The DOI matches its Crossref record; 173 of the 173 references it cites were found in a registry or an index.
The cognitive cost of sleep lost
Open accessAbstract
A substantial body of literature supports the intuitive notion that a good night’s sleep can facilitate human cognitive performance the next day. Deficits in attention, learning & memory, emotional reactivity, and higher-order cognitive processes, such as executive function and decision making, have all been documented following sleep disruption in humans. Thus, whilst numerous clinical and experimental studies link human sleep disturbance to cognitive deficits, attempts to develop valid and reliable rodent models of these phenomena are fewer, and relatively more recent. This review focuses primarily on the cognitive impairments produced by sleep disruption in rodent models of several human patterns of sleep loss/sleep disturbance. Though not an exclusive list, this review will focus on four specific types of sleep disturbance: total sleep deprivation, experimental sleep fragmentation, selective REM sleep deprivation, and chronic sleep restriction. The use of rodent models can provide greater opportunities to understand the neurobiological changes underlying sleep loss induced cognitive impairments. Thus, this review concludes with a description of recent neurobiological findings concerning the neuroplastic changes and putative brain mechanisms that may underlie the cognitive deficits produced by sleep disturbances.
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Metadata
- Authors
- McCoy, J. G., & Strecker, R. E.
- Venue
- Neurobiology of Learning and Memory
- Publisher
- Elsevier BV
- Published
- 2011-11
- Volume
- 96
- Issue
- 4
- Pages
- 564-582
- ISSN
- 1074-7427 (ISSN-L)
- OpenAlex
- W2079933139
- Cited by
- 286
- References
- 173
- FWCI
- 10.25
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.