Supervisor: Dr. Christopher Madan
School: Psychology

Description:

The field of decision making has grown to include influences from a variety of fields, including psychology, neuroscience, and computer science. This project will be centered within this multidisciplinary approach to decision making, investigating value-based decision making with computational methods such as multivariate pattern analysis (MVPA) of neuroimaging data (either EEG or fMRI) and/or reinforcement learning models.

Required skills:

• Demonstrable programming ability in Matlab or Python

Desirable skills:

• Previous experience with neuroimaging data (EEG or fMRI), prior experience implementing reinforcement learning models

Background readings:

1. Madan, C. R., Ludvig, E. A., & Spetch, M. L. (in press). Comparative inspiration: From puzzles with pigeons to novel discoveries with humans in risky choice. Behavioural Processes.
2. Madan, C. R., Ludvig, E. A., & Spetch, M. L. (2014). Remembering the best and worst of times: Memories for extreme outcomes bias risky decisions. Psychonomic Bulletin & Review, 21, 629-636.
3. Ludvig, E. A., Bellemare, M. G., & Pearson, K. G. (2011). A primer on reinforcement learning in the brain: Psychological, computational, and neural perspectives. In E. Alonso, E. Mondragon (Eds.), Computational Neuroscience for Advancing Artificial Intelligence: Models, Methods and Applications (pp. 111-144). Hershey, PA: IGI Global.

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