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Interrogating structural plasticity among synaptic engrams

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dc.contributor.authorChoi, Dong Il-
dc.contributor.authorKaang, Bong-Kiun-
dc.date.accessioned2022-09-30T06:04:54Z-
dc.date.available2022-09-30T06:04:54Z-
dc.date.created2022-06-29-
dc.date.issued2022-08-
dc.identifier.citationCurrent Opinion in Neurobiology, Vol.75, p. 102552-
dc.identifier.issn0959-4388-
dc.identifier.urihttps://hdl.handle.net/10371/185145-
dc.description.abstractOur daily experiences and learnings are stored in the form of memories. These experiences trigger synaptic plasticity and persistent structural and functional changes in neuronal synapses. Recently, cellular studies of memory storage and engrams have emerged over the last decade. Engram cells reflect interconnected neurons via modified synapses. However, we were unable to observe the structural changes arising from synaptic plasticity in the past, because it was not possible to distinguish the synapses between engram cells. To overcome this barrier, dual-eGRASP (enhanced green fluorescent protein reconstitution across synaptic partners) technology can label specific synapses among multiple synaptic ensembles. Selective labeling of engram synapses elucidated their role by observing the structural changes in synapses according to the memory state. Dual-eGRASP extends cellular level engram studies to introduce the era of synaptic level studies. Here, we review this concept and possible applications of the dualeGRASP, including recent studies that provided visual evidence of structural plasticity at the engram synapse.-
dc.language영어-
dc.publisherElsevier BV-
dc.titleInterrogating structural plasticity among synaptic engrams-
dc.typeArticle-
dc.identifier.doi10.1016/j.conb.2022.102552-
dc.citation.journaltitleCurrent Opinion in Neurobiology-
dc.identifier.wosid000806953300005-
dc.identifier.scopusid2-s2.0-85130399960-
dc.citation.startpage102552-
dc.citation.volume75-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorKaang, Bong-Kiun-
dc.type.docTypeArticle-
dc.description.journalClass1-
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