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dc.contributor.authorKozachkov, Leo
dc.contributor.authorTauber, John
dc.contributor.authorLundqvist, Mikael
dc.contributor.authorBrincat, Scott L
dc.contributor.authorSlotine, Jean-Jacques
dc.contributor.authorMiller, Earl K
dc.date.accessioned2023-01-18T14:23:59Z
dc.date.available2023-01-18T14:23:59Z
dc.date.issued2022-12-27
dc.identifier.urihttps://hdl.handle.net/1721.1/147183
dc.description.abstract<jats:p>Working memory has long been thought to arise from sustained spiking/attractor dynamics. However, recent work has suggested that short-term synaptic plasticity (STSP) may help maintain attractor states over gaps in time with little or no spiking. To determine if STSP endows additional functional advantages, we trained artificial recurrent neural networks (RNNs) with and without STSP to perform an object working memory task. We found that RNNs with and without STSP were able to maintain memories despite distractors presented in the middle of the memory delay. However, RNNs with STSP showed activity that was similar to that seen in the cortex of a non-human primate (NHP) performing the same task. By contrast, RNNs without STSP showed activity that was less brain-like. Further, RNNs with STSP were more robust to network degradation than RNNs without STSP. These results show that STSP can not only help maintain working memories, it also makes neural networks more robust and brain-like.</jats:p>en_US
dc.language.isoen
dc.publisherPublic Library of Science (PLoS)en_US
dc.relation.isversionof10.1371/journal.pcbi.1010776en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourcePLoSen_US
dc.titleRobust and brain-like working memory through short-term synaptic plasticityen_US
dc.typeArticleen_US
dc.identifier.citationKozachkov, Leo, Tauber, John, Lundqvist, Mikael, Brincat, Scott L, Slotine, Jean-Jacques et al. 2022. "Robust and brain-like working memory through short-term synaptic plasticity." PLOS Computational Biology, 18 (12).
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciencesen_US
dc.relation.journalPLOS Computational Biologyen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2023-01-18T14:12:16Z
dspace.orderedauthorsKozachkov, L; Tauber, J; Lundqvist, M; Brincat, SL; Slotine, J-J; Miller, EKen_US
dspace.date.submission2023-01-18T14:12:18Z
mit.journal.volume18en_US
mit.journal.issue12en_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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