We are grateful to the three anonymous reviewers for constructive criticism, to Profs. Joachim Gross and Ariel Schoenfeld for helpful comments on an earlier version of the manuscript, and to Dr. Artur Matysiak for fruitful discussions. Peter Heil is supported by the Deutsche Forschungsgemeinschaft (SFB-TRR 31 A6).
The M100 component of evoked magnetic fields differs by scaling factors: Implications for signal averaging
Article first published online: 22 FEB 2011
Copyright © 2011 Society for Psychophysiological Research
Volume 48, Issue 8, pages 1069–1082, August 2011
How to Cite
Zacharias, N., Sielużycki, C., Kordecki, W., König, R. and Heil, P. (2011), The M100 component of evoked magnetic fields differs by scaling factors: Implications for signal averaging. Psychophysiology, 48: 1069–1082. doi: 10.1111/j.1469-8986.2011.01183.x
- Issue published online: 5 JUL 2011
- Article first published online: 22 FEB 2011
- (Received August 19, 2010; Accepted December 23, 2010)
- Additive and multiplicative model;
- Arithmetic and geometric averaging;
- Auditory evoked magnetic fields;
- Source modeling
MEG and EEG studies of event-related responses often involve comparisons of grand averages, requiring homogeneity of the variances. Here, we examine the possibility, implied by the nature of neural sources and the measuring principles involved, that the M100 component of auditory-evoked magnetic fields of different subjects, hemispheres, to different stimuli, and at different sensors differs by scaling factors. Such a multiplicative model predicts a linear increase in the standard deviation with the mean, and thus would have important implications for averaging and comparing such data. Our analyses, at the sensor and the source level, clearly show that the multiplicative model applies. We therefore propose geometric, rather than arithmetic, averaging of the M100 component across subjects and suggest a novel and superior normalization procedure. Our results question the justification of the common practice of subtracting arithmetic grand averages.