Evidence map›Paper›PMID 41992065›Full record

ArticleCommunications psychology2026

Type-1 and type-2 decisions feature computational noise of similar magnitude.

Yunxuan Zheng, Kai Xue, Medha Shekhar, Dobromir Rahnev

Abstract read
In one paragraph

Article in Communications psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yunxuan ZhengSchool of Psychology, Georgia Institute of Technology, Atlanta, GA, USA. yzheng447@gatech.edu.ORCID http://orcid.org/0000-0002-2462-7057
Kai XueSchool of Psychology, Georgia Institute of Technology, Atlanta, GA, USA.ORCID http://orcid.org/0000-0003-0919-9231
Medha ShekharSchool of Psychology, Georgia Institute of Technology, Atlanta, GA, USA.
Dobromir RahnevSchool of Psychology, Georgia Institute of Technology, Atlanta, GA, USA.ORCID http://orcid.org/0000-0002-5265-2559

Funding

Uncovering the Architecture of MetacognitionR01MH119189 · NIMH · GEORGIA INSTITUTE OF TECHNOLOGY · PI RAHNEV, DOBROMIR · 2020 to 2024
$1.5M
NIMH NIH HHS R01 MH119189United States Department of Defense | United States Navy | Office of Naval Research (ONR) N00014-20-1-2622
6 · The paper itself

Abstract

Mounting evidence supports the existence of Type-2, metacognitive noise that affects human confidence judgments. The existence of this noise has led to the hypothesis that metacognitive judgments arise from a metacognitive system that is separate from the decision-making system responsible for Type-1 decisions. However, Type-2 decisions are different than standard Type-1 decisions in that they require evaluating the strength of sensory evidence rather than just making a simple categorical judgment. Here, we investigated whether Type-2 computational noise still exceeds Type-1 computational noise when both judgments require evaluation of the strength of sensory evidence. Participants (N = 319) performed a perceptual discrimination task and in different conditions provided Type-2 confidence judgments or Type-1 judgments based on biased expectations or unequal rewards. All these judgments require a similar fine-grained evaluation of the strength of sensory evidence (e.g., is the evidence high enough to justify a high-confidence rating or choosing the alternative with smaller probability or reward). We first confirmed that the confidence and expectation conditions resulted in similarly biased criteria and perceptual sensitivity drop, whereas the reward conditions exhibited less biased criteria and smaller perceptual sensitivity drop. Critically, formal computational modeling demonstrated that all conditions exhibited comparable levels of computational noise. These findings demonstrate that Type-1 and Type-2 decisions exhibit computational noise of similar magnitude when they require similar fine-grained evaluation of sensory evidence strength. More generally, our results have implications for the debate on whether Type-1 and Type-2 decisions are made by separate systems.

Identifiers

PMID41992065
PMCPMC13462944

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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.