Target spike patterns enable efficient and biologically plausible learning for complex temporal tasks.
Recurrent spiking neural networks (RSNN) in the brain learn to perform a wide range of perceptual, cognitive and motor tasks very efficiently in terms of energy consumption and their training requires very few examples. This motivates the search for biologically inspired learning rules for RSNNs, ai...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2021-01-01
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Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0247014 |