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Detection of synchronized oscillations in the electroencephalogram: An evaluation of methods
Author(s) -
Yeung Nick,
Bogacz Rafal,
Holroyd Clay B.,
Cohen Jonathan D.
Publication year - 2004
Publication title -
psychophysiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.661
H-Index - 156
eISSN - 1469-8986
pISSN - 0048-5772
DOI - 10.1111/j.1469-8986.2004.00239.x
Subject(s) - electroencephalography , synchronization (alternating current) , psychology , uncorrelated , noise (video) , signal (programming language) , pattern recognition (psychology) , waveform , set (abstract data type) , event related potential , speech recognition , cognitive psychology , artificial intelligence , neuroscience , computer science , statistics , mathematics , computer network , telecommunications , channel (broadcasting) , radar , image (mathematics) , programming language
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.