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Record W4403637670 · doi:10.1093/pnasnexus/pgae432

Cognitive effort increases the intensity of rewards

2024· article· en· W4403637670 on OpenAlexaff
Mejda Wahab, Nicole L. Mead, Stevenson Desmercieres, Virginie Lardeux, Emilie Dugast, Roy F. Baumeister, Marcello Solinas

Bibliographic record

VenuePNAS Nexus · 2024
Typearticle
Languageen
FieldNeuroscience
TopicNeurotransmitter Receptor Influence on Behavior
Canadian institutionsYork University
FundersInstitut pour la Recherche en Santé PubliqueCentre National de la Recherche ScientifiqueUniversité de PoitiersInstitut National de la Santé et de la Recherche Médicale
KeywordsOverconsumptionCognitionPsychologyAddictionEffects of sleep deprivation on cognitive performanceConsumption (sociology)Cognitive biasDevelopmental psychologySocial psychologyCognitive psychologyProduction (economics)PsychiatryEconomics

Abstract

fetched live from OpenAlex

An important body of literature suggests that exerting intense cognitive effort causes mental fatigue and can lead to unhealthy behaviors such as indulging in high-calorie food and taking drugs. Whereas this effect has been mostly explained in terms of weakening cognitive control, cognitive effort may also bias behavioral choices by amplifying the hedonic and emotional impact of rewards. We report parallel findings with animals and humans supporting this hypothesis. In rats, exerting cognitive effort immediately before access to cocaine self-administration significantly increased drug intake. In addition, exerting cognitive effort increased the psychostimulant effect of cocaine. The effects of cognitive effort on addiction-related behaviors were eliminated and even reversed when animals could rest in their home-cage for 2-4 h before access to cocaine self-administration. Among humans, we found that expending cognitive effort increased consumption of tasty (but unhealthy) food by increasing the hedonic enjoyment of consuming the food. In addition, the effects were specific for emotionally relevant stimuli (i.e. food rewards) and did not generalize to judgment about neutral objects. Altogether these data suggest that intense cognitive effort can increase the perceived intensity of rewards and lead to their overconsumption. This effect may contribute to bad decision making induced by excessive cognitive effort and make people more vulnerable to indulge in unhealthy behaviors such as use of addictive drugs.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.393

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.046
GPT teacher head0.317
Teacher spread0.271 · 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 designBench or experimental
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

Citations0
Published2024
Admission routes1
Has abstractyes

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