Abstract concept learning in a simple neural network inspired by the insect brain

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 rep...

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Veröffentlicht in:PLoS computational biology 2018-09, Vol.14 (9), p.e1006435-e1006435
Hauptverfasser: Cope, Alex J, Vasilaki, Eleni, Minors, Dorian, Sabo, Chelsea, Marshall, James A R, Barron, Andrew B
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Sprache:eng
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Zusammenfassung: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.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1006435