Schedule - Parallel Session 1 - NeuroscienceIMC Auditorium - 11:00 - 12:30
Expected Subjective Value Theory: A Representation of Decision in Time Under Risk
Over the past few years there has been growing interest in the notion that a representation involving divisive normalization (a canonical neural computation in sensory systems) normatively encodes option value in the brain. The divisive normalization algorithm has been shown to rationalize behaviors previously labeled as anomalous in economic theory, including violations of the independence of irrelevant alternatives (Louie, 2013). There is growing understanding that such anomalies in decision-making are in fact a result of an efficient value coding by a system that has limited neural resources (Glimcher, 2010; Woodford, 2012, 2014; Hunt et al, 2014). The implications of the efficient value coding through the divisive normalization algorithm have, however, not yet been carefully considered with respect to the decision making under risk. This paper presents a near-normative model of choice under risk that incorporates neurobiological constraints and costs into a traditional economic framework via divisive normalization. It yields an expected utility-like model that captures many of the behavioral phenomena around which prospect theory was built, but without recourse to a completely descriptive approach. The model defines the reference point as an adaptive mechanism that optimizes precision at expectation. It captures the same ‘representative agent’ choice behavior as prospect theory but unlike prospect theory also captures single agent behavior. It accounts for such behavioral phenomena as lack of a reflection effects on the individual level and the non-independence of loss aversion and risk seeking in individuals. It makes novel predictions about how risk attitudes and loss aversion depend on the history of experienced rewards – their timing, value and variation in a more normative fashion. It also captures heterogeneity in individual preferences related to individual differences in neural constraints (such as those present in aging or illness), thus allowing us to unify numerous previously observed associations between a host of brain changing variables and risk attitudes and loss aversion.
Alteration of Political Belief by Non-Invasive Brain Stimulation
Caroline Chawke; C. Chawke; R. Kanai
People generally have imperfect introspective access to the mechanisms underlying their political beliefs, yet can confidently communicate the reasoning that goes into their decision making process. An innate desire for certainty and security in ones beliefs may play an important and somewhat automatic role in motivating the maintenance or rejection of partisan support. The aim of the current study was to clarify the role of the DLPFC in the alteration of political beliefs. Recent neuroimaging studies have focused on the association between the DLPFC (a region involved in the regulation of cognitive conflict and error feedback processing) and reduced affiliation with opposing political candidates. As such, this study used a method of non-invasive brain simulation (tRNS) to enhance activity of the bilateral DLPFC during the incorporation of political campaign information. These findings indicate a crucial role for this region in political belief formation. However, enhanced activation of DLPFC does not necessarily result in the specific rejection of political beliefs. In contrast to the hypothesis the results appear to indicate a significant increase in conservative values regardless of participant’s initial political orientation and the political campaign advertisement they were exposed to.
(Emotional) Reference Point Formation
Milica Mormann; Luke Nowlan; Joseph Johnson
Investors code financial outcomes as gains or losses relative to a reference point (Kahneman and Tversky 1979; Shefrin & Statman 1985). Existing research shows that the reference point is set and updated based on the information that is integral, i.e., directly related, to the decision-making task, such as previous stock prices or expectations of future prices (Baucells et al. 2011; Shefrin and Statman 1985; Weber and Camerer 1998; Barberis and Xiong 2009; Odean 1998; Grinblatt and Keloharju 2001; Arkes et al. 2008). The purpose of our research is to examine whether incidental information that arises from situational sources unrelated to the decision-making task, and specifically incidental emotions (Lerner et al. 2015; Rick and Loewenstein 2008), affect reference point formation. More specifically, we here propose and test an emotional-attentional mechanism as a driver of reference point formation in the context of investor decision making.
To test this mechanism, we conduct an eye-tracking experiment consisting of two seemingly unrelated tasks. First, we induce incidental emotions by exposing participants to an emotional video (either fearful, joyful, or neutral; Lee and Andrade 2011) and ask them a set of questions related to the video. Next, we ask them to perform a “stock-market task”. More specifically, building on the reference point elicitation method from Baucells et al. (2011) and Arkes et al. (2008), we show participants a set of stock charts and ask them to state their neutral selling price for each stock. Our stock charts contain clearly identifiable regions of the initial (i.e., purchase), highest, lowest, and current stock prices. We use eye-tracking to measure how much attention participants allocate to each of the four price regions on stock charts as they form their reference points, indicate their likelihood to sell stocks, and predict future stock prices. Finally, using a multilevel modeling approach, we model the relationship between emotions, attention, and reference point formation.
We report several important findings. First, we find that situational factors, and specifically incidental emotions, shift the reference point: while joy shifts the reference point up, fear shifts the reference point down. Second, using eye-tracking, we find that incidental emotions influence how investors look at financial information. When looking at the stock charts, those exposed to joyful emotions look more at historic highs and less at the current price, while those exposed to fearful emotions look more at the current price and less at the purchase price. Third, we use the behavioral and eye-tracking data to model the underlying process and show that this differing attention to various stock prices mediates the effect of emotions on the reference point formation.
Where Does Satiation Come From?
Manel Baucells; Daniel Smith
In the mid 1800’s psychologists Weber and Fechner pioneered the quantitative study of the human response to a physical stimulus, and postulated a law of diminishing marginal returns. This translated into the notion of a concave utility function, central to economics. What exactly governs the attenuation and recovery of marginal returns? We address these questions by introducing a simple -yet novel- model of the neurobiological mechanism of chemical signaling. The model is a system composed of particle inputs, receptors, and response outputs. The system is a natural extension of the occupancy problem in probability theory. It provides a justification -at the neurobiological level- for the notion of diminishing marginal returns, in the precise sense formulated by the satiation utility function. By maximizing the satiation utility function we uncover some key properties of neurobiological signal transmission. Our central results shows that the optimal temporal distribution of inputs follows a high-low-high pattern.