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The Rangel Lab studies the computational and neurobiological basis of decision making using a combination of tools from neuroscience, economics, psychology, and computer science. Using tools including fMRI, EEG, TMS, single-unit recordings in human patients, eye-tracking, and computational modeling, the lab is addressing several important questions:

Computation of values in simple choice

We have used fMRI to investigate the neural correlates of value computation in simple choices, showing that activity in the medial orbitofrontal cortex (mOFC) and the right dorsolateral prefrontal cortex (dlPFC) correlates with the value assigned to appetitive food items at the time of choice (Plassmann et al., 2007). Subsequent studies have extended this basic finding in a number of ways, showing that the same two areas also encode the value of aversive food stimuli (Plassmann et al., under review), and that mOFC activity correlates with the value of money, food, and trinkets in very different choice situations (Chib et al., 2009).

Ongoing projects in the lab are harnessing the uniqe advantages of different experimental techniques, such as TMS, single-unit recording, and EEG (Harris et al., 2011). These projects will help us to better understand the dynamic role that the mOFC, dlPFC, and other regions play in the ability to make simple choices.

Comparison of values in simple choice

A key step in making a choice involves comparing values to select the best options. We have carried out a number of modeling, behavioral, and eye-tracking studies to characterize the properties of the comparison process. One line of research addresses a basic puzzle: Why is it that subjects look back and forth between options in order to make a choice, long after the identity of the options is known? Our research suggests that eye-fixations actually guide the comparion process. Using eye-tracking, we have shown that a simple extension of drift-diffusion models popular in psychology, which allows for the integration process to be biased towards the item being fixated, is able to explain the psychometric and eye-tracking data with remarkable quantitative and qualitative procession (Krajbich et al., 2010, 2011).

What is the neurobiological basis of this fixation effect? Our research suggests that areas of the temporal lobe bias valuation activity in mOFC in favor of the option being attended (Lim et al., 2011). A second critical open question, which we are currently pursuing with both fMRI and EEG, concerns where and how values are compared in order to make a choice.

Control processes in decision making

We also study more complex decisions, in which subjects need to balance immediate rewards (e.g., taste) with long-term consequences (e.g. health).

To study the question of self-control, we scanned dieters as they made choices between stimuli that varied in their taste and health properties, which were measured independently (Hare et al., 2009). This study found that activity in the mOFC encoded stimulus values regardless of the extent to which health or taste considerations drove the choices. However, health information had a greater influence on the OFC value signals (and choices) when a region of left dlPFC was activated. Functional connectivity analyses suggested that dlPFC might modulate the weight placed on different attributes during value computation in OFC.

We are currently following up on this study in a number of ways. First, we are combining rTMS over left dlPFC with fMRI to test if this area plays a causal role in self-control. Second, we are investigating what happens when subjects explicitly try to control their decisions. Preliminary results show that different networks are activated and suggest that deliberate regulation may have different consequences for behavior. Third, we are investigating whether long-term self-control training changes the ability of the dlPFC to carry out the necessary modulatory operations. Finally, we are beginning to investigate self-control networks in addiction.

Social decision-making

Although decision-making may rely on a core set of basic mechanisms, there are a priori reasons to believe that social decisions also might involve newer mechanisms that are specialized for social perception. We are actively investigating the ways in which social decision-making resembles decisions regarding more primary rewards, and also how it differs from such simple decisions. We have shown that decision-making concerning donations to charitable organizations recruits the same mOFC valuation mechanisms, but, crucially, that this region shows increased connectivity with regions such as the anterior insula and posterior superior temporal cortex, areas thought to be involved in empathy and social cognition (Hare et al., 2010).

We have also used fMRI to demonstrate signals within the mOFC and ventral striatum related to inequality aversion, a phenomenon long hypothesized by behavioral economists, but difficult to unequivocally prove using classical methods (Tricomi et al., 2010).

Current projects include examining how neural computations differ when we make decisions for ourselves compared to when we make decisions for others, as well as investigations into how we value and make decisions concerning moral behavior.

Applications of neuroeconomics

Neuroeconomics research uses tools and insights from both economics and neuroscience to design policies and institutions that induce more desirable outcomes by inducing better decision-making. In one set of studies, we have combined fMRI, decoding tools from machine learning, and the economic theory of mechanism design to show that it is possible to design institutions that solve the free-rider problem (Krajbich et al., 2009). We refer to this class of institutions as neurometric mechanisms. We are applying similar ideas to the problems of bilateral bargaining and auction design in follow-up work.