Evidence map›Paper›PMID 35416775›Full record

ArticleeLife2022

Neuronal origins of reduced accuracy and biases in economic choices under sequential offers.

Weikang Shi, Sebastien Ballesta, Camillo Padoa-Schioppa

Abstract read
In one paragraph

Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Neuronal Activity in Orbitofrontal Cortex during Trinary Choices under Risk.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
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  4. Review
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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.

Weikang ShiDepartment of Neuroscience, Washington University in St. Louis, St. Louis, United States.ORCID 0000-0002-4068-1168
Sebastien BallestaDepartment of Neuroscience, Washington University in St. Louis, St. Louis, United States.
Camillo Padoa-SchioppaDepartment of Neuroscience, Washington University in St. Louis, St. Louis, United States.ORCID 0000-0002-7519-8790

Funding

THE ROLE OF PREFRONTAL REGIONS IN ECONOMIC CHOICE AND CHOICE-GUIDED BEHAVIORR01DA032758 · NIDA · WASHINGTON UNIVERSITY · PI Camillo Padoa-Schioppa · 2012 to 2026
$5.4M
NEURONAL MECHANISMS OF GOOD-BASED ECONOMIC DECISIONSR01MH104494 · NIMH · WASHINGTON UNIVERSITY · PI PADOA-SCHIOPPA, CAMILLO · 2015 to 2025
$4.2M
NIDA NIH HHS R01 DA032758NIMH NIH HHS R01 MH104494
6 · The paper itself

Abstract

Economic choices are characterized by a variety of biases. Understanding their origins is a long-term goal for neuroeconomics, but progress on this front has been limited. Here, we examined choice biases observed when two goods are offered sequentially. In the experiments, rhesus monkeys chose between different juices offered simultaneously or in sequence. Choices under sequential offers were less accurate (higher variability). They were also biased in favor of the second offer (order bias) and in favor of the preferred juice (preference bias). Analysis of neuronal activity recorded in the orbitofrontal cortex revealed that these phenomena emerged at different computational stages. Lower choice accuracy reflected weaker offer value signals (valuation stage), the order bias emerged during value comparison (decision stage), and the preference bias emerged late in the trial (post-comparison). By neuronal measures, each phenomenon reduced the value obtained on average in each trial and was thus costly to the monkey.

Indexed as

Choice BehaviorNeuronsAnimalsBiasDecision MakingMacaca mulattaPrefrontal Cortexbehavioral economicsdecision makingmonkeyneuroeconomicsneuroscienceorbitofrontal cortexrationalityrhesus macaque

Identifiers

PMID35416775
PMCPMC9045815

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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.