Separate neural mechanisms underlie choices and strategic preferences in risky decision making

Abstract

Adaptive decision making in real-world contexts often relies on strategic simplifications of decision problems. Yet, the neural mechanisms that shape these strategies and their implementation remain largely unknown. Using an economic decision-making task, we dissociate brain regions that predict specific choices from those predicting an individual's preferred strategy. Choices that maximized gains or minimized losses were predicted by functional magnetic resonance imaging activation in ventromedial prefrontal cortex or anterior insula, respectively. However, choices that followed a simplifying strategy (i.e., attending to overall probability of winning) were associated with activation in parietal and lateral prefrontal cortices. Dorsomedial prefrontal cortex, through differential functional connectivity with parietal and insular cortex, predicted individual variability in strategic preferences. Finally, we demonstrate that robust decision strategies follow from neural sensitivity to rewards. We conclude that decision making reflects more than compensatory interaction of choice-related regions; in addition, specific brain systems potentiate choices depending on strategies, traits, and context.

Figure 1. Experimental task and behavioral results

(A) Subjects were first shown, for 4–6s, a multi-attribute mixed gamble consisting of five potential outcomes, each associated with a probability of occurrence. Then, two alternatives for improving the gambles were highlighted in red, whereupon subjects had 6s to decide which improvement they preferred. Finally, after two arrows identified the buttons corresponding to the choices, subjects indicated their choice by pressing the corresponding button as soon as possible. Here, the addition of $20 to the central, reference outcome would maximize the overall probability of winning (P_max choice), whereas the addition of $20 to the extreme loss would reflect a loss-minimizing (L_min) choice. The next trial appeared after a variable interval of 4, 6 or 8s. In other trials, subjects could have a chance to add money to the extreme gain outcome, reflecting a gain-maximizing (G_max) choice.

Figure 2. Distinct sets of brain regions predict choices

(A) Increased activation in the right anterior insula (peak MNI space coordinates: x = 38, y = 28, z = 0) and in the ventromedial prefrontal cortex (x = 16, y = 21, z = −23) predicted L_min and G_max choices respectively, while increased activation in the lateral prefrontal cortex (x = 44, y = 44, z = 27) and posterior parietal cortex (x = 20, y = −76, z = 57) predicted P_max choices. Activation maps show active clusters that surpassed a threshold of z > 2.3 with cluster-based Gaussian random field correction. (B–D) Percent signal change in these three regions to each type of choice. On this and subsequent figures, error bars represent ±1 standard error of the mean for each column.

Figure 3. Dorsomedial prefrontal cortex predicts strategy use during decision making

(A,B) Activation in dorsomedial prefrontal cortex (dmPFC, x = 10, y = 22, z = 45; indicated with arrow) and the right inferior frontal gyrus (rIFG) exhibited a p. 34 significant decision-by trait-interaction, such that the difference in activation between compensatory and simplifying choices was significantly correlated with preference for simplifying strategy (mean-subtracted) across individuals. (C,D) Functional connectivity of dmPFC varied as a function of strategy: there was increased connectivity with dlPFC (and PPC) for simplifying choices and increased connectivity with aINS (and amygdala) for compensatory choices.

Figure 4. Ventral striatal sensitivity to rewards predicts strategic variability

At the end of the experiment, some gambles were resolved to monetary gains or losses. (A,B) Activation in the ventral striatum (x = 14, y = 16, z = −10) increased when subjects were waiting for gambles to be resolved (anticipation) and, following resolution, increased to gains but decreased to losses. (C) Notably, the difference between gain-related and loss-related activation in the ventral striatum correlated with variability in strategic preferences across subjects, with subjects who were most likely to prefer the probability-maximizing exhibiting the greatest neural sensitivity to rewards.