in the representation of tasks, goals and reward prediction. Empirical evidence as well as computational theories indicate that various neurotransmitter systems (e.g., dopamine, norepinephrine, and serotonin) play important roles in reward-based decision making. In light of the apparent aging-related decline in various aspects of the dopaminergic system as well as the effects of neuromodulation on reward-related processes, this article focuses selectively on the literature that highlights the triadic relations between dopaminergic modulation, reward-based decision making, and aging. Directions for future research on aging and neuroeconomoics are discussed. (shrink)

Humans discount rewards as a function of the delay to their receipt. This tendency is referred to as delay discounting and has been extensively researched in the last decades. The magnitude effect and the trait effect are two phenomena which have been consistently observed for a variety of reward types. Here, we wanted to investigate if these effects also occur in the context of the novel but widespread reward types of Instagram followers and likes and if delay discounting of these (...) outcomes is related to self-control and Instagram screen time. In a within-subject online experiment, 214 Instagram users chose between smaller, immediate and larger, delayed amounts of hypothetical money, Instagram followers and likes. First, we found that the magnitude effect also applies to Instagram followers and likes. Second, delay discounting of all three reward types was correlated, providing further evidence for a trait influence of delay discounting. Third, no relationships were found between delay discounting and self-control as well as Instagram screen time, respectively. However, a user’s average like count was related to delay discounting of Instagram likes. (shrink)