Evidence map›Paper›PMID 41306425›Full record

SynthesisFrontiers in neuroscience2025

Neural correlates of uncertainty processing: meta-analysis of fMRI studies.

Andrey Timashkov, Sarah Anderson, Oksana Zinchenko

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Andrey TimashkovCentre for Cognition and Decision Making, Institute for Cognitive Neuroscience, HSE University, Moscow, Russia.
Sarah AndersonCentre for Cognition and Decision Making, Institute for Cognitive Neuroscience, HSE University, Moscow, Russia.
Oksana ZinchenkoCentre for Cognition and Decision Making, Institute for Cognitive Neuroscience, HSE University, Moscow, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Understanding the neural mechanisms underlying decision-making under uncertainty represents a fundamental challenge in cognitive neuroscience. This meta-analysis aimed to identify the consistent neural correlates of uncertainty processing specifically during decision-making tasks. Methods: We synthesized findings from 76 fMRI studies ( Results: The analysis revealed nine distinct activation clusters, revealing a comprehensive neural network involved in uncertainty processing. Key findings demonstrated predominant activations in the anterior insula (up to 63.7% representation), inferior frontal gyrus (up to 40.7%), and inferior parietal lobule (up to 78.1%). We found a functional specialization between emotional-motivational processes (clusters 1-5) and cognitive processes (clusters 6-9), with notable hemispheric asymmetries. The left anterior insula was more strongly associated with reward evaluation, while the right was involved in learning and cognitive control. Similarly, the right inferior frontal gyrus was linked to impulse control, and the left to motor planning. Discussion: Our findings extend the current understanding of the neural architecture of decision-making under uncertainty. The comprehensive mapping of neural signatures advances our knowledge of the distinct roles of key brain regions and provides insights into potential clinical applications, particularly for developing interventions for uncertainty-related anxiety. The study highlights important directions for future research in cognitive neuroscience and clinical practice.

Indexed as

ALEcascade modeldecision-makingfMRImeta-analysisuncertainty

Identifiers

PMID41306425
PMCPMC12644092

What OpenQuestion holds

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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.