The Vivid Present: Visualization Abilities Are Associated with Steep Discounting of Future Rewards

Abstract

Humans and other animals discount the value of future rewards, a phenomenon known as delay discounting. Individuals vary widely in the extent to which they discount future rewards, and these tendencies have been associated with important life outcomes. Recent studies have demonstrated that imagining the future reduces subsequent discounting behavior, but no research to date has examined whether a similar principle applies at the trait level, and whether training visualization changes discounting. The current study examined if individual differences in visualization abilities are linked to individual differences in discounting and whether practicing visualization can change discounting behaviors in a lasting way. Participants (n = 48) completed the Vividness of Visual Imagery Questionnaire (VVIQ) and delay discounting task and then underwent a 4-week intervention consisting of visualization training (intervention) or relaxation training (control). Contrary to our hypotheses, participants who reported greater visualization abilities (lower scores) on the VVIQ were higher discounters. To further examine this relationship, an additional 106 participants completed the VVIQ and delay discounting task. In the total sample (n = 154), there was a significant negative correlation between VVIQ scores and discount rates, showing that individuals who are better visualizers are also higher discounters. Consistent with this relationship but again to our surprise, visualization training tended, albeit weakly, to increase discount rates, and those whose VVIQ decreased the most were those whose discount rates increased the most. These results suggest a novel association between visualization abilities and delay discounting.

Developmental perspectives on risky and impulsive choice

“…Moreover, adults' self-reported simulation vividness, as well as the strength of functional coupling between the PFC and the hippocampus-a region implicated in episodic memory and prospective simulation [150,151]-predict the degree to which episodic simulation alters discount rates [148,149]. Collectively, this work suggests that individuals who spontaneously engage in such future-directed mentalizing behaviour might exhibit more patient choices (but see [152]) and that age-related changes in episodic simulation might contribute to developmental differences in intertemporal choice.…”

Cuing both positive and negative episodic foresight reduces delay discounting but does not affect risk-taking

“…Several lines of empirical evidence hint at the possibility that episodic foresight might affect delay discounting selectively depending on the content or valence of the thoughts. For instance, visualisation abilities (considered key to imagining future events in sufficient detail to generate the effect on delay discounting) have been found to correlate with steeper delay discounting (Parthasarathi, McConnell, Luery, & Kable, 2017), even though one study on adolescents found the vividness of episodic foresight imagery to correlate with reduced delay discounting elsewhere (Bromberg, Wiehler, & Peters, 2015). In addition, a recent study found no association between delay discounting and model-based control (a formalisation thought to reflect the mechanism underpinning scene-construction and future event simulation) (Solway, Lohrenz, & Montague, 2017).…”

Delay discounting decisions are linked to temporal distance representations of world events across cultures

“…On the delay discounting task, participant’s responses were modeled using the hyperbolic function, SV = A/(1 + kD), where a higher discount rate k indicated that a participant more steeply discounted future rewards (Fig. 2 b) 33 , 34 . We assessed the goodness-of-fit of the models using McFadden’s pseudo-R 2 and excluded participants whose R 2 fell below 0.3, a threshold set to exclude participants for responding randomly 7 , 10 , 35 .…”

“…Discount rates were estimated using a logistic regression model in MATLAB, where participants' choices were fit using maximum likelihood estimation 34 . The subjective values of options were estimated using a hyperbolic discounting model: SV = A/(1 + kD).…”