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The Anatomy of the Mesolimbic Reward System: A Link between Personality and the Placebo Analgesic Response

2009· article· en· W2062372003 on OpenAlex

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

VenueJournal of Neuroscience · 2009
Typearticle
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsMcGill University
FundersCanadian Institutes of Health Research
KeywordsVentral striatumPsychologyNeuroscienceDopaminePrefrontal cortexNucleus accumbensReward systemAnticipation (artificial intelligence)DopaminergicInsulaPlaceboStriatumAnalgesicMedicinePsychiatry

Abstract

fetched live from OpenAlex

The anticipation of clinical benefit, a crucial component of placebo analgesia, has been suggested to be a special case of reward anticipation. Since reward processing is closely linked to the ventral striatum and the neurotransmitter dopamine, we examined the relationships between brain gray matter, placebo analgesic response, and personality traits associated with dopaminergic neurotransmission. We report that dopamine-related traits predict a substantial portion of the pain relief an individual gains from a sham treatment. Voxel-based morphometry of magnetic resonance images shows that the magnitude of placebo analgesia is related to gray matter density (GMD) in several brain regions, including the ventral striatum, insula, and prefrontal cortex. Similarly, GMD in ventral striatum and prefrontal cortex is related to dopamine-related personality traits. Our findings highlight the relationship between placebo and reward and potentially offer ways of identifying subjects who are likely to show large placebo analgesic responses.

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)0.017
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.914
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
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 head0.028
GPT teacher head0.294
Teacher spread0.266 · 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