
About
Alexandre Pouget is a Full Professor in the Department of Basic Neuroscience at the University of Geneva, where he leads the Computational Cognitive Neuroscience Laboratory.
His research establishes that the brain represents knowledge as probability distributions and performs computations via probabilistic inference, enabling robust neural processing under uncertainty. This foundational framework applies across diverse domains including olfactory processing, spatial representations, sensory-motor transformations, multisensory integration, perceptual learning, attention control, decision making, causal reasoning, and simple arithmetic. The approach reveals how biologically plausible neural circuits implement probabilistic population codes for efficient computation.
Major recognition includes:
- Andrew Carnegie Prize in Mind and Brain Sciences (2016) from Carnegie Mellon University
His laboratory develops theoretical models demonstrating how probabilistic inference mechanisms may operate universally across species, including insects, suggesting a fundamental principle of neural computation. Current work explores applications to visual search, arithmetic processing, and causal reasoning through experimentally testable neural circuit implementations.
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