Evidence map›Paper›PMID 30690563›Full record

ArticleSocial cognitive and affective neuroscience2019

Differential modulation of cognitive control networks by monetary reward and punishment.

Ana Cubillo, Aidan B Makwana, Todd A Hare

Abstract read
In one paragraph

Article in Social cognitive and affective neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 2 pooled it
–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

21 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  13. Aversive motivation and cognitive control.Neuroscience and biobehavioral reviews · 2022
    Review
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  16. Decomposing the motivation to exert mental effort.Current directions in psychological science · 2021
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ana CubilloDepartment of Economics, University of Zurich, Zürich, Switzerland.
Aidan B MakwanaDepartment of Economics, University of Zurich, Zürich, Switzerland.
Todd A HareDepartment of Economics, University of Zurich, Zürich, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Incentives are primary determinants of if and how well an organism will perform a given behavior. Here, we examined how incentive valence and magnitude influence task switching, a critical cognitive control process, and test the predictions that the anterior cingulate cortex (ACC) and the ventral striatum (vStr) function as key nodes linking motivation and control systems in the brain. Our results indicate that reward and punishment incentives have both common and distinct effects on cognitive control at the behavioral and neurobiological levels. For example, reward incentives led to greater activity in the ACC during the engagement of control relative to punishments. Furthermore, the neural responses to reward and punishment differed as a function of individual sensitivity to each incentive valence. Functional connectivity analyses suggest a role for vStr in signaling motivational value during cognitive control and as a potential link between motivation and control networks. Overall, our findings suggest that similar changes in observed behavior (e.g. response accuracy) under reward and punishment incentives are mediated by, at least partially, distinct neurobiological substrates.

Indexed as

PunishmentRewardAdultBrainBrain MappingCognitionFemaleGyrus CinguliHumansMagnetic Resonance ImagingMaleMotivationVentral Striatumanterior cingulate cortexcognitive controlpunishmentrewardventral striatum

Identifiers

PMID30690563
PMCPMC6399610

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.