BEE FORAGING IN UNCERTAIN ENVIRONMENTS USING PREDICTIVE HEBBIAN LEARNING

RECENT work has identified a neuron with widespread projections to odo ur processing regions of the honeybee brain whose activity represents the reward value of gustatory stimuli(1,2). We have constructed a mode l of bee foraging in uncertain environments based on this type of neur on and a predictive form of hebbian synaptic plasticity. The model use s visual input from a simulated three-dimensional world and accounts f or a wide range of experiments on bee learning during foraging, includ ing risk aversion. The predictive model shows how neuromodulatory infl uences can be used to bias actions and control synaptic plasticity in a way that goes beyond standard correlational mechanisms. Although sev eral behavioural models of conditioning in bees have been proposed(3-7 ), this model is based on the neural substrate and was tested in a sim ulation of bee flight.