Nick Yeung is now at the Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA. Rafal Bogacz is now at the Department of Computer Science, Bristol University, Bristol, UK. Clay Holroyd is now at the Department of Psychology, University of Victoria, Victoria, British Columbia, Canada. The Matlab code used to generate the simulated EEG data is available from Rafal Bogacz at http://www.cs.bris.ac.uk/home/rafal/phasereset. The Matlab code used to visualize the data is available from Scott Makeig at http://www.sccn.ucsd.edu/~scott/index.html. The use of the EEGLab toolbox in the present research is gratefully acknowledged. We thank Sander Nieuwenhuis, Scott Makeig, and five anonymous reviewers for helpful comments on previous drafts of the manuscript. The research was supported by grants from the National Institutes of Health (P50-MH62196) and National Science Foundation (DBR98-71186), and by a postdoctoral fellowship from the National Institutes of Mental Health to Clay Holroyd (MH63550).
Detection of synchronized oscillations in the electroencephalogram: An evaluation of methods
Article first published online: 24 SEP 2004
Volume 41, Issue 6, pages 822–832, November 2004
How to Cite
Yeung, N., Bogacz, R., Holroyd, C. B. and Cohen, J. D. (2004), Detection of synchronized oscillations in the electroencephalogram: An evaluation of methods. Psychophysiology, 41: 822–832. doi: 10.1111/j.1469-8986.2004.00239.x
- Issue published online: 24 SEP 2004
- Article first published online: 24 SEP 2004
- (Received February 5, 2004; Accepted June 11, 2004)
- Event-related potential;
- Phase resetting
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.