EP Cognitive and Behavioural Neuroscience Seminar: Learning relative values through reinforcement learning: computational bases and neural evidence
Dr Stefano Palminteri (ENS, Paris)
Tuesday, 05 December 2017, 1pm to 2pm
Schlich Lecture Theatre, Plant Sciences, S. Parks Road, Oxford OX1 3RB
Hosted by Dr Matthew Apps
A fundamental question in the literature about value-based decision making is whether values are represented on an absolute, rather than on a relative scale (i.e. context-dependent). Such context-dependency of option values has been extensively investigated in economic decision-making in the form of reference point-dependence and range adaptation. However, context-dependency has been much less investigated in reinforcement learning (RL) situations. Using model-based behavioral analyses we demonstrate that option values are learnt in a context-dependent manner. In RL context-dependence produces several desirable behavioral consequences: i) reference point dependence of option values benefits punishment-avoidance learning and ii) range adaptation allows similar performance for different levels of reinforcer magnitude. Interestingly, these adaptive functions are traded against context-dependent violation of rationality, when options are extrapolated from their original choice contexts.