, Volume 3, Issue 4, pp 407-423

Topographic component (Parallel Factor) analysis of multichannel evoked potentials: Practical issues in trilinear spatiotemporal decomposition

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Summary

We describe a substantive application of the trilinear topographic components /parallel factors model (TC/PARAFAC, due to Möcks/Harshman) to the decomposition of multichannel evoked potentials (MEP's). We provide practical guidelines and procedures for applying PARAFAC methodology to MEP decomposition. Specifically, we apply techniques of data preprocessing, orthogonality constraints, and validation of solutions in a complete TC analysis, for the first time using actual MEP data. The TC model is shown to be superior to the traditional bilinear principal components model in terms of data reduction, confirming the advantage of the TC model's added assumptions. The model is then shown to provide a unique spatiotemporal decomposition that is reproducible in different subject groups. The components are shown to be consistent with spatial/temporal features evident in the data, except for an artificial component resulting from latency jitter. Subject scores on this component are shown to reflect peak latencies in the data, suggesting a new aspect to statistical analyses based on subject scores. In general, the results support the conclusion that the TC model is a promising alternative to principal components for data reduction and analysis of MEP's.

This paper contains portions of the first author's dissertation, submitted in partial fulfillment of the requirements for the Ph.D. degree, Department of Bioengineering, University of Illinois at Chicago. The authors are indebted to G. Raviv of Bio-logic Systems Corp., Mundelein, Illinois, USA, for providing proprietary data and topographic mapping software used in this research; R. A. Harshman and M. E. Lundy of Scientific Software Associates, London, Ontario, Canada, for advising on the use of the PARAFAC analysis package; the Computer Center of the University of Illinois at Chicago for providing computational and plotting facilities; J. Kripal for helping to collect the data; and M. Field for assisting with the manuscript. They also thank R. A. Harshman and anonymous reviewers for their comments on an earlier draft of the paper.