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Record W3202543093 · doi:10.1038/s41586-021-03954-w

Sensory processing during sleep in Drosophila melanogaster

2021· article· en· W3202543093 on OpenAlexaff
Alice S. French, Quentin Geissmann, Esteban J. Beckwith, Giorgio F. Gilestro

Bibliographic record

VenueNature · 2021
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsUniversity of British Columbia
FundersBiotechnology and Biological Sciences Research CouncilWellcome Trust
KeywordsSensory systemStimulus (psychology)NeuroscienceSalience (neuroscience)Drosophila melanogasterConsciousnessPsychologyArousalCognitive psychologyBiology

Abstract

fetched live from OpenAlex

During sleep, most animal species enter a state of reduced consciousness characterized by a marked sensory disconnect. Yet some processing of the external world must remain intact, given that a sleeping animal can be awoken by intense stimuli (for example, a loud noise or a bright light) or by soft but qualitatively salient stimuli (for example, the sound of a baby cooing or hearing one’s own name1–3). How does a sleeping brain retain the ability to process the quality of sensory information? Here we present a paradigm to study the functional underpinnings of sensory discrimination during sleep in Drosophila melanogaster. We show that sleeping vinegar flies, like humans, discern the quality of sensory stimuli and are more likely to wake up in response to salient stimuli. We also show that the salience of a stimulus during sleep can be modulated by internal states. We offer a prototypical blueprint detailing a circuit involved in this process and its modulation as evidence that the system can be used to explore the cellular underpinnings of how a sleeping brain experiences the world. The authors develop a paradigm to study sensory discrimination during sleep in Drosophila melanogaster.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.300
Teacher spread0.279 · 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

Citations62
Published2021
Admission routes1
Has abstractyes

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