Close
Institute of Cognitive Neuroscience
Value Computation, Uncertainty and Choice
Our group study the neural computations underpinning the decision-making process across a broad range of domains such as perceptual, economic and social choice. Our main question is how the brain copes with different sources of uncertainty and how this impact on the quality of decisions. We approach this question by combining computational modelling with experimental economics, psychophysics and brain imaging methods.
Available projects
(I) What code does the medial prefrontal cortex use to represent value and confidence?
(II) Understanding confidence-driven reinforcement learning (project supported by Google DeepMind)
(III) Are choice biases an 'adaptive'?
These are only some of the ongoing projects in the lab (see bdmalab.org for more info)
Other projects can be discussed and developed together with the students to fit their skills and curiosities.
Recent Publications:
Tarantola, T., Kumaran, D., Dayan, P., De Martino, B. Prior preferences beneficially influence social and non-social learning, Nature Communications (2017)
Vaghi, M., Luyckx, F., Sule, A., Fineberg,N., Robbins,T., De Martino, B Compulsivity Reveals a Novel Dissociation between Action and Confidence, Neuron (2017)
De Martino, B., Bobadilla-Suarez, S., Nouguchi, T., Sharot,T & Love, B. Social Information Is Integrated into Value and Confidence Judgments According to its Reliability, Journal of Neuroscience (2017)
Folke, T., Jacobsen, C., Fleming, S. M. & De Martino, B. Explicit representation of confidence informs future value-based decisions. Nature Human Behaviour (2016)