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Ventromedial Frontal Lobe Damage Disrupts Value Maximization in Humans

2011· article· en· W2170288531 on OpenAlexafffund
Nathalie Camille, Cathryn A. Griffiths, Khoi Vo, Lesley K. Fellows, Joseph W. Kable

Bibliographic record

VenueJournal of Neuroscience · 2011
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersNational Institute on Drug AbuseNational Institutes of HealthCanadian Institutes of Health ResearchKillam Trusts
KeywordsVentromedial prefrontal cortexNeuroeconomicsPsychologyCognitive psychologyFrontal lobeMaximizationOrbitofrontal cortexValue (mathematics)Prefrontal cortexNeuroimagingIntertemporal choiceNeuroscienceUtility maximizationPreferenceSocial psychologyComputer scienceCognitionEconomicsMathematical economicsEconometricsMicroeconomics

Abstract

fetched live from OpenAlex

Recent work in neuroeconomics has shown that regions in orbitofrontal and medial prefrontal cortex encode the subjective value of different options during choice. However, these electrophysiological and neuroimaging studies cannot demonstrate whether such signals are necessary for value-maximizing choices. Here we used a paradigm developed in experimental economics to empirically measure and quantify violations of utility theory in humans with damage to the ventromedial frontal lobe (VMF). We show that people with such damage are more likely to make choices that violate the generalized axiom of revealed preference, which is the one necessary and sufficient condition for choices to be consistent with value maximization. These results demonstrate that the VMF plays a critical role in value-maximizing choice.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.132
GPT teacher head0.293
Teacher spread0.161 · 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 designObservational
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

Citations230
Published2011
Admission routes2
Has abstractyes

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