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PLoS Comput Biol ; 14(9): e1006435, 2018 09.
Article in English | MEDLINE | ID: mdl-30222735

ABSTRACT

The capacity to learn abstract concepts such as 'sameness' and 'difference' is considered a higher-order cognitive function, typically thought to be dependent on top-down neocortical processing. It is therefore surprising that honey bees apparantly have this capacity. Here we report a model of the structures of the honey bee brain that can learn sameness and difference, as well as a range of complex and simple associative learning tasks. Our model is constrained by the known connections and properties of the mushroom body, including the protocerebral tract, and provides a good fit to the learning rates and performances of real bees in all tasks, including learning sameness and difference. The model proposes a novel mechanism for learning the abstract concepts of 'sameness' and 'difference' that is compatible with the insect brain, and is not dependent on top-down or executive control processing.


Subject(s)
Bees/physiology , Brain/physiology , Cognition , Mushroom Bodies/physiology , Neural Networks, Computer , Animals , Behavior, Animal , Computer Simulation , Learning , Machine Learning , Models, Neurological , Odorants , Probability , Software
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