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Record W2042920810 · doi:10.1037/a0017617

The role of the medial prefrontal cortex in the play fighting of rats.

2009· article· en· W2042920810 on OpenAlexafffund
Heather C. Bell, David R. McCaffrey, Margaret L. Forgie, Bryan Kolb, Sergio M. Pellis

Bibliographic record

VenueBehavioral Neuroscience · 2009
Typearticle
Languageen
FieldPsychology
TopicNeuroendocrine regulation and behavior
Canadian institutionsUniversity of Lethbridge
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Heritage Foundation for Medical Research
KeywordsPrefrontal cortexPsychologyOrbitofrontal cortexNeuroscienceDissociation (chemistry)CognitionChemistry

Abstract

fetched live from OpenAlex

Although decorticated rats are able to engage in play, their play is abnormal in three ways. First, decorticates do not display the normal, age-related shifts in defensive strategies during development. Second, decorticates do not modify their defensive tactics in response to the social identity of their partners. Third, decorticates display a global shift in defensive tactics from more complex to less complex strategies. It has been shown that lesions of the motor cortex (MC) selectively produce the abnormal developmental effects on play, and that lesions of the orbitofrontal cortex (OFC) selectively produce the deficits in behavioral discrimination between social partners. In the current set of experiments, we demonstrate that lesions of the medial prefrontal cortex (mPFC) produce the shift from more complex to less complex defensive tactics, while leaving intact the age-related and partner-related modulation of defensive strategies. Thus, we have evidence for a triple dissociation of function between the MC, the OFC, and the mPFC with respect to social play behavior.

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 score0.002
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 head0.032
GPT teacher head0.343
Teacher spread0.312 · 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

Citations118
Published2009
Admission routes2
Has abstractyes

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