Evidence map›Paper›PMID 32744502›Full record

ArticleeLife2020

Boosts in brain signal variability track liberal shifts in decision bias.

Niels A Kloosterman, Julian Q Kosciessa, Ulman Lindenberger, Johannes Jacobus Fahrenfort, Douglas D Garrett

Abstract read
In one paragraph

Article in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
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  4. Did you see it?eLife · 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

5 authors.

Niels A KloostermanMax Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany.ORCID 0000-0002-1134-7996
Julian Q KosciessaMax Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany.ORCID 0000-0002-4553-2794
Ulman LindenbergerMax Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany.ORCID 0000-0001-8428-6453
Johannes Jacobus FahrenfortDepartment of Experimental and Applied Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.ORCID 0000-0002-9025-3436
Douglas D GarrettMax Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany.ORCID 0000-0002-0629-7672

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adopting particular decision biases allows organisms to tailor their choices to environmental demands. For example, a liberal response strategy pays off when target detection is crucial, whereas a conservative strategy is optimal for avoiding false alarms. Using conventional time-frequency analysis of human electroencephalographic (EEG) activity, we previously showed that bias setting entails adjustment of evidence accumulation in sensory regions (Kloosterman et al., 2019), but the presumed prefrontal signature of a conservative-to-liberal bias shift has remained elusive. Here, we show that a liberal bias shift is reflected in a more unconstrained neural regime (boosted entropy) in frontal regions that is suited to the detection of unpredictable events. Overall EEG variation, spectral power and event-related potentials could not explain this relationship, highlighting that moment-to-moment neural variability uniquely tracks bias shifts. Neural variability modulation through prefrontal cortex appears instrumental for permitting an organism to adapt its biases to environmental demands.

Indexed as

Auditory PerceptionAcoustic StimulationAdultBrainDecision MakingElectroencephalographyFemaleHumansMaleYoung Adultbrain signal variabilitycognitive flexibilitydecision biashumanneuroscienceperceptual decision makingsignal detection theory

Identifiers

PMID32744502
PMCPMC7398662

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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.