Stochastic consolidation of lifelong memory.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
30 07 2022
30 07 2022
Historique:
received:
07
02
2022
accepted:
11
07
2022
entrez:
30
7
2022
pubmed:
31
7
2022
medline:
3
8
2022
Statut:
epublish
Résumé
Humans have the remarkable ability to continually store new memories, while maintaining old memories for a lifetime. How the brain avoids catastrophic forgetting of memories due to interference between encoded memories is an open problem in computational neuroscience. Here we present a model for continual learning in a recurrent neural network combining Hebbian learning, synaptic decay and a novel memory consolidation mechanism: memories undergo stochastic rehearsals with rates proportional to the memory's basin of attraction, causing self-amplified consolidation. This mechanism gives rise to memory lifetimes that extend much longer than the synaptic decay time, and retrieval probability of memories that gracefully decays with their age. The number of retrievable memories is proportional to a power of the number of neurons. Perturbations to the circuit model cause temporally-graded retrograde and anterograde deficits, mimicking observed memory impairments following neurological trauma.
Identifiants
pubmed: 35907920
doi: 10.1038/s41598-022-16407-9
pii: 10.1038/s41598-022-16407-9
pmc: PMC9339009
doi:
Types de publication
Journal Article
Research Support, U.S. Gov't, Non-P.H.S.
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
13107Informations de copyright
© 2022. The Author(s).
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