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Record W2579920998 · doi:10.3758/s13415-016-0496-2

Serotonin enhances the impact of health information on food choice

2017· article· en· W2579920998 on OpenAlexafffund
Ivo Vlaev, Molly J. Crockett, Luke Clark, Ulrich Müller, Trevor W. Robbins

Bibliographic record

VenueCognitive Affective & Behavioral Neuroscience · 2017
Typearticle
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsUniversity of British Columbia
FundersH. Lundbeck A/SMedical Research CouncilUniversity of WarwickInternational Seafood Sustainability FoundationUniversity of British ColumbiaWellcome TrustSunovionEli Lilly and Company
KeywordsCitalopramAtomoxetineSerotoninPsychologyPlaceboSerotonin reuptake inhibitorReuptake inhibitorPsychiatryAttention deficit hyperactivity disorderMedicineAntidepressantInternal medicineMethylphenidateAnxiety

Abstract

fetched live from OpenAlex

Serotonin has been implicated in promoting self-control, regulation of hunger and physiological homeostasis, and regulation of caloric intake. However, it remains unclear whether the effects of serotonin on caloric intake reflect purely homeostatic mechanisms, or whether serotonin also modulates cognitive processes involved in dietary decision making. We investigated the effects of an acute dose of the serotonin reuptake inhibitor citalopram on choices between food items that differed along taste and health attributes, compared with placebo and the noradrenaline reuptake inhibitor atomoxetine. Twenty-seven participants attended three sessions and received single doses of atomoxetine, citalopram, and placebo in a double-blind randomised cross-over design. Relative to placebo, citalopram increased choices of more healthy foods over less healthy foods. Citalopram also increased the emphasis on health considerations in decisions. Atomoxetine did not affect decision making relative to placebo. The results support the hypothesis that serotonin may influence food choice by enhancing a focus on long-term goals. The findings are relevant for understanding decisions about food consumption and also for treating health conditions such as eating disorders and obesity.

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)0.002
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.250
GPT teacher head0.409
Teacher spread0.158 · 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

Citations17
Published2017
Admission routes2
Has abstractyes

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