General differential Hebbian learning: Capturing temporal relations between events in neural networks and the brain.
Learning in biologically relevant neural-network models usually relies on Hebb learning rules. The typical implementations of these rules change the synaptic strength on the basis of the co-occurrence of the neural events taking place at a certain time in the pre- and post-synaptic neurons. Differen...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2018-08-01
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| Series: | PLoS Computational Biology |
| Online Access: | http://europepmc.org/articles/PMC6130884?pdf=render |