The Fred Kavli Plenary Lecture

The Kavli Foundation, based in Oxnard, California, is dedicated to the goals of advancing science for the benefit of humanity and promoting increased public understanding and support for scientists and their work. The Foundation’s mission is implemented through an international program of research institutes, professorships, and symposia in the fields of astrophysics, nanoscience, neuroscience, and theoretical physics as well as prizes in the fields of astrophysics, nanoscience and neuroscience. To learn more about their foundation, please visit their website.

2024 Kavli Speaker

Sendhil Mullainathan

Sendhil Mullainathan

Faculty Director of the Center for Applied Artificial Intelligence, Chicago Booth

Sendhil Mullainathan is the Roman Family University Professor of Computation and Behavioral Science at Chicago Booth, where he is also the inaugural Faculty Director of the Center for Applied Artificial Intelligence. His latest research is on computational medicine—applying machine learning and other data science tools to produce biomedical insights.  In past work he has combined insights from behavioral science with empirical methods—experiments, causal inference tools, and machine learning—to study social problems such as discrimination and poverty. He currently teaches a course on Artificial Intelligence.

Outside of research, he co-founded a non-profit to apply behavioral science (ideas42), a center to promote the use of randomized control trials in development (the Abdul Latif Jameel Poverty Action Lab), has worked in government in various roles, and currently serves on the board of the MacArthur Foundation board. He is also a regular contributor to the New York Times.

2023 Plenary Lecture

Lise Vesterlund

University of Pittsburgh

Lise Vesterlund is the Andrew W. Mellon Professor of the Department of Economics at the University of Pittsburgh and the Director of the Pittsburgh Experimental Economics Laboratory (PEEL) and of the Behavioral Economic Design Initiative (BEDI). She is a Research Associate with the National Bureau of Economic Research. A co-author of the book, “The No Club: Putting a Stop to Women’s Dead-End Work,” her highly influential research on gender differences in advancement has been featured by The New York Times, The Guardian, Wall Street Journal, The Washington Post, The Economist, and The Financial Times. .

 

2022 Plenary Lecture

Dana Small

Professor and Divisional Director, Department of Psychiatry, Yale University

Dr. Dana Small is a Professor in the Departments of Psychology and Psychiatry, and she is the Divisional Director of Nutritional Psychiatry at Yale University. She also founded and directs the Modern Diet and Physiology Research Center. Dana is known for developing and disseminating the tools and methods to study ingestive behavior in the fMRI environment and for her work uncovering the neural circuits of food reward. This work has been recognized by numerous awards from international societies and invitations to deliver over 200 lectures, including the Presidential Keynote for the Society for Neurosciences. Dana served two terms on the National Academy of Sciences Board on Behavior, Cognitive and Sensory Sciences and currently serves as the president for the Society of the Study of Ingestive Behavior.

 

2021 Plenary Lecture

Terrie E. Moffit

Professor of Social Development, King’s College, London, and Nannerl O. Keohane University Professor of Psychology, Duke University

Terrie E. Moffitt’s expertise is in the areas of lifelong aging, mental health, and longitudinal research methods. She is the associate director of the Dunedin Longitudinal Study, which follows a 1972 birth cohort in New Zealand. She also founded the Environmental Risk Longitudinal Twin Study (E-Risk), which follows a 1994 birth cohort in Britain. Moffitt is a licensed clinical psychologist, with specialization in neuropsychological assessment. Her current service includes chair of the Board on Behavioral, Cognitive and Sensory Sciences at the National Academies of Sciences, chair of the National Institute on Aging’s Data-Monitoring Board for the Health and Retirement Study, and chair of the jury for the Klaus J. Jacobs Prize (Switzerland). She is an elected fellow of the US National Academy of Medicine, British Academy, UK Academy of Medical Sciences, and Association of Psychological Science. Moffitt is recipient of the Stockholm Prize, the Klaus Jacobs Prize and the NARSAD Ruane Prize for her work on mental health, and the Maltilda White Riley Award from the NIH for her recent work on aging processes in midlife adults. Moffitt received her PhD in psychology at the University of Southern California, and completed her postdoctoral training at the UCLA Neuropsychiatric Institute. She enjoys working on her poison-ivy farm in North Carolina. Learn more at www.moffittcaspi.com.

 

2020 Plenary Lecture

Elke U. Weber

Professor of Psychology and Public Affairs, Princeton University

“Cognition and Motivation in Physical and Social Space and Time”
Perception, attention, learning, and memory are studied by cognitive psychologists, whereas values, goals, emotions, and social identity are the domain of social psychologists.  Things get interesting, however, when we look at the way in which cognition and motivation intersect and interact. The probabilities and utilities of the outcomes of risky choice alternatives, for example, are not evaluated independently, as normative models say they should be. Instead, wishful thinking increases the perceived odds of positive events and fear raises the perceived likelihood of adverse events. Attention is clearly driven by cognitive variables such as past experience but also by motivational variables such as social identity.  As boundedly-rational information processors, we navigate the long list of daily choices with input from our physical and social environmental where cognition and motivation intersect and with a focus that can shift from the past to the present and the future. I will argue that many patterns of behavior are better understood and predicted when the decisions of individuals are embedded into a framework that allows for the influence of the physical and social context on cognition and motivation and for some dynamic evolution over time.  I will illustrate this point with recent data on responses to important social issues, from intergenerational contributions to combat climate change to political polarization on Covid-19 and climate change and the depolarizing effect of personal exposure to these hazards.
2019 Plenary Lecture

Peter Dayan

Director, Max Planck Institute for Biological Cybernetics

“Savouring and its Modulation by Prediction Errors” 
Humans and animals apparently extract intrinsic value from anticipating, or savoring, impending rewards. Further, when these outcomes are uncertain, people typically prefer to know their fate in advance. We link these two phenomena through the suggestion that reward prediction errors occasioned by the revelation can boost the level of savoring. The result is a behavioural anomaly that has consequences for maladaptivity such as gambling. We formalize this proposal, and investigate its neurobiology in humans using fMRI. In a task involving delayed probabilistic rewards, we found that participants had a greater preference for advance information for greater delays and lower probabilities, consistent with the boosting hypothesis. Ventromedial prefrontal cortex (vmPFC) encoded the time-varying anticipatory value signal predicted by the behavioral model. Reward prediction errors, encoded in dopaminergic midbrain, were coupled to vmPFC via hippocampus. We suggest that boosting might be driven by enhanced hippocampus-based imagination of future outcomes.
2018 Plenary Lecture

Alex Kacelnik, FRS

Emeritus Professor of Behavioural Ecology Department of Zoology, Oxford University

“Choice and value: the biology of decision making” 
Economics and evolutionary biologists often deal with similar behavioural issues, including the construction of preferences, the relation between normative and descriptive accounts, the significance of violations of normative predictions, and biases for or against uncertainty and risk, to name just a few.  The structure of their research programs, however, differs substantially, and this is particularly salient regarding the justification for normative hypotheses and for the role of optimality. I will address some of these differences, drawing on examples from our experimental behavioural work on decision making across different species, ranging from plants to insects, fish, birds, and mammals. A common thread is the use of violations of optimality predictions to enrich and refine normative (evolutionary) analyses.
2017 Plenary Lecture

Robert Shiller

Yale University

Narrative Economics and Neuroeconomics
The human mind is highly tuned towards narratives or human-interest stories that can justify ongoing actions. The human brain, when confronted with the need to make economic decisions, does not simply maximize a stable utility function as hypothesized by much economic theory. This lecture considers the epidemiology of narratives relevant to economic outcomes, allowing them to “go viral” and spread far, even worldwide, thereby influencing economic outcomes. The 1920-21 Depression, the Great Depression starting in 1929, the so called “Great Recessions” of 1973-75, 1980-82, and 2007-9, the secular stagnation-inequality scare after 2008, and President Donald Trump’s economic revolution, are considered in view of the popular narratives of their respective times. These examples are seen as revealing the importance of the linkage of human brains and now computers through narratives associated with popular models of the economy, and offering new research opportunities for both economics and neuroscience.
2016 Plenary Lecture

Richard G M Morris, FRS

Centre for Cognitive and Neural Systems,The University of Edinburgh

“Retaining Memory: the paradoxical benefits of both novelty and familiarity” 
One key challenge in memory research is to understand the selectivity of memory consolidation – the process by which memory traces become stabilised over time. A key issue is that some events are remembered, others are not. In recent publications, I have argued that the ‘automatic recording of attended experience’ by which we keep track of daily events is followed by the loss of many but not all memory traces within the day, with only some persisting longer in association with the upregulation of plasticity-related proteins (PRPs) that stabilise synaptic potentiation (cellular consolidation) that is the basis of memory formation. Novelty is adept at upregulating PRPs. Memory traces are encoded in parallel in the cerebral cortex (cortical consolidation), with the additional twist that new information may be more successfully assimilated if it fits well with prior knowledge that has previously been stored in cortex in the form of ‘schemas’.  Prior knowledge is, of course, information with which we are most familiar.  The economic implications of this paradox are not my realm of expertise, but I will conclude with some thoughts about accuracy vs. gist that perhaps each affect our economic behaviour.
2015 Plenary Lecture

Ann Graybiel, PhD

Massachusetts Institute of Technology

“The basal ganglia: heartland of neuroeconomics”
 
Regions of the medial prefrontal cortex are known to function in organizing behavior and emotional decision-making, both key functions disturbed in a range of neurologic and neuropsychiatric disorders. In our laboratory, we are seeking to understand mechanisms underlying these functions by applying optogenetic manipulations and microstimulation to these regions and their corticostriatal circuits. We find that we can interrupt the transition from deliberative decision-making to a habitual mode of decisions to act, and can interrupt habitual and insistently repetitive behaviors. In other experiments, we can selectively disrupt decision-making under different contexts involving weighing the costs and benefits of such choices.
2014 Plenary Lecture

Colin Camerer, PhD

Robert Kirby Professor of Behavioral Finance and Economics at the California Institute of Technology ~ 2013 MacArthur Fellow

“The Neuroeconomics of Complex Social Valuation” 
The creation of mechanistic neural models of choice computation can come from bottom-up or top-down. I start with classic topics from the social science of collective behavior. In each of these topics, there are long-standing puzzles that do not appear to be easily resolved by simply observing more behavior. The approach discussed in this talk is therefore unapologetically top-down: We start with behavioral observation, hypothesize a biological cause for the behavior and investigate that cause at an intermediate level (e.g., neural circuitry), with whatever method is appropriate for understanding the intermediate level. Three examples illustrate this approach: the influence of affiliative hormones (AVP) on risky cooperation; bargaining with private information (behavior and fMRI); and the formation and crash of asset price bubbles (fMRI).
2013 Plenary Lecture

Vernon L. Smith, PhD

Professor of Economics and Law, Chapman University ~ Nobel Laureate in Economics, 2002

“Adam Smith: From Propriety and Sentiments to Property and Wealth” 
“Why return to Adam Smith?” Because we learn that he had fresh-for-today insights, derived from a modeling perspective that was never part of economic analysis. Smith wrote two classics: The Theory of Moral Sentiments (1759; hereafter Sentiments); and An Inquiry into the Nature and Causes of the Wealth of Nations (1776; hereafter Wealth). In Sentiments it is argued that human sociability in close-knit groups is governed by the “propriety and fitness” of conduct based on sympathy (that surely influenced Darwin). This non-utilitarian model provides new insights into the results of 2-person experimental “trust” and other games that defied the predictions of traditional game theory in the 1980s and 90s, and offers testable new predictions. Moreover, Smith shows how the civil order of “property” grew naturally out of the rules of propriety. Property together with what I call Smith’s Discovery Axiom then enabled his break-through in Wealth that defined the liberal intellectual and practical foundation of two centuries of Western economic growth.
2012 Plenary Lecture

William T. Newsome, PhD

Professor, Neurobiology, Stanford University School of Medicine ~ Investigator, Howard Hughes Medical Institute

“A new look at gating: Selective Integration of sensory signals through network dynamics”
 
A hallmark of decision-making in primates is contextual sensitivity: a given stimulus can lead to different decisions depending on the context in which it is presented. This kind of flexible decision-making depends critically upon gating and integration of context-appropriate information sources within the brain. We have analyzed neural mechanisms underlying gating and integration in animals trained to perform a context-sensitive decision task. Surprisingly, both relevant and irrelevant sensory signals are present within frontal lobe circuits that form decisions, implying that gating occurs very late in the process. Dynamical systems analysis of the neural data, combined with a dynamical recurrent network model, suggests a novel mechanism by which gating and integration are combined in a single process.
2011 Plenary Lecture

Professor Antonio Damasio

University Professor, Dornsife Professor of Neuroscience ~ Director of USC’s Brain and Creativity Institute

“About the Neural Basis of Feelings”
 
A reflection on recent advances and questions on the neuroscience of feelings, with an emphasis on the different neural platforms required for sensing affective states.
2010 Plenary Lecture

Professor Wolfram Schultz, MD, PhD, FRS

Department of Physiology, Development & Neuroscience, University of Cambridge, UK

At our 2010 Society for Neuroeconomics conference, we were proud to have the first Kavli sponsored lecture:
“Predictive, subjective and adaptive coding of reward value and risk”
We investigated basic neuronal reward and risk processes important for decision making using neurophysiological methods in monkeys and brain imaging in humans. Informed decisions between different rewards are based on predictions about future outcomes. We investigated the nature of reward predictive neuronal signals in the amygdala by manipulating the informative nature of the predictive stimulus. We changed the contextual background reward while keeping stimulus reward constant. True reward predictive responses reflected the difference between background and stimulus reward, suggesting that reward contingency rather than simple stimulus-reward pairing (contiguity) determined the predictive neuronal responses. Reward value appears to depend on the individual decision maker and the environment, and hence is subjective. Dopamine neurons in monkeys, and likely downstream striatal activations in humans, discounted reward value across temporal delays of a few seconds despite unchanged objective reward value, suggesting subjective value coding. Reward predictions inform about probability distributions of reward values with varying degrees of risk. Subpopulations of orbitofrontal and striatal neurons, and most dopamine neurons, showed adaptation of reward related responses to the mean and variance (risk) of predicted probability distributions of reward value. These data suggest matching of distributions between neuronal output responses and reward input, resulting in effective reward coding akin to sensory adaptation. Adaptive teaching signals provide stability of learning and established performance in noisy environments. Adaptive neuronal coding may explain such behavioural phenomena as reference dependent coding. The processing of risky outcomes depends on the subjective perception of risk and, separately, on the personal attitudes of individual decision makers towards risk. Dopamine and orbitofrontal neurons in monkeys showed distinct risk signals that were unlikely to constitute value or utility signals. In humans, risk signals and the influence of risk on value signals covaried with individual risk attitudes in subregions of prefrontal cortex, suggesting subjective coding of risk and its influence on reward value. Taken together, these data demonstrate the nature of neuronal reward predictions and suggest subjective coding of key reward variables via temporal delays and adaptive processes in main reward structures of the brain.

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