Antonio Rangel - US grants

This CAREER project proposes to analyze the role that intergenerational and behavioral issues play on the design and analysis of public policy. The project has three components. The first component studies what types of institutions, existing or not, are able to generate optimal investment in future generations, and to protect them from expropriation. It includes the development of theoretical models to understand how to design fiscal constitutions that generate optimal investment in intergenerational public goods, such as the environment, and protect future generations from expropriation through fiscal policy. The key question is: How can we design institutions that give a "voice" to the interests of people who have not been born yet. We plan to test empirically this theory by using the last 200 years of American history to study the extent to which American institutions have generated "good" intergenerational outcomes. This includes the development of a new database on the finances of the Federal Government from 1820 to the present. The second component develops a new model of decision-making and welfare that uses as primitives brain structures and their operations, instead of preferences and preference maximization. The model incorporates important insights from psychology and neuro-science, and has the potential to explain why agents engage in self-defeating behaviors such as under-saving and addiction. Also, and most importantly for Public Economics, the model generates well-defined welfare evaluations that can be used to evaluate public policy. This theory will be used to improve our understanding of advertisement, savings policy, drug policy, health policy, and risky behaviors. Finally, the third component of the project is the career educational plan on Public and Behavioral Economics that includes, among others, the development of a behavioral economics research group at Stanford University, and the development of a new graduate textbook in Public Economics.

Intergenerational and behavioral issues lie at the center of some of the most important current debates in public policy. Examples of intergenerational policy problems include Global Warming, R&D, and the AIDS epidemic. These problems are difficult to handle because the generations that would benefit most from these policies are not the ones paying for them. Examples of behavioral policy problems include the design of social insurance programs, crime, and addiction. Behaviors such as systematic financial mismanagement and the consumption of addictive substances challenge the predictions and the policy prescriptions of standard economic analysis, which presupposes that agents are quite "rational." The basic motivation for this research is that an improved understanding of these issues will allow us to design better public policies and ultimately better institutions.

In recent years, economic scholars in a wide variety of specializations have become increasingly interested in questions of Political Economy. A central objective of this movement has been to supplement our understanding of the relationships between the political environment (including institutions) and the economic policies that are adopted. Though much progress has been made, virtually nothing is known about the strategic issues arising from the possibility that a legislature might choose to reconsider some provision of a law after its passage but prior to its implementation. Legislative reconsideration is a common occurrence in practice. Moreover, it gives rise to complex strategic issues. The adoption of a policy provision for some future period changes the political landscape. Further discussion of the issues prior to the law's implementation takes place against a different backdrop. Though the provision can be changed, repealed, or replaced before it becomes effective, its adoption alters the terms of the ensuing debate. The purpose of this project is to explore the effects of legislative reconsideration on economic policy selection. The analysis identifies and explores a tendency for reconsideration to create high concentration of political power (irrespective of whether policies are actually changed after adoption and prior to implementation). Using the tools of game theory, the project undertakes comparative institutional analysis, examining the role of reconsideration under a variety of alternative rules and procedures within the context of particular economic problems. It seeks to understand the mechanisms by which particular institutions control (or fail to control) the tendency toward high concentration of power, and to elucidate the implications for economic policy.

The findings of this research are relevant to a wide range of practical issues. Collective choice problems are pervasive not only in public policy making, but also in cooperative research, education, partnerships, networks, and many other forms of social activity. These problems are resolved through a wide variety of formal and informal procedures. By improving our understanding of the relationships between procedures and outcomes, the study of collective choice will provide constructive guidance concerning the choice of procedures and the design of institutions. Insights concerning the effects of various rules on the influence of underrepresented groups may prove particularly useful.

This award will fund the First Summer School in Neuroeconomics for graduate students and post-docs in economics, neuroscience and psychology. The meeting will last 2 weeks and will be held in the Summer of 2006 at Stanford University. The first week of the meeting will focus on "computational neuroeconomics", which provides the unifying framework for the field and a common language for the three related fields. This part of the meeting will describe state-of-the art models of how the brain makes economic decisions (Which variables are computed? How are they computed? How do they interact with each other to generate choices?) The second week of the meeting will cover experimental techniques and their applications to neuroeconomics. The faculty for the program will consist of 12 of the leading researchers working in the field.

Intellectual Merit. The summer school program will seek to advance this new interdisciplinary field. First, it will provide an in-depth introduction to neuroeconomics to graduate students, post-docs, and some young researchers who are interested in doing work in this area. Second, it will help in the development of a common language and methodology for the field. This will be the first meeting of its kind and it will help to attract top scientific talent into the field.

Broader Impact. The meeting will foster relationships and collaborations between young and well-established researchers. This should prove especially valuable for underrepresented minorities, women, persons with disabilities, and scholars and institutions without the resources to get started with research in this demanding area.

DESCRIPTION (provided by applicant): There is a consensus among psychologists, neuroscientists, and clinicians that the consumption of addictive substances leads to malfunctions of brain's decision-making circutry, which eventually lead to systematic pathological choice. Advancements in behavioral neuroscience and neuroeconomics over the last decade have lead to the development of a number of competing theories about the nature of the underlying dysregulatory processes. One of the most prominent theories states that addiction is the result of a dysregulation of the reward learning circuitry. This application proposes three experiments that provide the first valid test of this theory. Aim 1 uses computational fMRI approaches imported from neuroeconomics in three novel experimental paradigms to test the theory. The grant also has a training component, Aim 2, designed to improve the nation's biomedical research base by training the Principal Investigator, a PhD student, and a post-doc on how to apply their knowledge on the neurobiology of decision making to the study of addiction. PUBLIC HEALTH RELEVANCE: A necessary condition for developing more successful treatments and prevention programs for addiction is to understand what are the mechanisms through which the addictive substances interfere with the proper functioning of the brain's decision-making circuitry. Advances in behavioral neuroscience over the last decade have lead to the development of a number of competing theories about the nature of the underlying dysregulatory processes. One of the most prominent competing theories states that addiction is the result of a dysregulation of the reward learning circuitry, and in particular of the computations that are encoded by the mesolimbic dopamine system. The neuroimaging experiments proposed in this application will provide critical new tests of this theory. Testing this theory is important because both its validation and its refutation will advance public health by narrowing down the set of possible mechanisms that clinicians and neuropharmacologists will have to consider in developing new treatments for addiction.

We often make choices without knowing why or in some cases even without being aware that we made a choice at all. Moreover, we sometimes find ourselves having made choices that, with hindsight, we do not believe we should have made. For example, we might find ourselves with a cookie in our mouth despite firm intentions to diet; or we might find ourselves strongly liking or disliking a person without any knowledge of why.

These examples are puzzling because we tend to think that all choices are deliberate and based on information of which we are fully aware. Clearly, this is not the case. In fact, it may be the exception. Yet there must always be some signature of our choice, and of the ingredients that went into it, in our brains. In this research project, the Principal Investigators will conduct a series of studies that systematically explore what happens our brains when we make various kinds of decisions, some conscious, some non-conscious, using state-of-the-art tools from cognitive neuroscience: high resolution magnetic resonance imaging, and rare electrical recordings of the brain from neurosurgical patients. These studies will result in an unprecedented dissection of the different components that contribute to how we make decisions and provide novel insights into the role of consciousness in human behavior.

The studies will help to answer some important outstanding questions in neuroscience, psychology, and economics. How quickly do we make decisions? Are consciously made choices slower than ones made in the absence of consciousness? Do animals make conscious choices? How conscious are the choices made by people who are addicted to drugs, to shopping, or to gambling? Can we consciously override strong preferences of which we are not aware? Answering these questions will allow us to understand the mechanisms behind decision-making. It will also give us a deeper understanding of the nature of consciousness and what it contributes to human behavior. Finally, the insights obtained from our studies will lay the groundwork for engineering intelligent decision-making in computers, robots, and distributed systems.

This three-year grant will purchase two pieces of equipment for magnetic resonance imaging of the brain at the California Institute of Technology. One equipment piece provides the best resolution in a horizontal orientation; the second provides imaging of behaving monkeys in vertical position. This will provide state-of-the-art tools for investigating brain structure and function in monkeys with noninvasive methods, and also provide opportunities for imaging post-mortem human brains. The technology will make possible a set of research studies on how the brain processes information, including how it sees faces, how it weighs different choices, and how it makes decisions and guides action. These are important questions in neuroscience, and the new equipment will greatly enhance science at the Caltech Brain Imaging Center. The grant will also provide opportunities for training of students and post-docs on the new equipment. This will include classes taught at Caltech as well as participation in individual research projects. The development of these new scientific tools will lead to a better understanding of how the brain works, and how it is "wired up." That knowledge, in turn, will contribute to efforts to build artificially intelligent systems. Taken together, the cutting-edge science enabled by the new equipment, and the training of the next generation of young scientists on it, will contribute substantially to cognitive neuroscience in America and worldwide.

"This award is funded under the American Recovery and Reinvestment Act of 2009
(Public Law 111-5)."

Self-control problems are at the core of many of the public policy challenges facing the United States. Examples include obesity, addiction, and low levels of savings. Not surprisingly, given its importance, the problem of self-control has been the subject of inquiry for many centuries. However, despite these efforts we still do not have answers to basic questions such as: What aspects of the brain?s decision making circuitry lead to temptation and self-control problems? Why are some brains much better at exercising self-control than others? What can be done to improve the brain?s ability to exercise self-control? In this research, the Principal Investigators plan to use the new tools and techniques of neuroeconomics (especially functional magnetic resonance imaging, diffusion tensor imaging, and repeated transcranial magnetic stimulation) to address these questions. The research involves studying the brains of dieters while they make decisions about which food they want to eat. The brain patterns of connectivity exhibited by successful and unsuccessful dieters will be compared to indicate the regions of the brain responsible for temptation and for self-control. The region of the brain thought to be responsible for self control ? the dorsolateral prefrontal cortex -- will also be studied using transcranial magnetic stimulation which may induce improvements in self-control.

"This award is funded under the American Recovery and Reinvestment Act of 2009
(Public Law 111-5)."


Firms, governments, and scientists are constantly striving to figure out what goods and services people want most and quantify their worth. The main technique used to do this in economics is to statistically analyze data on what people have bought before, in order to guess how purchases might change if people have more to spend, if prices rise or fall, or if similar products are introduced. However, this method is of limited use in forecasting the value of brand new products, and goods that are not traded in markets (particularly public goods which benefit everyone, such as clean air.)

When people are choosing, a complex cognitive and biological process underlies those choices. The proposed research uses empirical tools from cognitive neuroscience to measure aspects of these processes when experimental subjects make actual choices of consumer goods. Measures will include brain imaging, eyetracking of visual attention, and speed of responses. The goal is to use these measures to infer what people value, in order to understand the neural foundation of choice and to predict actual choices more accurately than other measures can.

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).

This NSF Major Research Instrumentation (MRI-R2) Award will enable a three-year grant to purchase an upgrade for a single piece of equipment for imaging the human brain at the California Institute of Technology. The upgrade, a 32-channel Total Imaging Matrix upgrade of a Siemens 3.0 Tesla MRI scanner, will substantially improve the resolution, the speed with which experiments can be done, and the kinds of imaging sequences that can be programmed. Taken together, these major enhancements will enable a range of questions about the structure, connectivity, and functioning of the human brain. Researchers at Caltech, in collaboration with a national and international consortium of scientists, will use the equipment to investigate how the brain makes financial decisions, how social information such as faces are processed, and how brain-machine interfaces can be built to decipher information from the brain to guide robotic prostheses. These are important, big open questions in neuroscience, and the new equipment will greatly enhance science at the Caltech Brain Imaging Center.

The grant will also provide opportunities for training of students and post-docs on the new equipment. This will include classes taught at Caltech as well as participation in individual research projects. The development of these new scientific tools will lead to a better understanding of how the brain works, how it is wired up, and how it may dysfunction in disease. That knowledge, in turn, will contribute to efforts to build artificially intelligent systems. Taken together, the cutting-edge science enabled by the new equipment, and the training of the next generation of young scientists on it, will contribute substantially to cognitive neuroscience in America and worldwide.

DESCRIPTION (provided by applicant): This project aims to contribute to our understanding of how the ability to exercise self-control changes across the life-cycle. It uses tools from neuroeconomics to investigate how the performance of a key self-control network in the brain changes with aging in healthy individuals. The overarching hypothesis is that the functional performance of this critical regulatory network improves with age, so that later in life it gets better at assigning values to the 'tempting options'that are consistent with their overall impact on well-being, as opposed to values that over-weight immediate rewards at the expense of other consequences. This hypothesis is based on prior neuroimaging studies that have shown that this network plays a critical role in dietary self- control, as well as related neuroimaging studies that have shown that the relevant circuitry changes with age. Ninety healthy individuals (30 young adults with ages 13-16, 30 middle-aged with ages 30-40, and 30 elderly adults with ages 65-70), who will be matched on gender and IQ, will participate in the study. In study 1 they will perform a self-control task in an fMRI experiment in which they have to make choices between smaller immediate monetary payments and larger but delayed payments. In study 2 we will collect structural and connectivity anatomical data to relate differences in behavioral and functional performance of the self-control circuitry to underlying anatomical differences. Preliminary behavioral data suggests the feasibility of the approaches for both planned studies, and all necessary infrastructure is available to rapidly implement the planned studies. The results will provide a detailed and quantitative picture of how the brain's ability to exercise self-control changes with the life-cycle. This will help us to understand why there are systematic improvements in self-control across the life-cycle for many individuals, and what neural impairments are present in those that do not exhibit such improvements. PUBLIC HEALTH RELEVANCE: The planned studies will investigate how the performance of the brain's self-control circuitry changes with aging (from adolescence to old age). The studies will also test how behavioral and functional changes in self-control are related to underlying neural anatomical changes over the life-cycle.

This Project investigates how the brain computes the values that rewards have for other people. While the prior two Projects study social decision-making that is based on the value that stimuli have for the person making the decision, this Project 3 studies decisions about the values rewards have for another person. Examples include altruistic behaviors, such as sacrificing food for a child or giving a donation to charity, but also encompass strategic and manipulative behaviors, such as a car salesman's need to figure out how much a customer might value a used car. These abilities are related to empathy and theory-of-mind, likely rare in other animals, and feature pronounced individual differences that can merge into pathology in mental illnesses such as autism. This Project will use the same computational framework as in Project 1, dissecting the neural signals that correlate with the value of decisions benefiting others at the time of choice, and with the values of the outcomes of those decisions (seeing somebody else get a benefit as a consequence of your decision). Only a handful of studies have addressed this topic, yet like the observational learning topic of Project 2 it is ubiquitous in human behavior. This Project continues our multimodal approach, using both fMRI and electrophysiological recordings, and investigating both humans and monkeys. Two Specific Aims compare the neural mechanisms behind processing decision values and experienced values for oneself, or for another person. A third Aim investigates how these mechanisms may be modulated by social context: if the other person is a stranger or familiar, or if they are judged to be deserving or not, and if the subject herself is being watched by others or not. A final fourth Aim leverages the data from Core 3 in an exploratory investigation of individual differences.

This NSF Major Research Instrumentation (MRI) Award will enable a three-year grant to purchase a major upgrade to the magnetic resonance imaging scanner used for studying the function and structure of the human brain by neuroscience researchers at the California Institute of Technology and their national and international collaborators. The award will support the upgrade of the existing Siemens Tim Trio 3T scanner at the Caltech Brain Imaging Center to the latest Siemens Prisma platform. The upgraded scanner will provide clearer and more detailed images of the human brain. Such an improvement in imaging capabilities will enable Caltech researchers to address fundamental problems such as how the brain learns from experience, how the brain makes decisions and how brains support the ability to learn from and interact with other people in social contexts. This new equipment will ultimately help Caltech researchers obtain a better understanding of how the brain works, how it is wired up, and how it may dysfunction in disease. That knowledge, in turn, will contribute to efforts to build artificially intelligent systems. The grant will also enable students and post-docs to obtain experience in using state-of-the-art brain imaging equipment, through classes taught at Caltech that offer hands-on-experience as well as through the participation of trainees in research projects that utilize the equipment. Taken together, the cutting-edge science enabled by the new equipment, and the training of the next generation of young scientists on it, will contribute substantially to cognitive, decision and social neuroscience at Caltech, in the US and worldwide.

To advance understanding about how the brain supports the capacity of humans to learn, make decisions and mediate social interactions it will be necessary to make progress in three distinct domains. First, there is a need to develop a much more detailed circuit-level understanding of the neural mechanisms underlying these various computational processes by resolving the functional properties of discrete neuroanatomical sub-divisions within each of the relevant brain areas of interest such as the amygdala, ventromedial prefrontal cortex, striatum and midbrain. Second, it is necessary to address how the various sub-processes that are implemented in these distinct sub-systems are ultimately integrated together at the systems level to drive complex behavior. Third, it will be important to characterize how the various computations and neural implementations differ across time, tasks and individuals. The Siemens Prisma scanner provides technical capabilities that are uniquely suited to advance progress in each of these three domains at the California Institute of Technology. The new platform will offer significant improvements in the quality of high resolution fMRI scans obtained from brain structures of interest, by minimizing dropout and geometric distortion, and by increasing signal-to-noise. These capabilities will also enhance the stability of the images obtained and hence improve test-retest reliability, while the improved gradient set will offer major gains in the quality of diffusion weighted imaging, and of functional connectivity data.