Sleep targets highly connected global and local nodes to aid consolidation of learned graph networks

• Verfasst von: Feld, Gordon Benedikt [VerfasserIn]
• Verfasst von: Bernard, M. [VerfasserIn]
• Verfasst von: Rawson, A. B. [VerfasserIn]
• Verfasst von: Spiers, Hugo J. [VerfasserIn]
• Titel: Sleep targets highly connected global and local nodes to aid consolidation of learned graph networks
• Verf.angabe: G.B. Feld, M. Bernard, A.B. Rawson & H.J. Spiers
• E-Jahr: 2022
• Jahr: 05 September 2022
• Umfang: 15 S.
• Fussnoten: Gesehen am 27.10.2022
• Titel Quelle: Enthalten in: Scientific reports
• Ort Quelle: [London] : Macmillan Publishers Limited, part of Springer Nature, 2011
• Jahr Quelle: 2022
• Band/Heft Quelle: 12(2022), Artikel-ID 15086, Seite 1-15
• ISSN Quelle: 2045-2322
• DOI: doi:10.1038/s41598-022-17747-2
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Human behaviour
• Sach-SW: Sleep
• K10plus-PPN: 1820224511

Abstract

Much of our long-term knowledge is organised in complex networks. Sleep is thought to be critical for abstracting knowledge and enhancing important item memory for long-term retention. Thus, sleep should aid the development of memory for networks and the abstraction of their structure for efficient storage. However, this remains unknown because past sleep studies have focused on discrete items. Here we explored the impact of sleep (night-sleep/day-wake within-subject paradigm with 25 male participants) on memory for graph-networks where some items were important due to dense local connections (degree centrality) or, independently, important due to greater global connections (closeness/betweenness centrality). A network of 27 planets (nodes) sparsely interconnected by 36 teleporters (edges) was learned via discrete associations without explicit indication of any network structure. Despite equivalent exposure to all connections in the network, we found that memory for the links between items with high local connectivity or high global connectivity were better retained after sleep. These results highlight that sleep has the capacity for strengthening both global and local structure from the world and abstracting over multiple experiences to efficiently form internal networks of knowledge.