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Inverse association between dopaminergic neurotransmission and Iowa Gambling Task performance in pathological gamblers and healthy controls

2010· article· en· W1536413929 on OpenAlexaff
Jakob Linnet, Arne Møller, Ericka Peterson, Albert Gjedde, Doris J. Doudet

Bibliographic record

VenueScandinavian Journal of Psychology · 2010
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPsychologyAssociation (psychology)PathologicalDopaminergicNeurotransmissionNeuroscienceTask forceTask (project management)Gambling disorderMedicineDopamineInternal medicineAddictionReceptorPsychotherapist

Abstract

fetched live from OpenAlex

The dopamine system is believed to affect gambling behavior in pathological gambling. Particularly, dopamine release in the ventral striatum appears to affect decision-making in the disorder. This study investigated dopamine release in the ventral striatum in relation to gambling performance on the Iowa Gambling Task (IGT) in 16 Pathological Gamblers (PG) and 14 Healthy Controls (HC). We used Positron Emission Tomography (PET) to measure the binding potential of [(11)C] raclopride to dopamine D2/3 receptors during a baseline and gambling condition. We hypothesized that decreased raclopride binding potentials in the ventral striatum during gambling (indicating dopamine release) would be associated with higher IGT performance in Healthy Controls, but lower IGT performance in Pathological Gamblers. The results showed that Pathological Gamblers with dopamine release in the ventral striatum had significantly lower IGT performance than Healthy Controls. Furthermore, dopamine release was associated with significantly higher IGT performance in Healthy Controls and significantly lower IGT performance in Pathological Gamblers. The results suggest that dopamine release is involved both in adaptive and maladaptive decision-making. These findings may contribute to a better understanding of dopaminergic dysfunctions in pathological gambling and substance related addictions.

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 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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.683

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.068
GPT teacher head0.388
Teacher spread0.320 · 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 teacher head, 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

Citations86
Published2010
Admission routes1
Has abstractyes

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