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PubMed · 7599022

Some limitations of spatio temporal source models.

D Cabrera Fernández·R Grave de Peralta Menéndez·S L González Andino
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Abstract

The spatio temporal source model (STSM) interprets the successive scalp topographies of an electrophysiological event as the summed activity of a few fixed generators. This modeling methodology is expected to provide a unique solution for a fixed number of sources. Because in general there is no "a priori" available physiological information, independent criteria need to be applied for determining the correct number of sources (Ns). This study illustrates theoretically as well as in simulations, that the existence of a unique solution can only be claimed when Ns is known a priori. Since most of the methods proposed for estimate Ns are not accurate as illustrated here, STSM may result in unpredictable non-physiological solutions. Basic modeling aspects and additional factors affecting reliability of STSM such as those related to the optimization process associated to the source parameter search are discussed. Some of the possible inverse solutions are illustrated in our simulations. Our main conclusion is the need to improve STSM before claims about neural generator localization can be accepted. We will also discuss, how attempts to apply STSM to clinical data, apparently supporting their reliability, are plagued with incorrect assumptions and do not justify the expectancy aroused about such models. We discuss some ways for improving STSM and the need to develop measures to evaluate their reliability, independent of the physiological plausibility of the solutions obtained. Finally we propose two mathematical measures that can be incorporated to the optimization process to contribute to the evaluation of its performance.

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AlgorithmsBrain MappingElectroencephalographyHumansMagnetoencephalographyMathematicsModels, NeurologicalJournal Article

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BibTeXRIS

D Cabrera Fernández, R Grave de Peralta Menéndez, S L González Andino. 1995. Some limitations of spatio temporal source models.. https://doi.org/10.1007/bf01202382

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