Can emotion influence decision-making, and if so, how? Emotional appeals pervade advertising, marketing, and politics. While some of these appeals convey relevant information about associated products or messages, others feature apparently unrelated items (e.g., a fashion model near a sports car). From the viewpoint of a strictly rational actor, if these unrelated emotional stimuli provide no useful additional information, they should not influence decisions related to the product or message under consideration. Yet, particularly in situations involving minimal reflective processing, researchers have demonstrated that incidental emotional stimuli may influence attitudes and even behavior. However, little is known about the physiological underpinnings, the timecourse, the specificity, or the limits of this potential influence. With support from the National Science Foundation, Dr. Brian Knutson and colleagues at Stanford University will investigate how emotions that occur during anticipation of outcomes (i.e., "anticipatory affect") influence financial risk taking. Using behavioral testing and brain imagining techniques (functional magnetic resonance imaging), the investigators will test a model of anticipatory affect that predicts that: (1) positive arousal (e.g., "excitement") promotes risk seeking; (2) negative arousal (e.g., "anxiety") promotes risk aversion; and (3) anticipatory affect has a stronger influence on financial risk taking when cognitive reflection is minimal.
Findings from these studies will integrate cognitive and affective neuroscience, inform decision theory, and advance neuroimaging methods for testing causal models. By advancing scientific understanding of human decision making, the findings may eventually inform policy related to decision making in financial, health, and welfare domains. Understanding how emotions guide decisions is important for accurate models of consumer spending, understanding the phenomenon of popular fads, and has the potential to provide insight into compulsive shopping or gambling. The studies will engage a diverse group of interdisciplinary students ranging from undergraduates to postdoctoral fellows, providing them with skills that will promote their future research expertise and development.
In our National Science Foundation funded research, we proposed to study the influence of anticipatory affect on financial risk taking. The overarching goal was to test an "Anticipatory Affect Model" which predicts that anticipatory affective states influence financial risk taking. Specifically, using novel behavioral and neuroimaging techniques (functional magnetic resonance imaging or FMRI), we examined whether states of positive arousal (e.g., "excitement") and correlated nucleus accumbens (NAcc) activity would promote risk seeking, while states of negative arousal (e.g., "anxiety") and correlated anterior insula activity would promote risk aversion. We also examined whether incidental affective stimuli could induce biases in risky choice and whether reflective cognition would significantly influence these biases. Findings provided broad support for the Anticipatory Affect Model, while also inspiring novel but related questions. Briefly, we found that: (1) neural activity associated with anticipatory affect predicts financial risk taking in both investing and gambling decision scenarios (Knutson and Greer, 2008; Wu et al., 2011); (2) presentation of incidental affective stimuli can bias financial risk taking by inducing anticipatory affect (e.g., erotic pictures can increase risk taking by enhancing NAcc activity; Knutson et al., 2008); (3) reflective input and cognitive load have minimal influence on the link between anticipatory affective brain activity and financial risk taking (Samanez-Larkin et al., 2011). Extending the model beyond traditional risk scenarios, we have further discovered that other modalities of affective stimuli (e.g., smell) can similarly bias financial risk taking (Wu et al., in preparation), and that neural activity associated with anticipatory affect can even predict risk taking when traditional qualities of financial risks are held constant (e.g., mean and variance) but higher order statistical moments are manipulated (e.g., skewness and kurtosis; Wu et al., 2011; Wu et al., in preparation). Together, our research demonstrates for the first time that activity in anticipatory affective brain circuits can promote or inhibit risk taking -- regardless of the relation of input to the decision at hand, and with minimal input from more reflective brain circuits. The anticipatory affect model developed in this research program has broad implications for numerous fields including psychology, economics, and cognitive neuroscience (reflected by many citations from those fields during the award period; see Figure 1), and has also captured the interest of the general public (reflected by numerous interdisciplinary presentations and substantial press coverage during the award period). Many students who received training as a function of conducting this research have gone on to become professors at other leading institutions (e.g., Harvard, Yale, New York University). Promising directions suggested by this research for future work include: (1) examining whether laboratory measures can account for individual differences in life financial outcomes, (2) exploring whether neural predictors in a small sample can scale to predictions about aggregate market behavior, and (3) clarifying links between brain activity and self-report as well as effective versus ineffective strategies for exerting control over anticipatory affective circuits.
