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Cited by 340

The DOI matches its Crossref record; 226 of the 226 references it cites were found in a registry or an index.

Visual mismatch negativity: a predictive coding view

Open access
Stefanics, Gábor, Kremláček, Jan, Czigler, István·2014·Frontiers in Human Neuroscience

Abstract

An increasing number of studies investigate the visual mismatch negativity (vMMN) or use the vMMN as a tool to probe various aspects of human cognition. This paper reviews the theoretical underpinnings of vMMN in the light of methodological considerations and provides recommendations for measuring and interpreting the vMMN. The following key issues are discussed from the experimentalist's point of view in a predictive coding framework: (1) experimental protocols and procedures to control "refractoriness" effects; (2) methods to control attention; (3) vMMN and veridical perception.

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Metadata

Authors
Stefanics, G., Kremláček, J., & Czigler, I.
Venue
Frontiers in Human Neuroscience
Published
2014-09-16
Volume
8
Pages
666-666
ISSN
1662-5161 (ISSN-L)
OpenAlex
W2018401563
Cited by
340
References
226
FWCI
10.38
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Visual mismatch negativity: a predictive coding view. https://app.cochat.ai/papers/10.3389/fnhum.2014.00666
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Stefanics, G., Kremláček, J., & Czigler, I. (2014). Visual mismatch negativity: a predictive coding view. Frontiers in Human Neuroscience. https://doi.org/10.3389/fnhum.2014.00666

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.