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Record W1578638574 · doi:10.3389/fpsyg.2015.01044

Sex-dependent effects on tasks assessing reinforcement learning and interference inhibition

2015· article· en· W1578638574 on OpenAlexafffund
Kelly Evans, Elizabeth Hampson

Bibliographic record

VenueFrontiers in Psychology · 2015
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPsychologyReinforcementTask (project management)Prefrontal cortexReinforcement learningCognitionStop signalCognitive psychologyDevelopmental psychologySocial psychologyNeuroscienceArtificial intelligence

Abstract

fetched live from OpenAlex

Increasing evidence suggests that the prefrontal cortex (PFC) is influenced by sex steroids and that some cognitive functions dependent on the PFC may be sexually differentiated in humans. Past work has identified a male advantage on certain complex reinforcement learning tasks, but it is unclear which latent task components are important to elicit the sex difference. The objective of the current study was to investigate whether there are sex differences on measures of response inhibition and valenced feedback processing, elements that are shared by previously studied reinforcement learning tasks. Healthy young adults (90 males, 86 females) matched in general intelligence completed the Probabilistic Selection Task (PST), a Simon task, and the Stop-Signal task. On the PST, females were more accurate than males in learning from positive (but not negative) feedback. On the Simon task, males were faster than females, especially in the face of incongruent stimuli. No sex difference was observed in Stop-Signal reaction time. The current findings provide preliminary support for a sex difference in the processing of valenced feedback and in interference inhibition.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.531
Threshold uncertainty score0.613

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 head0.100
GPT teacher head0.393
Teacher spread0.294 · 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

Citations55
Published2015
Admission routes2
Has abstractyes

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