Sleep Origins: Restful Jellyfish Are Sleeping Jellyfish

Lesku, John A.; Ly, Linh M.T.

doi:10.1016/j.cub.2017.08.024

Cited by 16 publications

(6 citation statements)

References 20 publications

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“…Sleep is one of the most critical physiological processes for all species with a nervous system, ranging from jellyfish and flatworms (Lesku and Ly, 2017; Omond et al, 2017) to complex mammals. In humans, sleep is essential for optimal cognitive performance, physiological processes, emotional regulation, and quality of life, and research consistently demonstrates that biological factors leading to disrupted sleep have dramatic effects on health and well-being (Spiegel et al, 2005; Sabanayagam and Shankar, 2010; Watanabe et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Validation of ‘Somnivore’, a Machine Learning Algorithm for Automated Scoring and Analysis of Polysomnography Data

Allocca

Martelli

et al. 2019

Front. Neurosci.

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Manual scoring of polysomnography data is labor-intensive and time-consuming, and most existing software does not account for subjective differences and user variability. Therefore, we evaluated a supervised machine learning algorithm, SomnivoreTM, for automated wake–sleep stage classification. We designed an algorithm that extracts features from various input channels, following a brief session of manual scoring, and provides automated wake-sleep stage classification for each recording. For algorithm validation, polysomnography data was obtained from independent laboratories, and include normal, cognitively-impaired, and alcohol-treated human subjects (total n = 52), narcoleptic mice and drug-treated rats (total n = 56), and pigeons (n = 5). Training and testing sets for validation were previously scored manually by 1–2 trained sleep technologists from each laboratory. F-measure was used to assess precision and sensitivity for statistical analysis of classifier output and human scorer agreement. The algorithm gave high concordance with manual visual scoring across all human data (wake 0.91 ± 0.01; N1 0.57 ± 0.01; N2 0.81 ± 0.01; N3 0.86 ± 0.01; REM 0.87 ± 0.01), which was comparable to manual inter-scorer agreement on all stages. Similarly, high concordance was observed across all rodent (wake 0.95 ± 0.01; NREM 0.94 ± 0.01; REM 0.91 ± 0.01) and pigeon (wake 0.96 ± 0.006; NREM 0.97 ± 0.01; REM 0.86 ± 0.02) data. Effects of classifier learning from single signal inputs, simple stage reclassification, automated removal of transition epochs, and training set size were also examined. In summary, we have developed a polysomnography analysis program for automated sleep-stage classification of data from diverse species. Somnivore enables flexible, accurate, and high-throughput analysis of experimental and clinical sleep studies.

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Section: Introductionmentioning

confidence: 99%

Validation of ‘Somnivore’, a Machine Learning Algorithm for Automated Scoring and Analysis of Polysomnography Data

Allocca

Martelli

et al. 2019

Front. Neurosci.

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“…The sleep-wake cycle has been characterized in chordate (mammals, birds and Squamata), Arthropoda (flies, bees, scorpions) cnidarian (jellyfish) and nematodes species (C. elegans [9][10][11]). Based in electroencephalographic traces, three states of vigilance have been identified in most of the studied animals, including mammals (Fig.…”

Section: Sleep Stages and Sleep Architecturementioning

confidence: 99%

Assessing the Management of Excessive Daytime Sleepiness by Napping Benefits

et al. 2020

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Your article is protected by copyright and all rights are held exclusively by Springer Nature Singapore Pte Ltd.. This e-offprint is for personal use only and shall not be selfarchived in electronic repositories. If you wish to self-archive your article, please use the accepted manuscript version for posting on your own website. You may further deposit the accepted manuscript version in any repository, provided it is only made publicly available 12 months after official publication or later and provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at link.springer.com".

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“…From a neurological perspective, it is a complex and tightly regulated process that shows remarkable evolutionary conservation ( Allada and Siegel, 2008 ). Despite the enormous evolutionary distances and physiological differences among organisms studied, commonalities in sleep behaviour have been found across taxa, from invertebrates – such as jellyfish ( Lesku and Ly, 2017 ; Nath et al, 2017 ), hydra ( Kanaya et al, 2020 ), flatworms ( Omond et al, 2017 ) and Drosophila ( Hendricks et al, 2000 ; Shaw et al, 2000 ) – to vertebrates, including fish ( Lesku et al, 2019 ), amphibians ( Libourel and Herrel, 2016 ), reptiles ( Shein-Idelson et al, 2016 ), birds and mammals ( Lesku et al, 2019 ). The near-ubiquitous occurrence of sleep behaviours, even in species without brains (e.g.…”

Section: Introductionmentioning

confidence: 99%

The interplay between sleep and ecophysiology, behaviour and responses to environmental change in fish

Norman,

Munson,

Cortese

et al. 2024

Journal of Experimental Biology

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Evidence of behavioural sleep has been observed in every animal species studied to date, but current knowledge of the behaviour, neurophysiology and ecophysiology associated with sleep is concentrated on mammals and birds. Fish are a hugely diverse group that can offer novel insights into a variety of sleep-related behaviours across environments, but the ecophysiological relevance of sleep in fish has been largely overlooked. Here, we systematically reviewed the literature to assess the current breadth of knowledge on fish sleep, and surveyed the diverse physiological effects and behaviours associated with sleep. We also discuss possible ways in which unstudied external factors may alter sleep behaviours. For example, predation risk may alter sleep patterns, as has been shown in mammalian, avian and reptilian species. Other environmental factors – such as water temperature and oxygen availability – have the potential to alter sleep patterns in fish differently than for terrestrial endotherms. Understanding the ecological influences on sleep in fish is vital, as sleep deprivation has the potential to affect waking behaviour and fitness owing to cognitive and physiological impairments, possibly affecting ecological phenomena and sensitivity to environmental stressors in ways that have not been considered.

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Sleep Origins: Restful Jellyfish Are Sleeping Jellyfish

Abstract: What is the 'simplest' animal that sleeps? When did sleep first evolve? Do all animals sleep? Tantalizing hints to answers come from new research showing that jellyfish, one of the earliest evolving groups of animals, have a sleep-like restful state.

Cited by 16 publications

References 20 publications

Validation of ‘Somnivore’, a Machine Learning Algorithm for Automated Scoring and Analysis of Polysomnography Data

Validation of ‘Somnivore’, a Machine Learning Algorithm for Automated Scoring and Analysis of Polysomnography Data

Assessing the Management of Excessive Daytime Sleepiness by Napping Benefits

The interplay between sleep and ecophysiology, behaviour and responses to environmental change in fish

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