Professional Preparation

Research Areas

Influence of Decision Features

The vast majority of decision making research has focused on examining monetary decisions. However, real-world decision making often requires that individuals weigh the costs and benefits across a variety of domains. Thus, my colleagues designed a set of discounting tasks to test how different types of costs and rewards influence choice behavior. We have found significant age differences in choice behavior depending on the type of cost and the reward domain (Seaman, Gorlick, et al., 2016). These results have been replicated in a recent study during the Covid-19 pandemic (Seaman, Juarez, et al., 2021). In a second study, which focused on decisions about monetary rewards, we discovered that while the tolerance of different costs is behaviorally dissociable, subjective value signals share a common representation in the brain across adulthood (Seaman, Brooks, et al., 2018). Collectively, this line of work demonstrates the importance of considering motivation when examining choice behavior across adulthood – and focusing on abstract monetary rewards may limit our ability to quantify age differences in domain-general decision making. Understanding what matters to people is critical to understanding the decisions they make.

Temporal Discounting and Aging

A number of theories in adult development make predictions about the link between age and temporal discounting, or the devaluation of future rewards. However, the empirical literature on this subject was mixed. Thus, with colleagues from Duke and the University of Basel, I conducted a systematic review and meta-analysis of temporal discounting across adulthood. Across 37 studies (N = 104, 737), we found no sizeable relationship between adult age and temporal discounting (Seaman et al., 2022). In conducting the review, we observed that studies use a variety of delay durations, ranging from days to years. Working with the founding members of my new lab, we decided to conduct a follow-up study systematically manipulating delay duration. Here, we found that that, at short to moderate time delays, older adults discounted less than younger adults. However, at very long delays (5 and 10 years), older adults discounted at similar rates to younger adults (Leverett et al., 2021). This suggests that observed age differences in temporal discounting may be methodological and that delay length may moderate the relationship between age and discounting.

Risk, Expected Value, and Aging

Emerging research suggests that some age-related deficits in decision making may be linked to the way individuals represent expected value. My work in this area has sought to examine how the probability and variance of outcomes can influence this representation in older adults. For instance, we found individual differences in perceptions of risk are related to residential choice in older adults (Seaman, Stillman, et al 2015). We also observed that older adults have a tendency to accept more positively-skewed financial risks (with a small chance of a large win) than other types of equivalent gambles (Seaman, Leong, et al, 2017) and this age-related positive-skew bias is related to age differences in the recruitment of the lateral prefrontal cortex. Further, a follow-up study showed that the age-related increase in acceptance of positively-skewed bets is not due increased in loss aversion in older adults (Seaman, Green, Shu & Samanez-Larkin, 2018). Taken together, these studies suggest that the processing of probabilistic information can profoundly affect the way individuals, and particularly older adults, make risky decisions.

Dopamine and Aging

Using PET imaging, my colleagues and I have recently explored adult age differences in dopamine D2/3 receptor binding potential across several cortical and subcortical brain regions. We found that using partial-volume correction on PET data increased estimates of binding potential and reduced the estimated age effects on binding potential (Smith et al., 2019). Using these partial-volume corrected data, we have shown that the rate and pattern of decline in dopamine receptor availability was regionally heterogeneous and did not fit with existing theories of adult brain development (Seaman, et al., 2019), that individual differences in dopamine binding potential are not associated with reward discounting in health populations (Castrellon, et al, 2019), and that correlative triad among aging, dopamine binding potential, and cognition is not a reliable as originally posited (Juarez, et al., 2019). Collectively, these results suggests that existing theories of adult brain development may need to be modified to better account for dopaminergic system aging.

Sequence Learning

Our worlds are filled with sequential relationships. Perceiving and understanding these contingencies allows us to predict and respond appropriately to future events. While a number of studies have demonstrated that the learning of sequential relationships changes with age, it is less clear how people use knowledge of sequential relationships to make predictions at different ages. Creating a new experimental paradigm, the Triplets Prediction Task, my colleagues and I discovered adult age-related deficits in the learning of sequential predictive relationships (Seaman, Howard & Howard, 2014). We later clarified that this was primarily due to older adults relying on simple, but disadvantageous, strategies (Seaman, Howard & Howard, 2015). This line of research confirmed an age-related prediction learning deficit and contributed to a growing literature suggesting older adults prefer simple cognitive strategies.

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