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Brain on Fire: Incentive Salience, Hedonic Hot Spots, Dopamine, Obesity, and Other Hunger Games

2017· review· en· W2618724069 on OpenAlexaff
Jameason D. Cameron, Jean‐Philippe Chaput, Anders Sjödin, Gary S. Goldfield

Bibliographic record

VenueAnnual Review of Nutrition · 2017
Typereview
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsDopamineSalience (neuroscience)ObesityPsychologyIncentiveNeuroscienceMedicineEndocrinologyEconomicsMicroeconomics

Abstract

fetched live from OpenAlex

This review examines human feeding behavior in light of psychological motivational theory and highlights the importance of midbrain dopamine (DA). Prospective evidence of both reward surfeit and reward deficit pathways to increased body weight are evaluated, and we argue that it is more complex than an either/or scenario when examining DA's role in reward sensitivity, eating, and obesity. The Taq1A genotype is a common thread that ties the contrasting models of DA reward and obesity; this genotype related to striatal DA is not associated with obesity class per se but may nevertheless confer an increased risk of weight gain. We also critically examine the concept of so-called food addiction, and despite growing evidence, we argue that there is currently insufficient human data to warrant this diagnostic label. The surgical and pharmacological treatments of obesity are discussed, and evidence is presented for the selective use of DA-class drugs in obesity treatment.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.880
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.057
GPT teacher head0.412
Teacher spread0.354 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations48
Published2017
Admission routes1
Has abstractyes

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