Neural basis of consumer decision making and neuroforecasting.

Abstract

Neuroscience, in recent years, has contributed significantly to a better understanding of how individuals make decisions and how these decisions are influenced by context, states, and individual traits. The past decade has seen the emergence of consumer neuroscience as an academic field of inquiry that applies tools and theories from neuroscience to better understand consumer behavior. These studies have primarily used functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), although the field extends to a wider range of tools, such as facial coding, eye-tracking, heart rate monitoring, and galvanic skin response.Investigating meaningful questions with appropriately designed studies that leverage neuroscientific knowledge has allowed researchers to generate useful insights about consumers from both theoretical and practical perspectives. Plassmann et al. (2015) identified five concrete ways in which consumer neuroscience has been applied to improve understanding of consumer behavior. First, it can be used to validate, refine, or extend existing theories by elucidating the underlying mechanisms. It has also suggested empirically testable hypotheses about preferences, judgments, or choices (e.g., Ho & Spence, 2009;Wadhwa et al., 2008) that accord with an understanding of biology. Second, neuroscience techniques have provided information about implicit processes that are difficult to access using other methods (e.g., Plassmann et al., 2008;Yoon et al., 2006). Third, neural measures have been used to test for dissociations between psychological processes. For example, fMRI has been used in studies to examine the extent to which two different kinds of decisions use similar or different neural mechanisms and thus whether they are likely to use similar or different cognitive processes (e.g., decisions under risk and ambiguity; Hsu et al., 2005;I. Levy et al., 2010). Fourth, fMRI studies have tested whether different individuals perform the same decision task in different ways (e.g., using heuristic vs. deliberative decision strategies; Venkatraman et al., 2009). Fifth and finally, studies have incorporated neural measures into models of choice and decision making to improve predictions. Although all five ways are indeed important ways in which consumer neuroscience can contribute to knowledge about consumers, this chapter focuses primarily on reviewing the research related to neural predictions. We choose to do so, in part, because there are already a number of recently published review articles that have described the advantages of neuroscientific methods and their contributions to consumer research more generally (Karmarkar & Plassmann, 2019;Karmarkar & Yoon, 2016;Plassmann et al., 2015;Smidts et al., 2014). However, the main impetus for the present topic is that it is currently garnering much research interest among academic scholars and practitioners alike for holding the promise of expanding our insights about

Brain activity of professional investors signals future stock performance

“…In fact, the information that we presented would be mostly unintelligible to untrained eyes, underlining the importance of our sample of professional investors with specific and relevant expertise. While previous studies found a relationship between market-level outcomes and brain responses of naïve participants to simplified stimuli presented out-of-context (7), our study shows that the market can be predicted by brain responses of experts processing comprehensive, realistic information.…”

“…Whether or not this implies that AIns responses can only be related to short-term market outcomes, or also long-term, remains an open question. The alleged different mechanisms of the brain components investigated here (i.e., NAcc, MPFC, AIns), and their potential for neuroforecasting, deserves more attention (7,8) and further stresses the importance of studying the neurobiology of financial decision-making (20).…”

“…Our results extend previous findings in neuroforecasting stock markets (23) by sampling brain activity from a select group of professionals, with high-level expertise in making investment decisions. While several studies have shown that NAcc activity from a small sample can be used to predict market-level outcomes (7), these studies typically recruited university students as participants. Moreover, most neuroforecasting studies to date have dealt with relatively simple stimuli that had to be evaluated in only a few seconds (e.g., crowdfunding options described in only a few sentences; ( 12)).…”

“…Recent findings have demonstrated that neural activity associated with individual choice can also be informative of aggregate choice (7). Thus, neural data could potentially be used to forecast the market (i.e., population-wide behavior).…”

“…Neuroforecasting studies sample anticipatory brain activity that occurs before individuals make a conscious choice. Though exceptions exist (15,16), the majority of neuroforecasting studies focusses on brain activity sampled from three distinct brain areas: predominantly the Nucleus Accumbens (NAcc), or entire Ventral Striatum (VS), the (ventral) Medial Prefrontal Cortex (MPFC), and the Anterior Insula (AIns) (7). It has been proposed that activity in these brain regions offers an opportunity to forecast population behavior because it represents a universal, generalizable response toward the stimulus under investigation (8).…”