Alan G. Sanfey - US grants

[unreadable] DESCRIPTION (provided by applicant): This project proposes a series of experiments that will contribute to the burgeoning field of neuroeconomics, which attempts understand the component processes of decision-making by examining both behavior and the underlying neural substrates. The proposed studies seek to begin specifying the mechanisms of decisions, in particular the cognitive and emotional components that make up the decision-making process. Emotional influences on decision-making have been largely ignored for many years, but recent interest in how our emotional states can affect the type of decisions we make offer an exciting opportunity to broaden our knowledge of this most important process. Specifically, the proposed experiments will use functional magnetic resonance imaging (fMRI) to measure brain function of people engaged in economic decision- making. This proposal builds on previous work by the author examining the cognitive and emotional processes underlying human decision-making. In a prior study, we found reliable, independent patterns of neural activity corresponding to emotional and cognitive biases in a well-studied task of economic decision- making known as the Ultimatum Game. In this game, participants are placed in a consequential social interaction with another person, and decisions are made which correspond to emotional or cognitive motives. In the present proposal, hypotheses generated in this previous study will be systematically tested, and pilot data generated for future research submissions. The degree to which emotion and cognition affect decisions will be explored in greater depth, via the use of variants of the Ultimatum Game and fMRI. This research will also have broader implications for assessment and treatment of, neurological and psychiatric disorders that are often accompanied by poor decision-making abilities. A fuller understanding of the processes and structures involved in normal decision-making may greatly help characterize the decision-making deficits of patients suffering from these disorders and suggest avenues for the future treatment. [unreadable] [unreadable] [unreadable]

[unreadable] DESCRIPTION (provided by applicant): This project proposes a series of experiments that will contribute to the burgeoning field of the neuroeconomics of aging, which attempts understand the component processes of decision-making across the lifespan by examining both behavior and the underlying neural substrates. The proposed studies seek to begin specifying the mechanisms of decisions, in particular the deliberative and affective components that make up the decision-making process. Affective influences on decision-making have been largely ignored for many years, but recent interest in how our emotional states can affect the type of decisions we make offer an exciting opportunity to broaden our knowledge of this most important process. Further, examining the degree to which affective and deliberative processing differentially influence decision-making across the lifespan can provide important clues for the assessment of these basic cognitive functions. Specifically, the proposed experiments will use functional magnetic resonance imaging (fMRI) to measure brain function of people engaged in economic decision-making. This proposal builds on previous work by the author examining the processes underlying human decision-making in a consequential social interaction with another person. These studies have found reliable, independent patterns of neural activity corresponding to affective and deliberative biases, and shown that subsequent decisions appear to be based on these different motives. In the present proposal, hypotheses generated in this previous study will be systematically tested. Experiments using fMRI and variants of Ultimatum and Trust Games will explore in greater depth the degree to which affective and deliberative processes influence decisions in both young and older populations. [unreadable] [unreadable] The field of neuroeconomics is growing rapidly as researchers from many different and disparate areas seek to understand the neural basis of human decision-making behavior. It allows the study of individuals in meaningful social interactions allied to sophisticated methodological and technological approaches enabling investigation at various levels, from behavioral responses to the neural activity that underlie them. This approach offers a valuable method by which to assess how decision-making operates across the lifespan, and this research can have immediate impact in terms of better understanding real-life decisions faced by elderly populations in a variety of important domains. [unreadable] [unreadable] [unreadable]

Social and economic decisions cannot be fully explained by "rational" attempts to maximize monetary gain, even in very simple game-theoretic scenarios. Complex emotional processes such as anger, guilt or generosity act as hidden forces that lead to observable actions. Such "non-rational" motivations can drive our own decisions and they affect our beliefs about what motivates others' decisions as well. The goal of this project is to use automatic measurements of dynamic facial expressions, in combination with other measurements such as functional MRI (fMRI) and eye-tracking, to investigate the role of non-rational motivations in social decision making. The core of the approach is to use state-of-the-art computer vision techniques to extract facial actions from video in real-time while participants interact with a computer or with each other, in some cases viewing live video of each others' faces. The investigators will use powerful statistical machine learning techniques to make inferences about the participants' internal emotional states during the interactions. The goal is to use the inferences concerning emotional state (a) to predict participants' behavior; (b) to explain why a decision is made in terms of the hidden forces driving it; and (c) to build autonomous agents that can use this information to drive their interactions with humans.

This multidisciplinary project contributes to several fields such as psychology, neuroscience, and economics. First, it develops new methodologies to study decision processes. Second, it uses these methods to test hypotheses about social decision-making and to bridge the gap between observable actions and the internal states that generated them. Third, the investigators intend to make available a dataset and toolset that should be an extremely useful for other investigators analyzing facial expression in multiple contexts. Additionally, automatic and on-line decoding of internal motivational states lays the groundwork for "affectively-aware" interactive computers, or artificial systems that can make inferences about the emotions and intentions of their users. Through the development of these systems, this project will make a significant contribution to the growing field of human-machine interaction.

[Supported by Perception, Action and Cognition, Decision, Risk and Management Sciences, and Robust Intelligence]