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Cited by 250

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Detection of synchronized oscillations in the electroencephalogram: An evaluation of methods

Yeung, Nick, Bogacz, Rafal, Holroyd, Clay B., Cohen, Jonathan D.·2004·Psychophysiology

Abstract

The signal averaging approach typically used in ERP research assumes that peaks in ERP waveforms reflect neural activity that is uncorrelated with activity in the ongoing EEG. However, this assumption has been challenged by research suggesting that ERP peaks reflect event‐related synchronization of ongoing EEG oscillations. In this study, we investigated the validity of a set of methods that have been used to demonstrate that particular ERP peaks result from synchronized EEG oscillations. We simulated epochs of EEG data by superimposing phasic peaks on noise characterized by the power spectrum of the EEG. When applied to the simulated data, the methods in question produced results that have previously been interpreted as evidence of synchronized oscillations, even though no such synchrony was present. These findings suggest that proposed analysis methods may not effectively disambiguate competing views of ERP generation.

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Crossref · 10.1111/j.1469-8986.2004.00239.x

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Metadata

Authors
Yeung, N., Bogacz, R., Holroyd, C. B., & Cohen, J. D.
Venue
Psychophysiology
Publisher
Wiley
Published
2004-09-24
Volume
41
Issue
6
Pages
822-832
ISSN
  • 0048-5772 (ISSN-L)
  • 1469-8986
OpenAlex
W1976426522
Cited by
250
References
7
FWCI
5.92
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Detection of synchronized oscillations in the electroencephalogram: An evaluation of methods. https://app.cochat.ai/papers/10.1111/j.1469-8986.2004.00239.x
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Yeung, N., Bogacz, R., Holroyd, C. B., & Cohen, J. D. (2004). Detection of synchronized oscillations in the electroencephalogram: An evaluation of methods. Psychophysiology. https://doi.org/10.1111/j.1469-8986.2004.00239.x

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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.