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Record W4313328883 · doi:10.3390/brainsci13010060

Water Drinking Behavior Associated with Aversive Arousal in Rats: An Integrative Approach

2022· review· en· W4313328883 on OpenAlexaff
Stefan M. Brudzyński

Bibliographic record

VenueBrain Sciences · 2022
Typereview
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsBrock University
Fundersnot available
KeywordsCarbacholThirstPolydipsiaPsychologyCholinergicNeuroscienceArousalAnxietyAversive StimulusReticular activating systemLimbic systemStimulationEndocrinologyMedicineCentral nervous systemPsychiatryReticular formation

Abstract

fetched live from OpenAlex

Cholinergic muscarinic stimulation of vast areas of the limbic brain induced a well-documented polydipsia in laboratory rats. This excessive water-drinking behavior has not received any convincing biological and physiological interpretation for the last 50 years. This review offers such an interpretation and suggests that cholinergically induced drinking response, mostly by carbachol, is associated with activation of the ascending mesolimbic cholinergic system that serves for initiation of emotional aversive arousal of the organism. The ascending cholinergic system originates from the laterodorsal tegmental nucleus, has a diffuse nature, and affects numerous subcortical limbic structures. It is proposed that the carbachol-induced drinking response is related to the state of anxiety and does not serve the regulation of thirst. Instead, the response is anxiety-induced polydipsia that might occur as a soothing procedure that decreases the aversiveness of the negative emotional state induced by carbachol. It is concluded that carbachol-induced water-drinking behavior is a rewarding process that contributes to alleviating the feeling of anxiety by bringing some relief from the cholinergically induced aversive state, and it is a homologue to anxiety-driven polydipsia in humans.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.203
GPT teacher head0.426
Teacher spread0.223 · 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 designNot applicable
Domainnot available
GenreReview

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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