Evidence map›Paper›PMID 42325284›Full record

ArticleOxford open neuroscience2026

Sex differences in task engagement and lapse rate during reward learning.

Claudia G Aguirre, Jae H Woo, Lana Alhabbal, Taylor Fujioka, Romi Moore, Tony Ye, Jaime J Castrellon, Alireza Soltani, Alicia Izquierdo

Abstract read
In one paragraph

Article in Oxford open neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Claudia G AguirreDepartment of Psychology, University of California, Los Angeles, 502 Portola Plaza, Los Angeles, CA 90045, United States.
Jae H WooDepartment of Psychological and Brain Sciences, Dartmouth College, 6207 Moore Hall, Hanover, NH 03755, United States.
Lana AlhabbalDepartment of Psychology, University of California, Los Angeles, 502 Portola Plaza, Los Angeles, CA 90045, United States.
Taylor FujiokaDepartment of Psychology, University of California, Los Angeles, 502 Portola Plaza, Los Angeles, CA 90045, United States.
Romi MooreDepartment of Psychology, University of California, Los Angeles, 502 Portola Plaza, Los Angeles, CA 90045, United States.
Tony YeDepartment of Psychology, University of California, Los Angeles, 502 Portola Plaza, Los Angeles, CA 90045, United States.
Jaime J CastrellonDepartment of Psychology, University of California, Los Angeles, 502 Portola Plaza, Los Angeles, CA 90045, United States.
Alireza SoltaniDepartment of Psychological and Brain Sciences, Dartmouth College, 6207 Moore Hall, Hanover, NH 03755, United States.
Alicia IzquierdoDepartment of Psychology, University of California, Los Angeles, 502 Portola Plaza, Los Angeles, CA 90045, United States.ORCID https://orcid.org/0000-0001-9897-2091

Funding

CRCNS Research Proposal: Cortico-amygdalar substrates of adaptive learningR01DA047870 · NIDA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Alicia Izquierdo, Alireza Soltani · 2018 to 2026
$4.1M
NIDA NIH HHS R01 DA047870
6 · The paper itself

Abstract

Our understanding of sex differences in reward learning has been limited due to the predominant study of males. Here, we evaluated sex differences in flexible learning in two domains: the learning of stimulus- and action-based associations and their reversals. During action-based learning, rats selected between two identical visual stimuli presented on a touchscreen, where the spatial location predicted a higher probability of reward. For stimulus-based learning, rats chose between two distinct visual stimuli presented in pseudorandom spatial locations, one of which was associated with a higher probability of reward. Reversal phases involved switching reward contingency between the two actions or stimuli. We found that females did not differ in their discrimination or reversal learning accuracy compared to males, yet they collected fewer rewards and were more likely to omit trials than males in both domains. To gain a detailed understanding of differences across conditions, we modeled animals' trial-by-trial choices using reinforcement learning (RL) models and examined their steady-state behavior to capture transitions between distinct behavioral states. Although the estimated parameters of the best-fitting RL model revealed some sex differences, the model that incorporated transitions between different behavioral states provided a better overall fit to the data. This model also revealed that across all reversal phases, females exhibited a higher transition-specific lapse rate than males, indicating greater task disengagement once there was no need for further learning. Together, our fine-grained analysis of behavior adds to a growing literature on sex differences in flexible reward learning.

Indexed as

action learningdeterministicprobabilisticSex differencesstimulus learning

Identifiers

PMID42325284
PMCPMC13280948

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.