Research fellow at Inserm
École Normale Supérieure, Inserm, Paris, France
Biases of human learning and decision-making
Stefano Palminteri and his team are studying the biases of human learning and decision-making. More precisely, they decipher the cognitive mechanisms and neural bases of these cognitive biases using a combination of experimental psychology, mathematical modelling and brain imaging.
Whereas the investigation of decision-making biases, in the form of deviations from optimal decision-making, has a long and venerable history in economics and psychology, learning biases have been much less systematically documented, investigated and formalized. This is problematic since most of the decisions we deal with in everyday life are experience-based and choice contexts are often recurrent, thus allowing learning to occur and influence decision-making. The relative lack of experimental investigation of learning biases is also surprisingly considering the great importance of these processes might play in psychiatric pathogenesis and economic maladaptive behaviours. In the present proposal we aim at studying learning biases at different levels of investigation (behavioural, computational and neural) and to try to link them to inter-individual variability. The results expected from this project will be of several natures. First, computational and behavioural studies will lead to the proposition of models that explain learning biases and idiosyncrasies observed in human subjects. Second, we will identify the neurobiological determinants of these biases in both terms of anatomical and functional correlates. The neural mapping of learning biases will help us to understand why the biases themselves arise (neural constraints) and also to formulate hypotheses concerning their relations with brain maturation and pathological states. Third, our studies will shed light on the relation between computational learning biases and psychiatric traits. These studies will be used to generate hypotheses concerning the computational mechanism underlying psychiatric diseases that will be subsequently tested in clinical populations. Finally, we will investigate the relation between learning biases and diverse socioeconomic environments. This will represent a step forward trying to understand, form a computational point of view, how aberrant learning processes contribute to the vicious loop sustaining poverty and maladaptive economic behaviours.
2012: PhD, Pierre and Marie Curie University, Paris, France
2012-2013: Post-doctorate, Ecole Normale Supérieure, Paris, France, Giorgio Coricelli's team
2014-2015 : Post-doctoral fellow, University College London, Great Britain, Sarah-Jayne Blakemore's team
2016 : Post-doctoral fellow, Ecole Normale Supérieure, Paris, France, Etienne Koechlin's team
2017: appointed Team Leader, Ecole Normale Supérieure, Paris, France
2017: winner of the Emergence(s) program of the City of Paris
2017: Winner of the ATIP-Avenir program
2018: winner of the Fyssen Foundation