Evidence map›Paper›PMID 29581379›Full record

ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2018

Visual Mismatch and Predictive Coding: A Computational Single-Trial ERP Study.

Gabor Stefanics, Jakob Heinzle, András Attila Horváth, Klaas Enno Stephan

Open access · bronzeAbstract read
In one paragraph

Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 2 pooled it
7.2field-weighted citation impact, top 2% of its field
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

52 citing papers in PubMed, 2 syntheses or guidelines pooled it, 131 citations in OpenAlex.

  1. Pooled it
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  10. The Somatosensory Mismatch Negativity.The European journal of neuroscience · 2025
    Review
  11. Article
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  14. Article
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  18. Article
  19. Perceptual oddities: assessing the relationship between film editing and prediction processes.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    Article
  20. The aesthetic valve: how aesthetic appreciation may switch emotional states from anxiety to curiosity.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    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

4 authors at 3 institutions in 4 countries.

Gabor StefanicsTranslational Neuromodeling Unit, University of Zurich & ETH Zurich, 8032 Zurich, Switzerland, stefanics@biomed.ee.ethz.ch.ORCID 0000-0002-0324-0996
Jakob HeinzleTranslational Neuromodeling Unit, University of Zurich & ETH Zurich, 8032 Zurich, Switzerland.ORCID 0000-0001-5228-041X
András Attila HorváthNational Institute of Clinical Neurosciences, Department of Neurology, National Brain Research Program, 1145, Budapest, Hungary.ORCID 0000-0002-5614-7015
Klaas Enno StephanTranslational Neuromodeling Unit, University of Zurich & ETH Zurich, 8032 Zurich, Switzerland.ORCID 0000-0002-8594-9092
University of Zurich · CHOrszágos Idegsebészeti Tudományos Intézet · HUWellcome Centre for Human Neuroimaging · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Predictive coding (PC) posits that the brain uses a generative model to infer the environmental causes of its sensory data and uses precision-weighted prediction errors (pwPEs) to continuously update this model. While supported by much circumstantial evidence, experimental tests grounded in formal trial-by-trial predictions are rare. One partial exception is event-related potential (ERP) studies of the auditory mismatch negativity (MMN), where computational models have found signatures of pwPEs and related model-updating processes. Here, we tested this hypothesis in the visual domain, examining possible links between visual mismatch responses and pwPEs. We used a novel visual "roving standard" paradigm to elicit mismatch responses in humans (of both sexes) by unexpected changes in either color or emotional expression of faces. Using a hierarchical Bayesian model, we simulated pwPE trajectories of a Bayes-optimal observer and used these to conduct a comprehensive trial-by-trial analysis across the time × sensor space. We found significant modulation of brain activity by both color and emotion pwPEs. The scalp distribution and timing of these single-trial pwPE responses were in agreement with visual mismatch responses obtained by traditional averaging and subtraction (deviant-minus-standard) approaches. Finally, we compared the Bayesian model to a more classical change model of MMN. Model comparison revealed that trial-wise pwPEs explained the observed mismatch responses better than categorical change detection. Our results suggest that visual mismatch responses reflect trial-wise pwPEs, as postulated by PC. These findings go beyond classical ERP analyses of visual mismatch and illustrate the utility of computational analyses for studying automatic perceptual processes.

Indexed as

Evoked Potentials, VisualModels, NeurologicalVisual PerceptionAdultBayes TheoremCerebral CortexEmotionsFemaleHumansMaleBayesian inferencecomputational modelingEEGprecision-weighted prediction errorvisual MMN

Identifiers

PMID29581379
PMCPMC6705923
OpenAlexW2791775851

What OpenQuestion holds

Textmetadata
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.