Evidence map›Paper›PMID 28751458›Full record

ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2017

Information-Theoretic Evidence for Predictive Coding in the Face-Processing System.

Alla Brodski-Guerniero, Georg-Friedrich Paasch, Patricia Wollstadt, Ipek Özdemir, Joseph T Lizier, Michael Wibral

Abstract read
In one paragraph

Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. From generative AI to the brain: five takeaways.Frontiers in computational neuroscience · 2025
    Article
  6. Article
  7. Article
  8. Article
  9. Predictive processing models and affective neuroscience.Neuroscience and biobehavioral reviews · 2021
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Measuring spectrally-resolved information transfer.PLoS computational biology · 2020
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

6 authors.

Alla Brodski-GuernieroMEG Unit, Brain Imaging Center, J.W. Goethe University, 60323 Frankfurt am Main, Germany, and.ORCID 0000-0002-5852-4750
Georg-Friedrich PaaschMEG Unit, Brain Imaging Center, J.W. Goethe University, 60323 Frankfurt am Main, Germany, and.
Patricia WollstadtMEG Unit, Brain Imaging Center, J.W. Goethe University, 60323 Frankfurt am Main, Germany, and.ORCID 0000-0002-7105-5207
Ipek ÖzdemirMEG Unit, Brain Imaging Center, J.W. Goethe University, 60323 Frankfurt am Main, Germany, and.ORCID 0000-0001-6807-9390
Joseph T LizierComplex Systems Research Group and Centre for Complex Systems, Faculty of Engineering & IT, The University of Sydney, New South Wales 2006, Australia.ORCID 0000-0002-9910-8972
Michael WibralMEG Unit, Brain Imaging Center, J.W. Goethe University, 60323 Frankfurt am Main, Germany, and wibral@bic.uni-frankfurt.de.ORCID 0000-0001-8010-5862

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Predictive coding suggests that the brain infers the causes of its sensations by combining sensory evidence with internal predictions based on available prior knowledge. However, the neurophysiological correlates of (pre)activated prior knowledge serving these predictions are still unknown. Based on the idea that such preactivated prior knowledge must be maintained until needed, we measured the amount of maintained information in neural signals via the active information storage (AIS) measure. AIS was calculated on whole-brain beamformer-reconstructed source time courses from MEG recordings of 52 human subjects during the baseline of a Mooney face/house detection task. Preactivation of prior knowledge for faces showed as α-band-related and β-band-related AIS increases in content-specific areas; these AIS increases were behaviorally relevant in the brain's fusiform face area. Further, AIS allowed decoding of the cued category on a trial-by-trial basis. Our results support accounts indicating that activated prior knowledge and the corresponding predictions are signaled in low-frequency activity (<30 Hz).

Indexed as

AdultBrainBrain WavesFacial RecognitionFemaleForecastingHumansMagnetoencephalographyMalePattern Recognition, VisualPhotic StimulationYoung Adultface perceptioninformation storageinformation theoryMooneypredictionpredictive coding

Identifiers

PMID28751458
PMCPMC6596791

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.