Most computations performed by the brain are subject to large amount of uncertainty because sensory inputs are noisy and ambiguous. As Laplace and Hemlholtz have pointed out over the last two centuries, the best way to compute in the presence of uncertainty is to adopt a probabilistic approach, that is, to represent knowledge in the form of probability distributions and to perform probabilistic computations. Several hypotheses have emerged recently regarding the neural implementations of these probabilistic inferences. I will review in particular one such hypothesis, based on the notion of probabilistic population codes, which shows how neurons perform probabilistic inference with simple biologically plausible linear and nonlinear neural circuits. We are applying this approach to a wide array of seemingly different behaviors such as decision making, visual search, simple arithmetic, perceptual learning, multisensory integration and olfactory processing to name a few. Interestingly, the mechanisms involved are so simple that they might also be used in insects, suggesting that probabilistic inference provides a general framework to understand neural computation in all species.

Carnegie Mellon University will award the fourth annual Andrew Carnegie Prize in Mind and Brain Sciences to Alexandre Pouget, from the University of Geneva.   

Alex Pouget is currently Professor in the Department of Basic Neuroscience at the University of Geneva, where he leads the computational cognitive neuroscience laboratory. His research focuses on general theories of representation and computation in neural circuits with a strong emphasis on neural theories of probabilistic inference.  This approach is built on the notion that knowledge in the brain takes the form of probability distributions and new knowledge is acquired via probabilistic inference. This allows robust computations in the presence of uncertainty, a situation that arises in almost all real-life computations. He is currently applying this framework to a wide range of topics including olfactory processing, spatial representations, sensory motor transformations, multisensory integration, perceptual learning, attentional control, decision making, causal reasoning and simple arithmetic. Dr. Pouget has two secondary affiliations.  He is Professor in the Department of Brain and Cognitive Sciences at the University of Rochester and is also an honorary faculty member at the Gatsby Computational Neuroscience Unit in London.

The prize, given by the Center for the Neural Basis of Cognition (CNBC) and funded by the Carnegie Corporation of New York as part of its centennial celebration, recognizes trailblazers in the mind and brain sciences whose research has helped advance the field and its applications.  

Reception to follow.