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Record W2170380292 · doi:10.1073/pnas.141218998

The affective component of pain in rodents: Direct evidence for a contribution of the anterior cingulate cortex

2001· article· en· W2170380292 on OpenAlexfundno aff
Joshua P. Johansen, Howard L. Fields, Barton H. Manning

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2001
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsnot available
FundersNational Institute of Neurological Disorders and StrokeMedical Research CouncilNational Institutes of HealthMedical Research Council CanadaLife Sciences Research Foundation
KeywordsLickingNociceptionAnterior cingulate cortexNeuroscienceNociceptorStimulationCingulate cortexStimulus (psychology)PsychologyMedicineCentral nervous systemCognitionCognitive psychologyInternal medicineReceptor

Abstract

fetched live from OpenAlex

Numerous human and animal studies indirectly implicate neurons in the anterior cingulate cortex (ACC) in the encoding of the affective consequences of nociceptor stimulation. No causal evidence, however, has been put forth linking the ACC specifically to this function. Using a rodent pain assay that combines the hind-paw formalin model with the place-conditioning paradigm, we measured a learned behavior that directly reflects the affective component of pain in the rat (formalin-induced conditioned place avoidance) concomitantly with "acute" formalin-induced nociceptive behaviors (paw lifting, licking, and flinching) that reflect the intensity and localization of the nociceptive stimulus. Destruction of neurons originating from the rostral, but not caudal, ACC reduced formalin-induced conditioned place avoidance without reducing acute pain-related behaviors. These results provide evidence indicating that neurons in the ACC are necessary for the "aversiveness" of nociceptor stimulation.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

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 studies0.0000.001
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 head0.045
GPT teacher head0.349
Teacher spread0.304 · 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 designBench or experimental
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

Citations665
Published2001
Admission routes1
Has abstractyes

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