Biomedical subjects

R Biscay-Lirio

Publications and source records attributed to R Biscay-Lirio.

4 recordsLinked to original sources

PubMed1995

The estimation of event related potentials affected by random shifts and scalings.

There is considerable evidence for trial to trial variability of the event related potentials (ERPs) within a given subject's recording. This variability influences the outcome of usual procedures in ERP analysis. Better results may be obtained if the sources of variability are explicitly taken into account in an appropriate model. This paper considers a probabilistic model, the random shift and scaling (RSS) model, where the response is modified by a random time shift and a random scale factor. In addition to this, an additional random scale factor which affects both the response and the background noise is taken into account. This time shift and these scale factors are handled as nuisance parameters. Maximum likelihood and least squares estimators of these parameters and the waveform of response are derived for the RSS model. It is shown that the Woody estimate of the ERP reported in earlier work can be derived by restricting the assumptions for the RSS model. Test statistics for hypotheses on means are obtained for the RSS model and a new type of discriminant function. The usefulness of the method is illustrated by means of simulation studies. Receiver operating characteristic (ROC) curves are used to demonstrate that the new type of discriminant performs better than the usual Fisher's Linear Discriminant.

Artifacts↗

PubMed1993

Spatial resolution of neuronal generators based on EEG and MEG measurements.

A unique solution to the electromagnetic inverse problem of neurophysiology does not exist due to the fact that scalp measurements of electric potential differences and of magnetic field components contain only partial information about the sources. Three different information functionals are introduced in this paper and are based on the following intuitive ideas, where the amount of information is: (1) Directly related to the amount of change in the measurements due to a very small change in the source; (2) Directly related to the angle between two sets of measurements corresponding to two different sources; and (3) Inversely related to the distance between the minimum norm inverse solution and the actual source. These definitions are used for comparing the source resolution of EEG and MEG in an inhomogeneous spherical head model. The main conclusion is that in many realistic situations electric measurements are more informative than magnetic measurements.

Brain↗

PubMed1992

Model parameters estimation when the evoked potential recordings are affected by a random scale factor.

In many situations an important source of the average evoked potentials (EPs) variability is a random scale factor affecting each recording. As a result, the outcome of any EP detection method may be greatly affected. However, using an appropriate probabilistic model these scale factor can be estimated, and the performance of any available detection index improved by data rescaling. In this paper the Maximum Likelihood Estimators of the waveform of the response and the scale factor affecting both background noise and this waveform are obtained. Also, an iterative algorithm for model parameters estimation is presented and its convergence is examined in a simulation study. The Linear Discriminant function is computed using simulated test data in both situations, before and after rescaling of recordings. The performance of these statistics is evaluated by mean of ROC curves.

Algorithms↗

PubMed1988

Current source density estimation and interpolation based on the spherical harmonic Fourier expansion.

A method for the spatial analysis of EEG and EP data, based on the spherical harmonic Fourier expansion (SHE) of scalp potential measurements, is described. This model provides efficient and accurate formulas for: (1) the computation of the surface Laplacian and (2) the interpolation of electrical potentials, current source densities, test statistics and other derived variables. Physiologically based simulation experiments show that the SHE method gives better estimates of the surface Laplacian than the commonly used finite difference method. Cross-validation studies for the objective comparison of different interpolation methods demonstrate the superiority of the SHE over the commonly used methods based on the weighted (inverse distance) average of the nearest three and four neighbor values.

Brain↗