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Discharge of Identified Orexin/Hypocretin Neurons across the Sleep-Waking Cycle

2005· article· en· W2100743305 on OpenAlexafffund
Maan‐Gee Lee, Oum Kaltoum Hassani, Barbara E. Jones

Bibliographic record

VenueJournal of Neuroscience · 2005
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersNational Institute of Mental HealthCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsOrexinNarcolepsyWakefulnessArousalNeuroscienceMuscle toneOrexin receptorSleep (system call)PsychologyNeuroscience of sleepCataplexyRapid eye movement sleepMedicineNeurologyInternal medicineEye movementNeuropeptideReceptorElectroencephalography

Abstract

fetched live from OpenAlex

Although maintained by multiple arousal systems, wakefulness falters if orexin (hypocretin), orexin receptors, or orexin neurons are deficient; narcolepsy results with hypersomnolence or sudden onset of rapid eye movement sleep [or paradoxical sleep (PS)] and loss of muscle tonus. To learn how orexin neurons maintain wakefulness, we recorded neurons in head-fixed rats across the sleep-waking cycle and then labeled them with Neurobiotin to identify them by immunohistochemistry. We show that identified orexin neurons discharge during active waking, when postural muscle tone is high in association with movement, decrease discharge during quiet waking in absence of movement, and virtually cease firing during sleep, when postural muscle tone is low or absent. During PS, they remain relatively silent in association with postural muscle atonia and most often despite phasic muscular twitches. They increase firing before the end of PS and thereby herald by several seconds the return of waking and muscle tone. The orexin neurons would thus stimulate arousal, while antagonizing sleep and muscle atonia.

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 score0.001
Threshold uncertainty score0.003

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 head0.060
GPT teacher head0.355
Teacher spread0.294 · 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

Citations868
Published2005
Admission routes2
Has abstractyes

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