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Record W4392356362 · doi:10.1242/jeb.246582

Penguins prefer power naps

2024· article· en· W4392356362 on OpenAlexaff
Sarah J. Young

Bibliographic record

VenueJournal of Experimental Biology · 2024
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsPower (physics)Physics

Abstract

fetched live from OpenAlex

If you ask a student, parent or working professional whether they get enough sleep each night, many will laugh at the question. Sufficient rest may seem an impossible goal in the hustle and bustle of modern life, but what if you could achieve the prized 8 hours of sleep without ever sleeping at all? This is, of course, impossible for humans. However, busy penguins never seem to sleep. Chinstrap penguins nest as a colony and in every penguin pair, one parent stays home with their young while the other parent forages to feed the family. As any human parent knows, full-time childcare is tiring work, as is providing for the family. Factor on top of these the necessity for chinstrap penguins to be vigilant against predators and it is obvious that both nesting and foraging penguin parents will need a lot of rest. However, sleeping for hours would put them, and their chicks, at great risk. A new study shows that chinstrap penguins mitigate this trade-off by utilizing a strategy known as microsleeping.Paul-Antoine Libourel (Neuroscience Research Centre of Lyon, France) and colleagues from France, the Republic of Korea and Germany investigated how nesting chinstrap penguins are able to obtain enough rest without sleeping for extended periods of time. The researchers monitored the activity of nesting penguins by filming them and outfitting individuals with wearable motion sensors. The sensors tracked the animal's body posture and sleep stages to identify when the tired penguins nodded off, similar to a human fitness tracker. The research team was particularly interested in slow wave sleep picked up by the sensor, which indicates deep and restorative rest. The team also investigated how sleep quality compares between individuals nesting on the colony's border, who are more vulnerable to predators, and individuals in the center of the colony, who are protected from predation.Libourel and colleagues found that nesting chinstrap penguins attained an incredible total of ∼15 hours of slow wave sleep per day despite never appearing to take a nap. Astonishingly, these hours came from the accumulation of thousands of daily naps that lasted only 4 seconds. Not only that, but most of these naps were not really naps at all. Rather, the penguins were taking microsleeps, where they put one hemisphere of their brain to sleep and close only the associated eye, while concurrently the other hemisphere of the brain, and the other eye, remain wide awake. Both the right and left hemispheres of the brain received a luxurious 11–12 hours of sleep per day. Moreover, contrary to expectation, the team discovered that penguins on the edge of the colony enjoyed longer, deeper and less fragmented sleep than penguins at the center of the colony, suggesting that aggression from penguin peers is more stressful than the risk posed by predators.Microsleeping is an incredible testament to the strategies that animals can employ to balance their physiological and ecological needs. In the case of chinstrap penguins, taking microsleeps allows them to restore their physiological systems while remaining vigilant for threats from predators and peers. The success of the species suggests that, although fragmented, this sleep pattern provides the same large-scale restorative functions as uninterrupted sleep. However, further research is warranted into how the full restorative value of microsleeping compares to that of typical sleep.Although it has long been known that birds experience slow wave sleep in shorter bouts than mammals, Libourel and colleagues’ discovery that chinstrap penguins accumulate 15 hours of sleep daily over thousands of microsleeps that last only 4 seconds is unprecedented. If only human systems could operate this way and allow us to benefit from the many times we've nodded off during boring lectures.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.061
GPT teacher head0.383
Teacher spread0.322 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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