The Fête de la Science is a free event, open to all, which takes place over ten days in France and overseas. It is organised by the Ministry of Higher Education, Research and Innovation, in collaboration with many stakeholders in the French scientific and cultural landscape.
The researchers at the ENS open the doors of their laboratories to all! Come and discover their research through visits, workshops, conferences and exhibitions.
In light of the new tools for researchers to conduct and communicate their research, we organized a workshop to discuss essential elements for a researcher in 2019. Morning session speakers (Dr. Franck Ramus, Élodie Chabrol, and Judith Lenglet) will advise researchers on how to communicate their research to their peers and the general public (e.g. blogs, twitter, graphical presentation), while afternoon speakers (Dr. Guillaume Dumas, Georgia Loukatou, Sacha Altay, and Dr. Camila Scaff) will showcase crucial tools (e.g.
To meet Ingrid Johnsrude, please contact Daniel Pressnitzer: daniel.pressnitzer@gmail.com.
To meet Coren Apicella, please contact Nicolas Baumard: nbaumard@gmail.com.
To meet Catherine Hobaiter, please contact Philippe Schlenker: philippe.schlenker@gmail.com
To meet Stephen Fleming, please contact Catherine Tallon-Baudry: catherine.tallon-baudry@ens.fr
The brain and cognitive sciences are hard at work on a great scientific quest — to reverse engineer the human mind and its intelligent behavior. Yet these field are still in their infancy. Not surprisingly, forward engineering approaches that aim to emulate human intelligence (HI) in artificial systems (AI) are also still in their infancy.
Western history of thought abounds with claims that knowledge is valued and sought. Yet people often choose not to know. We call the conscious choice not to seek or use knowledge (or information) deliberate ignorance. Using examples from a wide range of domains, we demonstrate that deliberate ignorance has important functions. We systematize types of deliberate ignorance, describe their functions, discuss their normative desirability, and consider how they can be modeled. We conclude that the desire not to know is no anomaly.
Modern theories of reinforcement learning posit two systems competing for control of behavior: a "model-free" or "habitual" system that learns cached state-action values, and a "model-based" or "goal-directed" system that learns a world model which is then used to plan actions. I will argue that humans can adaptively invoke model-based computation when its benefits outweigh its costs. A simple meta-control learning rule can capture the dynamics of this cost-benefit analysis. Neuroimaging evidence points to the role of cognitive control regions in this computation.
Huntington’s disease (HD) is a inherited neurodegenerative disease of the middle life due to striatum atrophy. HD patients show language impairments yet, the role of the striatum in language remains debated. Indeed, task assessing language require decision-making, which is impaired in HD. I studied HD to specify the role of the striatum in the interaction between language and decision-making, and to understand how compensatory mechanisms delay language deficits. I used brain structure analysis associated to models unravelling the cognitive processes underlying language and decision-making.
