Probabilistic Interpretation of Population Codes

Part of Advances in Neural Information Processing Systems 9 (NIPS 1996)

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Richard Zemel, Peter Dayan, Alexandre Pouget


We present a theoretical framework for population codes which generalizes naturally to the important case where the population provides information about a whole probability distribution over an underlying quantity rather than just a single value. We use the framework to analyze two existing models, and to suggest and evaluate a third model for encoding such probability distributions.