English  |  Français 

Decision making with unknown sensory reliability

Principal investigator(s): Sophie Deneve

To make fast and accurate behavioural choices, we need to integrate the noisy sensory input, take into account prior knowledge, and adjust our decision criteria. This is more difficult that it looks, because the reliability of the sensory observations is usually not known in advance. We use Bayesian decision models to model how human observers and neural populations could extract and use an estimate such sensory reliability on line.

Publications

Deneve, S., Making decisions with unknown sensory reliability., Frontiers in Neuroscience, 6:75, doi: 10.3389/fnins.2012.00075 (2012).

Deneve, S., Bayesian approach to decision making, Handbook of reward and Decision making, (2009).

INSERM ENS