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About the lab

Why do we do what we do? We are largely unaware of the mechanisms that motivate our behavior. Motivation can be construed as a set of processes that identify goals and translate them into action. A goal can be reduced to an expected reward, i.e. an anticipated situation with a positive value: earning money, winning awards, being loved, etc. Uncovering how the brain assigns subjective values to potential situations is central to answer our main research questions, since these values determine both the orientation and the intensity of the behavior. During the past decade, neuroscience has made significant progress in deciphering the neural code for subjective vale. Novel important questions can now be addressed:

a) how various dimensions are integrated to construct subjective values (benefits, costs, risks, physiological state, social context …)

b) how these neural values determine behavioral outputs (effort production, decision making, likeability judgment …) and

c) how these neural values are updated through associative learning and social interaction.

To answer these questions, we combine five approaches:

1) human cognitive neuroscience, which is central as we ultimately wish to understand ourselves, as well as human pathological conditions where motivation is either deficient (apathy) or difficult to control (impulsivity),

2) primate neurophysiology, which is essential to describe information processing at the single-neuron level and to derive causality by observing behavioral consequences of brain manipulations,

3) computational modeling, which is mandatory to quantitatively link the different description levels (from single cells to brain-scale activities to motor outputs).

4) applications in neurology of all of the above,

5) applications in psychiatry of all of the above.

Our long-term objective is to build a neuro-computational model that would account for the psycho-physiological determinants of human behavior. Such a model would allow predicting the behavioral consequences of changes in the inputs (new information, different context) or the physiological state (metabolism, drug intake). Conversely, it would allow inferring states of neural activity or connectivity from the observed behavior. Such a model would have far-reaching applications in many domains, which we have started to develop. In the clinics, it would help profiling the patients and therefore help personalize the design of both diagnostic and therapeutic tools for various motivational dysfunctions manifested in neuropsychiatric disorders. In management, it would help setting up better work conditions so as to increase efficiency while avoiding burnout. In economics, it would help preventing a number of irrational behaviors that arise from the heuristics developed by the primate brain through natural selection, which are often maladaptive to the modern world.