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Record W6969324922 · doi:10.5683/sp3/pdkdw3

A Comparison of Brain-State Dynamics across Common Anesthetic Agents in Male Sprague-Dawley Rats

2022· dataset· en· W6969324922 on OpenAlexaff

Bibliographic record

VenueBorealis · 2022
Typedataset
Languageen
FieldSocial Sciences
TopicMigration, Identity, and Health
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAnestheticIsofluranePropofolNeurophysiologyChloral hydrateAnesthetic AgentElectrophysiologyForebrainBenzocaine

Abstract

fetched live from OpenAlex

Anesthesia is a powerful tool in neuroscientific research, especially in sleep research where it has the experimental advantage of allowing surgical interventions that are ethically problematic in natural sleep. Yet, while it is well documented that different anesthetic agents produce a variety of brain states, and consequently have differential effects on a multitude of neurophysiological factors, these outcomes vary based on dosages, the animal species used, and the pharmacological mechanisms specific to each anesthetic agent. Thus, our aim was to conduct a controlled comparison of spontaneous electrophysiological dynamics at a surgical plane of anesthesia under six common research anesthetics using a ubiquitous animal model, the Sprague-Dawley rat. From this direct comparison, we also evaluated which anesthetic agents may serve as pharmacological proxies for the electrophysiological features and dynamics of unconscious states such as sleep and coma. We found that at a surgical plane, pentobarbital, isoflurane and propofol all produced a continuous pattern of burst-suppression activity, which is a neurophysiological state characteristically observed during coma. In contrast, ketamine-xylazine produced synchronized, slow-oscillatory activity, similar to that observed during slow-wave sleep. Notably, both urethane and chloral hydrate produced the spontaneous, cyclical alternations between forebrain activation (REM-like) and deactivation (non-REM-like) that are similar to those observed during natural sleep. Thus, the choice of anesthesia, in conjunction with continuous brain state monitoring, are critical considerations in order to avoid brain-state confounds when conducting neurophysiological experiments.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.172
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.057
GPT teacher head0.413
Teacher spread0.356 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2022
Admission routes1
Has abstractyes

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