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Record W2134320198 · doi:10.1093/cercor/bhs297

Selective Involvement by the Medial Orbitofrontal Cortex in Biasing Risky, But Not Impulsive, Choice

2012· article· en· W2134320198 on OpenAlex
Colin M. Stopper, E. B. Green, Stan Floresco

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCerebral Cortex · 2012
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsOrbitofrontal cortexDelay discountingPsychologyDiscountingTemporal discountingNeuroscienceProbabilistic logicTask (project management)Prefrontal cortexOddsCognitive psychologyImpulsivityCognitionMedicineDevelopmental psychologyComputer scienceEconomicsInternal medicine

Abstract

fetched live from OpenAlex

Separate regions of the orbitofrontal cortex (OFC) have been implicated in mediating different aspects of cost-benefit decision-making in humans and animals. Anatomical and functional imaging studies indicate that the medial (mOFC) and lateral OFC may subserve dissociable functions related to reward and decision-making processes, yet the majority of studies in rodents have focused on the lateral OFC. The present study investigated the contribution of the rat mOFC to risk and delay-based decision-making, assessed with probabilistic and delay-discounting tasks. In well-trained rats, reversible inactivation of the mOFC increase a risky choice on the probabilistic discounting task, irrespective of whether the odds of obtaining a larger/risky reward decreased (100-12.5%) or increased (12.5-100%) over the course of a session. The increase in risky choice was associated with enhanced win-stay behavior, wherein rats showed an increased tendency to choose the risky option after being rewarded for the risky choice on a preceding trial. In contrast, mOFC inactivation did not alter delay discounting. These findings suggest that the mOFC plays a selective role in decisions involving reward uncertainty, mitigating the impact that larger, probabilistic rewards exert on subsequent choice behavior. This function may promote the exploration of novel options when reward contingencies change.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.508
Threshold uncertainty score0.851

Codex and Gemma teacher scores by category

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.086
GPT teacher head0.341
Teacher spread0.256 · 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