Evidence map›Paper›PMID 33385564›Full record

ArticleNeuroImage2021

Activation of the cognitive control network associated with information uncertainty.

Tingting Wu, Kurt P Schulz, Jin Fan

Abstract read
In one paragraph

Article in NeuroImage, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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

  1. Pooled it
  2. Pooled it
  3. CMROLa Radiologia medica · 2025
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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.

Tingting WuDepartment of Psychology, Queens College, The City University of New York, Queens, NY, USA.
Kurt P SchulzDepartment of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Jin FanDepartment of Psychology, Queens College, The City University of New York, Queens, NY, USA. Electronic address: jin.fan@qc.cuny.edu.

Funding

Uncertainty, Cognitive Control, and the BrainR01MH094305 · NIMH · QUEENS COLLEGE · PI FAN, JIN · 2012 to 2016
$1.7M
NIMH NIH HHS R01 MH094305
6 · The paper itself

Abstract

The cognitive control network (CCN) that comprises regions of the frontoparietal network, the cingulo-opercular network, and other sub-cortical regions as core structures is commonly activated by events with an increase in information uncertainty. However, it is not clear whether this CCN activation is associated with both information entropy that represents the information conveyed by the context formed by a sequence of events and the surprise that quantifies the information conveyed by a specific type of event in the context. We manipulated entropy and surprise in this functional magnetic resonance imaging study by varying the probability of occurrence of two types of events in both the visual and auditory modalities and measured brain response as a function of entropy and surprise. We found that activation in regions of the CCN increased as a function of entropy and surprise in both the visual and auditory tasks. The frontoparietal network and additional structures in the CCN mediated the relationship between these information measures and behavioral response. These results suggest that the CCN is a high-level modality-general neural entity for the control of the processing of information conveyed by both context and event.

Indexed as

UncertaintyAcoustic StimulationAdultBrainCognitionFemaleHumansMagnetic Resonance ImagingMaleNerve NetPhotic StimulationRandom AllocationCognitive controlCognitive control networkEntropySurpriseUncertainty

Identifiers

PMID33385564
PMCPMC8558818

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.