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Group leader: Alexandre Pouget

Group name: Laboratory of cognitive computational neuroscience

Affiliation: Medical Sciences

Research activities:

image The goal of our research is to uncover general principles of representation and computation in neural circuits. Most computations of interest, such as recognizing an object or making a decision, are performed in the presence of high uncertainty. Recent behavioral work in humans and animals has shown that the nervous system handles this uncertainty near optimally, which is to say that the brain represents probability distributions over variables of interest and combine these distributions according to the laws of statistical inference. Our current work focuses on understanding how these inferences are performed at the neuronal level using a type of neural code known as population code. We apply our theory to a variety of domains, including decision making, multisensory integration, number representation, early visual processing and perceptual learning.

Group website: http://www.bcs.rochester.edu/people/alex/

Selected Publications:

  • Bejjanki, V.R., Lu, Z.L., Beck, J.M., and Pouget, A. Perceptual learning as improved probabilistic inference in early sensory areas. Nature Neuroscience.14(5):642-8. 2011.
  • Ma, W..J., Navalpakkam, V., Beck, J., van den Berg, R. and Pouget, A. Behavior and neural basis of near-optimal visual search. Nature Neuroscience. 14(6):783-90. 2011.
  • Fetsch, C.R., Pouget, A., DeAngelis, A.G.C. and Angelaki, D.E. Neural correlates of reliability-based cue weighting during multisensory integration. Nature Neuroscience. 15(1):146-54.818. 2012.

Contact:
University Medical Center
Département des neurosciences fondamentales
Email: Alexandre (dot) Pouget (at) unige (dot) ch