We study the problemof statisticallycorrect inference in networks whose basic representations are population codes. Population codes are ubiquitous in the brain, and involve the s...
We present a general encoding-decoding framework for interpreting the activity of a population of units. A standard population code interpretation method, the Poisson model, start...
As animals interact with their environments, they must constantly update estimates about their states. Bayesian models combine prior probabilities, a dynamical model and sensory e...
Richard S. Zemel, Quentin J. M. Huys, Rama Nataraj...
Probabilistic mixture models are used for a broad range of data analysis tasks such as clustering, classification, predictive modeling, etc. Due to their inherent probabilistic na...
Sensory systems often use groups of redundant neurons to represent stimulus information both during transduction and population coding of features. This redundancy makes the syste...