Bee foraging in uncertain environments using predictive hebbian learning

Nature. 1995 Oct 26;377(6551):725-8. doi: 10.1038/377725a0.

Abstract

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.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Animals
  • Bees / physiology*
  • Computer Simulation
  • Environment
  • Feeding Behavior / physiology
  • Learning / physiology*
  • Models, Neurological*
  • Neurons / physiology
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