Reasoning and Economic Decisions
What we do
Neuro and cognitive-economics are emerging fields at the intersection of Neuroscience, Psychology and Economics with the aim of providing a unified theory of human decision-making. These lines of research bring together theoretical and formal models with empirical approaches and provide conceptual tools for understanding and modeling human cognition, reasoning and behavior. The aim is to understand both physiological and psychological mechanisms by which economic decisions are made. The economic approach is used to describe choice behavior globally and formally. The psychological approach is used to understand the role of attentional mechanisms, logical thinking, and reasoning skills in information representation and to examine individual differences. The neurobiological approach focuses on the identification of the brain functional networks supporting economic decisions.
Particular emphasis is given to the following topics:
Plasticity of strategic sophistication in interactive decision making.
Neural correlates of strategic thinking.
Role of intelligence in individual and social learning.
How attentional mechanisms, logical thinking, and reasoning skills affects how individuals encode and represent relational information about contingencies.
Identification of sources of heterogeneity in interactive and non-interactive decision making.
To study these topics, we use methods such as psychophysics (eye-tracking and skin conductance), computerized behavioral tasks, and neuroimaging (fMRI).
Plasticity of strategic sophistication (with Davide Marchiori and Sibilla di Guida, University of Southern Denmark)
Who does Forward Induction, and how: an eye-tracking study (with Aldo Rustichini, University of Minnesota)
The effect of evidential impact on perceptual probabilistic judgments (with Katya Tentori, Stefania Pighin and Marta Mangiarulo, University of Trento)
Combining eye-tracking with fMRI to disclose the neural processes underlying strategic thinking in games (with Joshua Zonca, Italian Institute of Tecnology, Nadege Bault, University of Plymouth, Giorgio Coricelli, University of Southern California)
Learning optimal Bayesian strategy through observation (with Alexander Vostroknutov, University of Maastricht)
Who we are
Sean Anthony Byrne
What we publish
Testing the level of consistency between choices and beliefs in games using eye tracking. Polonio, L., and Coricelli, G. (2019), Games and Economic Behavior, 113, 566-586. https://doi.org/10.1016/j.geb.2018.11.003
We use eye-tracking to identify possible causes of inconsistency between choices and beliefs in games. Participants play a series of two-player 3x3 one-shot games (choice task) and state their beliefs about which actions they expect their counterpart to play (belief elicitation task). We use a model-based clustering method to group participants according to the pattern of visual analysis they use to make their decisions in the two tasks. We find that heterogeneity in the lookup patterns reflects the adoption of different models of choice. Our results suggest that there are two main reasons why participants do not best respond to their beliefs in games. First, many of them take into account the incentives of the counterpart when stating their beliefs, but not when choosing their actions. Second, some participants have other-regarding preferences and attempt to find a cooperative solution of the game.
The role of intelligence in social learning. Vostroknutov, A., Polonio, L., and Coricelli, G. (2018). Scientific Reports, 8(1), 6896. https://doi.org/10.1038/s41598-018-25289-9
Studies in cultural evolution have uncovered many types of social learning strategies that are adaptive in certain environments. The efficiency of these strategies also depends on the individual characteristics of both the observer and the demonstrator. We investigate the relationship between intelligence and the ways social and individual information is utilised to make decisions in an uncertain environment. We measure fluid intelligence and study experimentally how individuals learn from observing the choices of a demonstrator in a 2-armed bandit problem with changing probabilities of a reward. Participants observe a demonstrator with high or low fluid intelligence. In some treatments they are aware of the intelligence score of the demonstrator and in others they are not. Low fluid intelligence individuals imitate the demonstrator more when her fluid intelligence is known than when it is not. Conversely, individuals with high fluid intelligence adjust their use of social information, as the observed behaviour changes, independently of the knowledge of the intelligence of the demonstrator. We provide evidence that intelligence determines how social and individual information is integrated in order to make choices in a changing uncertain environment.
Gaze data reveal individual differences in relational representation processes. Zonca, J., Coricelli, G., and Polonio, L. (2020). Journal of Experimental Psychology: Learning, Memory, and Cognition, 46(2), 257–279. https://doi.org/10.1037/xlm0000723
In our everyday life, we often need to anticipate the potential occurrence of events and their consequences. In this context, the way we represent contingencies can determine our ability to adapt to the environment. However, it is not clear how agents encode and organize available knowledge about the future to react to possible states of the world. In the present study, we investigated the process of contingency representation with three eye-tracking experiments. In Experiment 1, we introduced a novel relational-inference task in which participants had to learn and represent conditional rules regulating the occurrence of interdependent future events. A cluster analysis on early gaze data revealed the existence of 2 distinct types of encoders. A group of (sophisticated) participants built exhaustive contingency models that explicitly linked states with each of their potential consequences. Another group of (unsophisticated) participants simply learned binary conditional rules without exploring the underlying relational complexity. Analyses of individual cognitive measures revealed that cognitive reflection is associated with the emergence of either sophisticated or unsophisticated representation behavior. In Experiment 2, we observed that unsophisticated participants switched toward the sophisticated strategy after having received information about its existence, suggesting that representation behavior was modulated by strategy generation mechanisms. In Experiment 3, we showed that the heterogeneity in representation strategy emerges also in conditional reasoning with verbal sequences, indicating the existence of a general disposition in building either sophisticated or unsophisticated models of contingencies.
Combining eye-tracking with fMRI to disclose the neural processes of strategic thinking in games. In preparation.
We combined fMRI and eye-tracking to study the neural correlates of strategic thinking. In this project we are trying to define the brain networks that sustain the decision making process of differ types of players (sophisticated, unsophisticated, self-centered and with other regarding preferences). Following the hierarchical model of the prefrontal cortex of Koechlin et al. (2003), we hypothesize that more sophisticated strategies are represented in more anterior portions of the prefrontal cortex and involve regions that are part of “theory of mind” circuitry, necessary to predict what others believe and intend to do.
Aldo Rustichini - University of Minnesota
Giorgio Coricelli - University of Southern California
Alexander Vostroknutov - Maastricht University
Sibilla Di Guida - University of Southern Denmark
Davide Marchiori - University of Southern Denmark
Paolo Cherubini - University of Milan Bicocca
Katya Tentori - University of Trento
Nicolao Bonini - University of Trento
Joshua Zonca - Italian Institute of Technology
Nadege Bault - University of Plymouth
Carlo Reverberi - University of Milan Bicocca
Luca Polonio -Neuroeconomics seminar, University of Zurich, Zurich Center for Neuroeconomics (ZCN), Invited talk: “The Process of Choice in Normal-Form Games”.
Luca Polonio - Department of Economics, Ca’ Foscari University of Venice, Invited talk: “Cognitive Skills explain richness of Strategic Behavior”.
Luca Polonio - School of Economics and Management, University of Florence, Invited talk: “Cognitive Skills explain richness of Strategic Behavior”.
Luca Polonio - Workshop on Cross-disciplinary Experimental Methods, Department of Economics, University of Essex. Keynote speaker: “Gaze data reveal strategic behavior and social preferences in interactive decision making”.
Luca Polonio - Department of Economics, University of Bristol. Invited talk: “From the patterns of visual analysis to the models of choice in interactive decision making”.
Luca Polonio - 15th NeuroPsychoEconomics Conference, Oral Presentation: “Disclosing the link between cognitive reflection and sophistication in strategic interaction: the crucial role of game representation”.
Mangiarulo, M., Pighin, S., Polonio, L., and Tentori, K. (2020). The effect of evidential impact on perceptual probabilistic judgments. Cognitive Science, in press. DOI: 10.1111/cogs.12919
Zonca, J., Coricelli, G., and Polonio, L. (2020). Gaze patterns disclose the link between cognitive reflection and sophistication in strategic interaction. Judgment and Decision Making, Vol. 15, No. 2, pp. 230 – 245.
Zonca, J., Coricelli, G., and Polonio, L. (2020). Gaze data reveal individual differences in relational representation processes. Journal of Experimental Psychology: Learning, Memory, and Cognition, 46(2), 257–279. https://doi.org/10.1037/xlm0000723
Zonca, J., Coricelli, G. and Polonio, L. (2019). Does exposure to alternative decision rules change gaze patterns and behavioral strategies in games? Journal of the Economic Science Association, 5(1), 14-25. https://doi.org/10.1007/s40881-019-00066-0
Polonio, L., and Coricelli, G. (2019). Testing the level of consistency between choices and beliefs in games using eye-tracking. Games and Economic Behavior, 113, 566-586. https://doi.org/10.1016/j.geb.2018.11.003
Vostroknutov, A., Polonio, L., and Coricelli, G. (2018). The role of intelligence in social learning. Scientific Reports, 8(1), 6896. https://doi.org/10.1038/s41598-018-25289-9