How people make decisions.
The goal of the lab is to reverse-engineer the algorithms that are used by the brain to make decisions. To this end, we design behavioral experiments that allow us to distinguish between alternative theories about how decisions are made.
The kinds of decisions we study range from very simple ones like deciding which of two objects is brighter, to more complex decisions that require planning and reasoning.
The main tools we use are computational models and behavioral experiments in humans. We also collaborate with laboratories that make neurophysiological recordings in non-human animals.
We are particularly interested in understanding how people assign degrees of confidence to their decisions. We are also interested in how people learn internal models of the environment, and how these internal models are used in decision making.
Read more about our research...
- Counterfactual reasoning underlies the learning of priors in decision making. Zylberberg A, Wolpert DM, Shadlen MN (2018). Neuron, 99, 1-15.
- The construction of confidence in a perceptual decision. Zylberberg, A., Barttfeld, P., Sigman, M. (2012). Frontiers in integrative neuroscience, 6.
- The human Turing machine: a neural framework for mental programs. Zylberberg, A., Dehaene, S., Roelfsema, P. R., Sigman, M. (2011). Trends in cognitive sciences, 15(7), 293-300.