SC7: Self and Future: Optimism Bias
The course will focus on psychological and neuroimaging research that investigates biases in the perception of our future. It will encompass
i) an overview of empirical evidence for optimism bias,
ii) a closer look at recent methodological developments and findings relating to belief updating, computational modeling and dynamic causal modeling, and
iii) a consideration of implications for other domains such as decision making and psychiatric disorders.
Conceptual: To scrutinize whether what we believe is biased by what we want to believe, and whether the value of desirable beliefs is processed similarly to that of external rewards such as food or money.
Methodological: Development of experimental designs that can assess biased belief updating, and analysis of underlying computational and neural mechanisms.
Sharot, T., & Garrett, N. (2016). Forming Beliefs: Why Valence Matters. Trends Cogn Sci, 20(1), 25-33. http://www.ncbi.nlm.nih.gov/pubmed/26704856
Kunda, Z. (1990). The case for motivated reasoning. Psychol Bull, 108(3), 480-498. http://www.ncbi.nlm.nih.gov/pubmed/2270237
Shepperd, J. A., Klein, W. M., Waters, E. A., & Weinstein, N. D. (2013). Taking Stock of Unrealistic Optimism. Perspect Psychol Sci, 8(4), 395-411. http://www.ncbi.nlm.nih.gov/pubmed/26045714
Bojana Kuzmanovic is postdoc at the Max Planck Institute for Metabolism Research,
Translational Neurocircuitry Group. After studying psychology, she did her PhD at the University Hospital Cologne and at the Research Center Juelich. Her interests migrated from social cognition to belief updating and decision making.