Burst-dependent synaptic plasticity can coordinate learning in hierarchical circuits.
Journal
Nature neuroscience
ISSN: 1546-1726
Titre abrégé: Nat Neurosci
Pays: United States
ID NLM: 9809671
Informations de publication
Date de publication:
07 2021
07 2021
Historique:
received:
30
03
2020
accepted:
15
04
2021
pubmed:
15
5
2021
medline:
18
9
2021
entrez:
14
5
2021
Statut:
ppublish
Résumé
Synaptic plasticity is believed to be a key physiological mechanism for learning. It is well established that it depends on pre- and postsynaptic activity. However, models that rely solely on pre- and postsynaptic activity for synaptic changes have, so far, not been able to account for learning complex tasks that demand credit assignment in hierarchical networks. Here we show that if synaptic plasticity is regulated by high-frequency bursts of spikes, then pyramidal neurons higher in a hierarchical circuit can coordinate the plasticity of lower-level connections. Using simulations and mathematical analyses, we demonstrate that, when paired with short-term synaptic dynamics, regenerative activity in the apical dendrites and synaptic plasticity in feedback pathways, a burst-dependent learning rule can solve challenging tasks that require deep network architectures. Our results demonstrate that well-known properties of dendrites, synapses and synaptic plasticity are sufficient to enable sophisticated learning in hierarchical circuits.
Identifiants
pubmed: 33986551
doi: 10.1038/s41593-021-00857-x
pii: 10.1038/s41593-021-00857-x
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1010-1019Subventions
Organisme : CIHR
ID : RN383647-418955
Pays : Canada
Commentaires et corrections
Type : CommentIn
Type : ErratumIn
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