Bee Foraging in Uncertain Environments using Predictive Hebbian Learning

P Read Montague   Peter Dayan   Christophe Person   TJ Sejnowski
Nature, 377, 725-728.


Recent work has identified a neuron with widespread projections to odour processing regions of the honeybee brain whose activity represents the reward value of gustatory stimuli. We have constructed a model of bee foraging in uncertain environments based on this type of neuron and a predictive form of hebbian synaptic plasticity. The model uses visual input from a simulated three-dimensional world and accounts for a wide range of experiments on bee learning during foraging, including risk aversion. The predictive model shows how neuromodulatory influences can be used to bias actions and control synaptic plasticity in a way that goes beyond standard correlational mechanisms. Although several behavioural models of conditioning in bees have been proposed, this model is based on the neural substrate and was tested in a simulation of bee flight.

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